Oxford Textbook of

Cognitive Neurology and Dementia

Oxford Textbooks in Clinical Neurology


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Oxford Textbook of

Cognitive Neurology and Dementia

Edited by

Masud Husain

Professor of Neurology & Cognitive Neuroscience, Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, UK

Jonathan M. Schott

Reader in Clinical Neurology, Dementia Research Centre, Department of Neurodegenerative Diseases, UCL Institute of Neurology, UK

Series Editor

Christopher Kennard



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Cognitive neurology, or behavioural neurology as it is known in the United States, has a reputation of being a complex sub- specialty. To the outsider it presents a formidable challenge, seemingly requiring knowledge of several di erent areas of expertise ranging from basic aspects of neuroscience—molecular, cognitive, and neuroimaging—through to neuropsychology, neuropsychiatry, and bedside neurological assessment. Even for experts, the dramatic growth of basic neuroscience research in these areas has meant that it can be extremely di cult to keep up with new developments or key conceptual advances. Perhaps more challenging still is to know how such advances can best be applied in practice when confronted with a patient with a cogni- tive complaint.

Our aim in producing this textbook is to bring some order to the apparent chaos for both the novice and those established in the eld. While there are several excellent texts that selectively cover either dementia or the neuroscience underlying cognitive disor- ders, we wanted to produce a modern, pragmatic resource that covers both these areas in an accessible manner for clinicians. Our second objective was to produce a textbook that spans diverse areas of expertise in an integrated fashion. Wherever possible, therefore,

we have tried to link information in chapters on basic sciences to those on clinical syndromes.

e text is rmly based on the clinical approach to the patient with cognitive impairment and dementia, but it also provides essential background knowledge that is fundamental to clinical practice. It is written for those who want to learn more about cog- nition and dementia, including neurologists, geriatricians, and psy- chiatrists who are involved in assessing and treating such patients, but also for others curious to nd out about cognitive disorders and their underlying neurobiology. We hope that, whatever your background, you will nd this the one essential textbook that you want to revisit.

Bringing together such a diverse range of information has been a challenge for us. We are extremely grateful to our contributors for being so considerate in taking up our suggestions for changes to their manuscripts and for their patience. Finally, we acknowl- edge with thanks the forbearance of our families who observed our involvement in this project with much more than tolerance and grace.

Masud Husain Jonathan M. Schott

Abbreviations ix Contributors xv



Cognitive dysfunction

10 Bedside assessment of cognition 105 Seyed Ahmad Sajjadi and Peter J. Nestor

11 Neuropsychological assessment 113 Diana Caine and Sebastian J. Crutch

12 Acquired disorders of language and speech 123 Dalia Abou Zeki and Argye E. Hillis

13 Memory disorders 135
Lara Harris, Kate Humphreys, Ellen M. Migo, and Michael D. Kopelman

14 Vision and visual processing de cits 147 Anna Katharina Schaadt and Georg Kerkho

15 Disorders of attentional processes 161 Paolo Bartolomeo and Ra aella Migliaccio

16 Apraxia 173 Georg Goldenberg

17 Acquired calculation disorders 183 Marinella Cappelletti

18 Disorders of reading and writing 189 Alexander P. Le

19 Neuropsychiatric aspects
of cognitive impairment
197 Dylan Wint and Je rey L. Cummings

Normal cognitive function

. 1  Historical aspects of neurology 3 Charles Gross

. 2  Functional specialization and network connectivity in brain function 17 Giovanna Zamboni

. 3   e frontal lobes 27
Teresa Torralva, Ezequiel Gleichgerrcht, Agustin Ibañez, and Facundo Manes

. 4   e temporal lobes 39
Morgan D. Barense, Jason D. Warren, Timothy J. Bussey, and Lisa M. Saksida

. 5   e parietal lobes 51 Masud Husain

. 6   e occipital lobes 59 Geraint Rees

. 7   e basal ganglia in cognitive disorders 69 James Rowe and Timothy Rittman

. 8  Principles of white matter organization 81 Marco Catani

. 9  Neurochemistry of cognition 91 Trevor W. Robbins


viii contents


Cognitive impairment and dementia

. 20  Epidemiology of dementia 211 ais Minett and Carol Brayne

. 21  Assessment and investigation of
the cognitively impaired adult
Jonathan M. Schott, Nick C. Fox, and Martin N. Rossor

. 22  Delirium, drugs, toxins 231
Barbara C. van Munster, Sophia E. de Rooij, and Sharon K. Inouye

. 23  CNS infections 239
Sam Nightingale, Benedict Daniel Michael, and Tom Solomon

. 24  Metabolic dementia 253
Nicholas J.C. Smith and Timothy M. Cox

. 25  Vascular cognitive impairment 275 Geert Jan Biessels and Philip Scheltens

. 26  Cerebral amyloid angiopathy
and CNS vasculitis
Sergi Martinez-Ramirez, Steven M. Greenberg, and Anand Viswanathan

. 27  Cognition in multiple sclerosis 295 Maria A. Ron

. 28  Autoimmune encephalitis 299
Sarosh R. Irani, omas D. Miller, and Angela Vincent

. 29  Pathology of degenerative dementias 315 Tamas Revesz, Tammaryn Lashley, and Janice L. Holton

. 30  Genetics of degenerative dementias 329 Rita Guerreiro and Jose Bras

. 31  Other genetic causes of cognitive impairment 339
Davina J. Hensman Moss, Nicholas W. Wood, and Sarah J. Tabrizi

32 Changing concepts and new de nitions for Alzheimer’s disease 353
Bruno Dubois and Olga Uspenskaya-Cadoz

33 Presentation and management of Alzheimer’s disease 361
Susan Rountree and Rachelle S. Doody

34 Primary progressive aphasia 381 Jonathan D. Rohrer and Jason D. Warren

35 Frontotemporal dementia 391 Bruce Miller and Soo Jin Yoon

36 Dementia with Lewy bodies and Parkinson’s disease dementia 399
Haşmet A. Hanağası, Başar Bilgiç, and Murat Emre

37 Corticobasal degeneration, progressive supranuclear palsy, multiple system atrophy, argyrophilic grain disease,
and rarer neurodegenerative diseases
413 Elizabeth A. Coon and Keith A. Josephs

38 Prion diseases 425
Simon Mead, Peter Rudge, and John Collinge

39 Traumatic brain injury 435
David J. Sharp, Simon Fleminger, and Jane Powell

40 Neurosurgery for cognitive disorders 453 Tom Foltynie and Ludvic Zrinzo

41 Cognition in severe mental
illness: Schizophrenia, bipolar disorder, and depression
Philip D. Harvey and Christopher R. Bowie

Index 471

3C ree-City Study
5-CSRTT 5-choice serial reaction time task 5-HIAA 5-hydroxyindoleacetic acid
5-HT Serotonin
Aβ amyloid β
ABCA ATP-binding cassette
ACA Anterior cerebral artery
ACC Anterior cingulate circuit
ACE–R Addenbrooke’s Cognitive Examination

Ach Acetylcholine

AChE Acetylcholinesterase inhibitors AD Alzheimer’s disease
ADC Apparent di usion coe cient ADEAR Alzheimer’s Disease Education &

Referral Center
ADHD Attention de cit/hyperactivity disorder

ADL Activities of daily living AE Autoimmune encephalitis AEDs Antiepileptic drugs

. AF  Arcuate fasciculus

. AG  Argyrophilic grains

AGD Argyrophilic grain disease
AI Anterior insula
AIP Anterior intraparietal sulcus
ALS amyotrophic lateral sclerosis AMACR α-Methylacyl-CoA
aMCI amnesic mild cognitive impairment AMPA α-amino-3-hydroxy-5-methyl-4-

isoxazolepropionic acid AMTS Abbreviated Mental Test Score

Ang Angular gyrus
ANI Asymptomatic neurocognitive impairment AOS Apraxia of speech
APA American Psychiatric Association
APGBD Adult polyglucosan body disease

. APO  Apolipoprotein

. APP  Amyloid precursor protein

ARSACS Autosomal recessive spastic ataxia of

Charlevoix–Saguenay ART Antiretroviral therapy

ASYMAD Asymptomatic AD

ATP Adenosine 5′-triphosphate ATXN Ataxin
AWD Alcohol-withdrawal delirium BACE Beta secretase

BIBD Basophilic inclusion body disease
BIC Binding of item and context
BIN Bridging integrator
BIRT Brain Injury Rehabilitation Trust
BMIPB BIRT Memory and Information Processing

BOLD Blood oxygenation level dependent

BORB Birmingham Object Recognition Battery BPSD Behavioural and psychological symptoms

of dementia
BSE Bovine spongiform encephalopathy

bvFTD Behavioural variant frontotemporal dementia

CAA Cerebral amyloid angiopathy CAA-RI CAA-related in ammation CADASIL Cerebral autosomal dominant

arteriopathy with subcortical infarcts and

CAG Cytosine–adenine–guanine

CAM Confusion Assessment Method CAMCOG–R Cambridge Cognition–Revised CAMDEX Cambridge mental disorders of the older

population examination
CANTAB Cambridge Automatic Neuropsychological

Test Battery
CARASIL Cerebral autosomal recessive

arterioapthy with subcortical infarcts and

CASPR2 Contactin-associated protein 2

CASS Cas sca olding
CAT Computed axial tomography CBD Corticobasal degeneration cblC Cobalamin C disease

. CBS  Corticobasal syndrome

. CBT  Cognitive behaviour therapy

CC75C Cambridge City over-75s

Cohort Study
CCAS Cerebellar cognitive a ective syndrome




CERAD Consortium to Establish a Registry of EF Alzheimer’s Disease EL

CFS–NMT Cramp-fasciculation ELSA syndrome–neuromyotonia EMEA

ChE-Is Cholinesterase inhibitors EMG CI Con dence interval EPESE CIS Clinically isolated syndrome
CJD Creutzfeld–Jakob disease EMP CLS Complementary learning system ESCRT CLU Clusterin

CMB Cerebral microbleed ETV CNS Central nervous system EWS CoA Coenzyme A FA CPAP Continuous positive airway pressure FAB CPE CNS penetration e ectiveness FAD CR Complement component receptor FBD CRAFT Convergence, Recollection, and FBDS

Familiarity eory FCSRT CRF Corticotrophic releasing factor FDA CRT Cognitive remediation therapy FDD CS Contention scheduler FDG

CS Contrast sensitivity FDOPA cSAH Subarachnoid blood in the convexity FEF CSHA Canadian Study of Health and Aging FEP
CSF Cerebrospinal uid FERM CT Computed tomography FFA CTE Chronic traumatic encephalopathy FFI CTSD Cathepsin D FIQ CVLT California verbal learning test FLAIR DA Dopamine fMRI DAI Di use axonal injury FMRIB DALY Disability-adjusted life years FRDA DAN Dorsal attentional network FSL DAT Dopamine transporter FTA-Abs DDA Direct detection assay FTD DHA Docosahexanoic acid FTLD DIAN Dominantly Inherited Alzheimer Network FTLD-t DIR Double inversion recovery FTLD-u DIs Dystrophic neurites FUS DLB Dementia with Lewy bodies GABA DL-PFC Dorsolateral prefrontal circuit GAD DM Decision making GBA DMN Default mode network GBD DMTs Disease modifying therapies GBE DMTS Delayed-matching-to-sample GCIs DPVS Dilated perivascular spaces GCL DRPLA Dentatorubral-pallidoluysian atrophy GCS DRS Dementia rating scale GDNF DSM Diagnostic and Statistic Manual GFAP DTI Di usion tensor imaging GHD DTX Dendrotoxin GLM DWI Di usion-weighted imaging Gpe

EC Entorhinal cortex Gpi
ECF Extracytoplasmic function GMS/AGECAT EClipSE Epidemiological Clinicopathological Studies

in Europe
ECT Electroconvulsive therapy GRE

EDS Excessive daytime sleepiness GSS EEG Electro-encephalography GWAS

Executive functions
Encephalitis lethargica
English Longitudinal Study of Ageing European Medicines Agency Electromyogram
Established Populations for Epidemiologic Studies of the Elderly
Epilepsy, progressive myoclonus Endosomal-sorting complex required
for transport
Endoscopic third ventriculostomy
Ewing’s sarcoma protein
Fractional anisotropy
Frontal assessment battery
Flavin adenine dinucleotide
Familial British dementia
Faciobrachial dystonic seizures
Free and Cued Selective Reminding Test Food and Drug Administration
Familial Danish dementia Fluorodeoxyglucose
18F- uorodopa
Frontal eye elds
First episode psychosis
Fusiform face area
Fatal familial insomnia
Full-scale IQ
Fluid-attenuated inversion recovery Functional magnetic resonance imaging Functional MRI of the Brain
Friedreich’s ataxia
FMRIB So ware Library
Fluorescent treponemal antibody-absorption Frontotemporal dementia
Frontotemporal lobar degeneration Frontotemporal degeneration-tau Frontotemporal degeneration-ubiquitin Fused-in-sarcoma
Gamma aminobutyric acid
Glutamic acid decarboxylase Glucoserebrosidase
Global Burden of Disease
Glycogen brancher enzyme
Glial cytoplasmic inclusions
Granule cell layer
Glasgow Coma Scale
Glial-derived neurotrophic factor
Glial brillary acidic protein
Growth hormone de ciency
General linear model
Global pallidus external
Globus pallidus internal
Geriatric Mental State Examination/ Automated Geriatric Examination Computer Assisted Taxonomy
Gradient-recalled echo Gerstmann–Sträussler syndrome Genome-wide association studies

1H-MRS Proton magnetic resonance spectroscopy HAD HIV-associated dementia
HADS Hospital Anxiety and Depression Scale HANDs HIV-associated neurocognitive disorders HCV Hepatitis C virus

HD Huntington’s disease
HDL Huntington’s disease-like syndrome
HIC High-income countries
HIV Human immunode ciency virus
HIVE HIV encephalopathy
HMG-CoA Hydroxy-3-methylglutaryl-coenzyme A
HR Hazard ration
HRT Hormone replacement therapy
HSV Herpes simplex virus
HTLV Human T-lymphotropic virus
IBMPFD Inclusion body myopathy with Paget disease

of the bone and frontotemporal dementia IBVM 123I-iodobenzovesamicol

ICA Independent component analysis
ICD International Classi cation of Diseases ICDs Impulse control disorders
ICH Intracerebral haemorrhages
iCJD Iatrogenic CJD
ICN Intrinsic connectivity networks
ICU Intensive care unit
IDED Intra- and extra-dimensional
IFOF Inferior fronto-occipital fasciculus IGF-II Insulin-like growth factor II
Ig Immunoglobulin
IGT Iowa Gambling Task
ILF Inferior longitudinal fasciculus
ILSA Italian Longitudinal Study of Ageing IPD Inherited prion disease
IPL Inferior parietal lobule
IPS Intraparietal sulcus
IRIS Immune reconstitution in ammatory

IT Inferotemporal

IWG International Working Group
JC John Cunningham
LAMIC Low and medium-income countries LDX Lisdexanphetamine dimesylate

LE Limbic encephalopathy
LGI1 leucine-rich glioma inactivated 1
LOC Lateral occipital cortex
LP Lumbar puncture
LPA Logopenic progressive aphasia
LTD Long-term depression
LTM Long-term memory
LTOCs long-term observational controlled studies LTP Long-term potentiation
M4PA Methyl-4-piperidyl acetate
MAPT Microtubule-associated tau
MATRICS Measurement and Treatment Research for

Improving cognition in schizophrenia MB Microbleeds

MBD Marchiafava–Bignami disease
MCA Middle cerebral artery
MCCB MATRICS consensus cognitive battery




nbM NCIs NE nfvPPA






Mild cognitive impairment
Minimially conscious state
Multiple demand
Myocyte enhancer factor Magnetoencephalography
Mitochondrial encephalopathy lactic acidosis and stroke-like episodes Myoclonic epilepsy with ragged red bres Metaiodobenzylguanidine

Multi-infarct dementia
Medial intraparietal sulcus Methylmalonic acid Mini-Mental State Examination Mild neurocognitive impairment Motor neurone disease

Montreal Neurological Institute Montreal Cognitive Assessment Medial occipitoparietal junction Morvan’s syndrome Methylphenidate

Medical Research Council
Medical Research Council’s cognitive function and ageing study
Magnetic resonance imaging
Magnetic resonance spectroscopy Multiple sclerosis
Multiple system atrophy
Mental state examination
Maple-syrup urine disease
Middle temporal gyrus Methylenetetrahydrofolate reductase Medial temporal lobes
N-acetyl aspartate/Creatinine Noradrenaline
National Adult Reading Test Normal-appearing white matter Neurodegeneration with brain iron accumulation
Nucleus basalis of Meynert
Neuronal cytoplasmic inclusions Norepinephrine
Non- uent variant primary progressive aphasia
Nerve growth factor
National Institute for Health and Care Excellence
Neuronal intermediate lament inclusion disease
Neuronal intranuclear inclusions National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association
National Institute of Neurologic Disease and Stroke
NMDA receptor
Neuropsychiatric Inventory

abbreviations xi



NPH Normal pressure hydrocephalus PVS NSAbs Neuronal surface-directed antibody PVS OFC Orbitofrontal circuit RA OMPFC Orbitomedial prefrontal cortex RAVLT OMS Opsoclonus-myoclonus syndrome RBD OPRI Octapeptide repeat insertion mutation rCBF OR Odds ration RCT OTC Ornithine transcarbamylase REM PACS Primary angiitis of the central RMT

nervous system ROI PANDA Parkinson neuropsychometric dementia ROS assessment RPD Paquid Personnes âgées QUID RPR

PAS Periodic acid–Schi RRMS PASAT Paced auditory serial addition test RSN PCA Posterior cerebral artery rtQUIC PCA Posterior cortical atrophy

PCA Principal component analysis SAG
PCR Polymerase chain reaction SAS PD-CRS PD Cognitive Rating Scale SCA
PDD Parkinson’s disease with dementia sCJD
PEF Parietal eye elds SCLC PERM Progressive encephalomyelitis with rigidity SCOPA-Cog

and myoclonus
PET Positron emission tomography SD

PFC Prefrontal cortex SDAT PFNA Progressive non uent aphasia SE PiB Pittsburgh Compound-B SEC PICALM Phosphatidylinositol binding clathrin SI

assembly protein SLC PiD Pick’s disease SLF

PIGD Postural-instability gait di culty SMA PIQ Performance IQ Smg PLEDS Periodic lateralizing epileptiform discharges SN PML Progressive multifocal leukoencephalopathy SNP PNFA Progressive non- uent aphasia SNpc PNS Peripheral nerve hyperexcitability SNpr PPA Parahippocampal place area SNr PPA Primary progressive aphasia SNRIs PPC Posterior parietal cortex

PPMS Primary progressive MS SO PPN Pedunculopontine nucleus SOL PPT-1 Palmitoyl-protein thioesterase 1 SORL PPVT Peabody picture vocabulary test SPECT PrP Prion protein

PSA Potential support ratio SPL PSEN Presenilin SPM PSIR Phase-sensitive inversion recovery SPMS PSP Progressive supranuclear palsy SPS PSP–CBS PSP–corticobasal syndrome SPSMQ PSP–CSTD PSP–corticospinal tract dysfunction Spt PSP–P PSP–parkinsonism SS PSP–PAGF PSP–pure akinaesia with gait freezing SSI PSP–PPAOS PSP–primary progressive apraxia of speech SSPE PSP–RS PSP–Richardson’s syndrome SSRI PSTI Pancreatic secretory trypsin inhibitor SSRT PTA Post-traumatic amnesia STG PTK Protein tyrosine kinase STM PTSD Post-traumatic stress disorder STN

Persistent vegetative state Prominent perivascular spaces Retrograde amnesia
Rey auditory verbal learning test REM sleep behaviour disorder Regional cerebral blood ow Randomized controlled trial Rapid eye movement Recognition memory test Regions of interest

Reactive oxygen species
Rapidly progressive dementia
Rapid plasma reagin
Relapsing and remitting MS
Resting state network
Real-time Quaking-Induced
Conversion Assay
Supervisory attentional gateway Supervisory attentional system Spinocerebellar ataxia
sporadic CJD
Small cell lung cancer
SCales for Outcomes of PArkinson’s disease-cognition
Semantic dementia
Senile dementia of Alzheimer type
status epilepticus
Structured event complex Stimulus-independent
Solute carrier
Superior longitudinal fasciculus Supplementary motor area
Supramarignal gyrus
Salience network
Single nucleotide polymorphism Substantia nigra pars compacta
Substantia nigra pars reticulata
Substantia nigra Serotonin-norepinephrine reuptake inhibitors
Space-occupying lesion
Sortilin-related receptor
Single photon emission computed tomography
Superior parietal lobule
Statistical parametric mapping
Secondary progressive MS
Sti -person syndrome
Short portable mental status questionnaire Sylvian parietotemporal
Super cial siderosis
Small subcortical infarct
Subacute sclerosing panencephalitis Selective serotonin reuptake inhibitors Stop-signal reaction time
Superior temporal gyrus
Short-term memory
Subthalmic nucleus

STRIVE STandards for ReportIng Vascular changes VaMCI on nEuroimaging VAN STS Superior temporal sulcus VBM SVD Small vessel disease VCD

svPPA Semantic variant primary progressive VCI aphasia vCJD

SWI Susceptibility-weighted images VDRL tACS Transcranial alternating current stimulation VENs TAF TATA-binding protein-associated factor VFD TCA Tricarboxylic acid VGKC TCMA Transcortical motor aphasia VIP tDCS Transcranial direct current stimulation vIPS TDP TAR DNA-binding protein VIQ TFND Transient focal neurological de cits VL TMS Transcranial magnetic stimulation VLSM ToM eory of Mind

TPHA treponema pallidum haemaglutination assay VOSP TPPA treponema pallidum particle agglutination VTA

. TPI  treponema pallidum immobilization VVS

. TPJ  Temporoparietal junction VWFA

TRD Treatement-resistant depression WAIS TREM Triggering receptor expressed on WCST

myeloid cells WHO
Uf Uncinate fasciculus WHOSIS

UHDRS Uni ed Huntington’s Disease Rating Scale WMH V1 Primary visual cortex WRAT VA Ventral anterior YLD VaD Vascular dementia YLL

MCI of vascular origin
Ventral attentional network Voxel-based morphometry
Vascular cognitive disorder
Vascular cognitive impairment variant CJD
Venereal disease research laboratory Von Economo neurons
Visual eld disorders
Voltage-gated potassium channel Vasoactive intestinal polypeptide Ventral intraparietal sulcus
Verbal IQ
Voxel-based lesion symptom mapping
Visual object and space perception Ventral tegmental area
Ventral visual stream
Visual word form area
Wechsler Adult Intelligence Scale Wisconsin Card Sorting Test
World Health Organization
WHO Statistical Information Systems White matter MRI hyperintensities Wide Range Achievement Test
Years lost due to disability
Years of healthy life lost

abbreviations xiii

Dalia Abou Zeki, Johns Hopkins University School of Medicine, Baltimore, USA

Morgan D. Barense, University of Toronto, Canada; Rotman Research Institute, Baycrest Hospital, Toronto, Canada

Paolo Bartolomeo, INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), Pitié- Salpêtrière Hospital, Paris, France

Geert Jan Biessels, Department of Neurology, Brain Centre Rudolf Magnus, University Medical Centre, Utrecht, e Netherlands

Başar Bilgiç, Associate Professor of Neurology, Istanbul University, Istanbul Faculty of Medicine, Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul, Turkey

Christopher R. Bowie, Departments of Psychology and Psychiatry, Queens University Kingston, Ontario, Canada

Jose Bras, Department of Molecular Neuroscience, Institute of Neurology, University College London, UK

Carol Brayne, Department of Public Health & Primary Care, University of Cambridge, UK

Timothy J. Bussey, Department of Psychology, University of Cambridge, UK; MRC and Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK

Diana Caine, Department of Neuropsychology, National Hospital for Neurology and Neurosurgery, London, UK

Marinella Cappelletti, Department of Psychology, Goldsmiths College, University of London, UK; UCL Institute of Cognitive Neuroscience, UK

Marco Catani, NatBrainLab, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK

John Collinge, MRC Prion Unit, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology and NHS National Prion Clinic, National Hospital for

Neurology and Neurosurgery, UCL Hospitals NHS Foundation Trust, UK

Elizabeth A. Coon, Assistant Professor and Consultant of Neurology, Division of Autonomic Neurology, Mayo Clinic, Rochester, USA

Timothy M. Cox, Department of Medicine, University of Cambridge, UK

Sebastian J. Crutch, Dementia Research Centre, UCL Institute of Neurology, UK

Je rey L. Cummings, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, USA

Rachelle S. Doody, Professor, Baylor College of Medicine, Department of Neurology, Houston, USA

Bruno Dubois, Dementia Research Center (IM2A) and Behavioral Unit, Salpêtrière University Hospital, Université Pierre et Marie Curie, Paris, France

Murat Emre, Professor of Neurology, Istanbul University, Istanbul Faculty of Medicine, Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul, Turkey

Simon Fleminger, Department of Neuropsychiatry, Institute of Psychiatry, King’s College London, UK

Tom Foltynie, Senior Lecturer & Honorary Consultant Neurologist, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, UK

Nick C. Fox, Dementia Research Centre, Department of Neurodegenerative Diseases, UCL Institute of Neurology, UK

Ezequiel Gleichgerrcht, Department of Neurology and Neurosurgery, Medical University of South Carolina, USA

Georg Goldenberg, Department of Neurology, Technical University Munich, Germany

Steven M. Greenberg, Hemorrhagic Stroke Research Program, Massachusetts General Hospital, USA




Charles Gross, Department of Psychology and Princeton Neuroscience Institute, Princeton University, USA

Rita Guerreiro, Department of Molecular Neuroscience, Institute of Neurology, University College London, UK

Haşmet A. Hanağası, Professor of Neurology, Istanbul University, Istanbul Faculty of Medicine, Department of Neurology, Behavioral Neurology and Movement Disorders Unit, Istanbul, Turkey

Lara Harris, King’s College London, Institute of Psychiatry, Psychology and Neuroscience, UK

Philip D. Harvey, Leonard M. Miller Professor of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, USA

Davina J. Hensman Moss, Clinical Fellow, Department of Neurodegenerative Disease, UCL Institute of Neurology and National Hospital for Neurology and Neurosurgery, UK

Argye E. Hillis, Professor of Neurology, Executive Vice Chair, Dept. of Neurology, Director, Cerebrovascular Division, Johns Hopkins University School of Medicine, Baltimore, USA

Janice L. Holton, Queen Square Brain Bank for Neurological Disorders, UCL Institute of Neurology, UK

Kate Humphreys, South London and Maudsley NHS Foundation Trust, UK

Masud Husain, Professor of Neurology & Cognitive Neuroscience, Nu eld Department of Clinical Neurosciences, University of Oxford, John Radcli e Hospital, UK

Agustin Ibañez, Institute of Translational and Cognitive Neuroscience (ITCN), Ineco Foundation, Favaloro University, Buenos Aires, Argentina; University Adolfo ibañez, Chile; Centre of Excellence in Cognition and its Disorders, Australian Research Council (ACR), Sydney, Australia

Sharon K. Inouye, Aging Brain Center, Institute for Aging Research, Hebrew SeniorLife, Boston, USA; Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA

Sarosh R. Irani, Honorary Consultant Neurologist and Senior Clinical Fellow, Nu eld Department of Clinical Neurosciences, University of Oxford, UK

Keith A. Josephs, Professor and Consultant of Neurology, Divisions of Behavioural Neurology & Movement Disorders, Mayo Clinic, Rochester, USA

Georg Kerkho , Saarland University Department of Psychology, Clinical Neuropsychology Unit and Neuropsychological Outpatient Service, Campus Saarbrücken, Germany

Michael D. Kopelman, King’s College London, Institute of Psychiatry, Psychology and Neuroscience, UK

Tammaryn Lashley, Queen Square Brain Bank for Neurological Disorders, UCL Institute of Neurology, UK

Alexander P. Le , Reader in Cognitive Neurology and Honorary Consultant Neurologist, Institute of Neurology & National Hospital for Neurology and Neurosurgery, University College London, UK

Facundo Manes, Institute of Translational and Cognitive Neuroscience (ITCN), Ineco Foundation, Favaloro University, Buenos Aires, Argentina; UDP-INECO Foundation Core on Neuroscience (UIFCoN), Diego Portales University, Santiago, Chile; Australian Research Council (ACR) Centre of Excellence in Cognition and its Disorders, Sydney, Australia, National Scienti c and Technical Research Council (CONICET), Buenos Aires, Argentina

Sergi Martinez-Ramirez, Hemorrhagic Stroke Research Program, Massachusetts General Hospital, USA

Simon Mead, MRC Prion Unit, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology and NHS National Prion Clinic, National Hospital For Neurology and Neurosurgery, UCL Hospitals NHS Foundation Trust, UK

Benedict Daniel Michael, Post-Doctoral Research Fellow, Massachusetts General Hospital, Harvard Medical School; Institute of Infection and Global Health, University of Liverpool, UK; Walton Centre for Neurology and Neurosurgery, Liverpool, UK

Ra aella Migliaccio, INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, and Université Pierre et Marie Curie-Paris 6, UMR S 1127, Institut du Cerveau et de la Moelle épinière (ICM), and Department of Neurology, Institute of memory and Alzheimer’s disease, Pitié-Salpêtrière Hospital, Paris, France

Ellen M. Migo, King’s College London, Institute of Psychiatry, Psychology and Neuroscience, UK

Bruce Miller, Department of Neurology, UCSF School of Medicine, San Francisco, USA

omas D. Miller, Patrick Berthoud/Encephalitis Society Clinical Research Fellow, Nu eld Department of Clinical Neurosciences, University of Oxford, UK; Specialist Registrar in Neurology, National Hospital For Neurology and Neurosurgery, University College London, London, UK

ais Minett, Specialty Registrar in Radiology, Academic Clinical Fellow, Department of Radiology, University of Cambridge, UK

Barbara C. van Munster, Department of Internal Medicine, Academic Medical Centre, Amsterdam, The Netherlands; Department of Geriatrics, Gelre Hospitals, Apeldoorn, e Netherlands

Peter J. Nestor, German Centre for Neurodegenerative Diseases (DZNE), Magdeburg, Germany

Sam Nightingale, Institute of Infection and Global Health, University of Liverpool, UK

Jane Powell, Goldsmiths, University of London, UK Geraint Rees, UCL Institute of Cognitive Neuroscience, UK

Tamas Revesz, Queen Square Brain Bank for Neurological Disorders, UCL Institute of Neurology, UK

Timothy Rittman, Clinical Research Fellow, University of Cambridge, UK

Trevor W. Robbins, Professor of Cognitive Neuroscience and Experimental Psychology Director, Behavioural and Clinical Neuroscience Institute Head of Dept. Psychology, University of Cambridge, UK

Jonathan D. Rohrer, Dementia Research Centre, UCL Institute of Neurology, UK

Maria A. Ron, Emeritus Professor of Neuropsychiatry, UCL Institute of Neurology, UK

Sophia E. de Rooij, Department of Internal Medicine, Academic Medical Centre, Amsterdam, e Netherlands; Department of Internal Medicine, University Medical Centre Groningen, e Netherlands

Martin N. Rossor, Dementia Research Centre, Department of Neurodegenerative Diseases, UCL Institute of Neurology, UK

Susan Rountree, Associate Professor, Baylor College of Medicine, Department of Neurology, Houston, USA

James Rowe, Professor of Cognitive Neurology, University of Cambridge, UK

Peter Rudge, MRC Prion Unit, Department of Neurodegenerative Disease, University College London (UCL) Institute of Neurology and NHS National Prion Clinic, National Hospital For Neurology and Neurosurgery, UCL Hospitals NHS Foundation Trust, UK

Lisa M. Saksida, Department of Psychology, University of Cambridge, UK; MRC and Wellcome Trust Behavioural and Clinical Neuroscience Institute, University of Cambridge, UK

Seyed Ahmad Sajjadi, Neurology Department, Addenbrooke’s Hospital, Cambridge, UK

Anna Katharina Schaadt, Saarland University Department of Psychology, Clinical Neuropsychology Unit and Neuropsychological Outpatient Service, Campus Saarbrücken, Germany

Philip Scheltens, Alzheimer Centre and Department of Neurology, VU University Medical Centre, Neuroscience Campus Amsterdam, the Netherlands

Jonathan M. Schott, Reader in Clinical Neurology, Dementia Research Centre, Department of Neurodegenerative Diseases, UCL Institute of Neurology, UK

David J. Sharp, National Institute of Health (NIHR) Professor and Consultant Neurologist, e Computational, Cognitive and Clinical Neuroimaging Laboratory, Division of Brain Sciences, Imperial College London, UK

Tom Solomon, Institute of Infection and Global Health, University of Liverpool, UK; Walton Centre for Neurology and Neurosurgery, Liverpool, UK

Nicholas J.C. Smith, Department of Neurology, Women’s and Children’s Health Network and Discipline of Paediatrics, School of Medicine, University of Adelaide, Australia

Sarah J. Tabrizi, Professor of Clinical Neurology, Honorary Consultant Neurologist, Department of Neurodegenerative Disease, UCL Institute of Neurology and National Hospital for Neurology and Neurosurgery, UK

Teresa Torralva, Institute of Translational and Cognitive Neuroscience (ITCN), Ineco Foundation, Favaloro University, Buenos Aires, Argentina; UDP-INECO Foundation Core on Neuroscience (UIFCoN), Diego Portales University, Santiago, Chile; Australian Research Council (ACR) Centre of Excellence in Cognition and its Disorders, Sydney, Australia

Olga Uspenskaya-Cadoz, Quintiles; CNS Medical Strategy and Science; Levallois-Perret, France

Angela Vincent, Professor of Neuroimmunology and Honorary Clinical Immunologist, Nuffield Department of Clinical Neurosciences, University of Oxford, UK

Anand Viswanathan, Hemorrhagic Stroke Research Program, Massachusetts General Hospital, USA

Jason D. Warren, Dementia Research Centre, UCL Institute of Neurology, UK

Dylan Wint, Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, USA

Nicholas W. Wood, Galton Chair of Genetics, Vice Dean Research Faculty of Brain Sciences, NIHR UCLH BRC Neuroscience Programme Director, UCL Institute of Neurology, UK

Soo Jin Yoon, Associate Professor, Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, Korea

Giovanna Zamboni, Nu eld Department of Clinical Neurosciences (NDCN), University of Oxford, UK

Ludvic Zrinzo, Senior Lecturer & Consultant in Neurosurgery, Sobell Department of Motor Neuroscience, UCL Institute of Neurology, UK

contributors xvii


Normal cognitive function

Before science

consequently they are incapable of action if the brain is disturbed or shi s its position, for this stops up the passages through which senses act. is power of the brain to synthesize sensations makes it also the seat of thought: the storing up of perceptions gives memory and belief, and when these are stabilized you get knowledge.12

Alcmaeon is reported to have been the rst to use dissection as a tool for intellectual inquiry. He dissected the eye and described the optic nerves and chiasm and suggested they brought light to the brain.7–12

e Hippocratic school

e other centre of Greek medicine was the island of Cos in the Aegean Sea and its most famous inhabitant Hippocrates (~425 BCE). e Hippocratic corpus of writing is the rst large body of Western scienti c writings that has survived. It consists of over 60 treatises of unknown authorship and date, perhaps a remnant of the library which once existed on Cos.8

e Hippocratic treatise of greatest relevance to neurology is the famed essay ‘On the Sacred Disease’ (i.e. epilepsy). e author of this treatise has no doubt that the brain is the seat of epilepsy; on the general functions of the brain he is equally clear:

It ought to be generally known that the source of our pleasure, merri- ment, laughter and amusement, as of our grief, pain, anxiety and tears is none other than the brain. It is specially the organ which enables us to think, see, and hear and to distinguish the ugly and the beautiful, the bad and the good, pleasant and unpleasant . . . it is the brain too which is the seat of madness and delirium.13

Neurological and other disorders were explained and treated in terms of the theory of the four humours: phlegm (from the brain), blood (from the heart), yellow bile (from the liver), and black bile (from the spleen). ese ideas, as elaborated later by Galen (129– 210), pervaded medicine and were central to medical education well into the nineteenth century.7–10,13,14

Curiously, Aristotle (384–322 BCE) argued against the brain and in favour of the heart as the dominant organ for sensation, cogni- tion, and movement. He systematically attacked the encephalocen- tric views of Alcmaeon and the Hippocratic doctors on a number of anatomical and embryological grounds, but the critical evidence available at this time was from the clinic, the study of brain-injured humans, and clinical medicine held no interest for Aristotle.15


Galen of Pergamon (129–213) was by far the most important physician, anatomist, and physiologist in classical antiquity.14 Furthermore, he was the rst to carry out systematic experiments on the nervous system, thereby initiating experimental neurol- ogy.16 Galen’s descriptions of the gross anatomy of the brain were


Historical aspects of neurology

Charles Gross

e oldest known neurological procedure is trepanning or trephin- ing, the removal of a piece of bone from the skull. It was practised from the late Palaeolithic period onwards and throughout the world. e motivation for trephining in non-literate cultures is obscure but may have been related to the treatment of epilepsy or headaches caused by skull injury, or relief of symptoms thought to have been caused by demonic forces. From classical Greece to the Renaissance, trephining was used to treat such maladies as head injury, epilepsy, and mental disease.1,2

e rst written reference to the brain is in the Edwin Smith Surgical Papyrus written in about 1700 BCE but a copy of an older treatise dated to about 3000 BCE. It appears to be a handbook for a battle eld surgeon and consists of a coolly empirical description of 48 cases from the head down to the shoulders, when the text breaks o . For each case the author describes the examination, diagnosis, and feasibility of treatment.3,4 e Smith papyrus stands out as a rock of empiricism in the ocean of magic and superstition in which Egyptian medical writings swim for about the next twenty-four centuries. It re ects cra and some empirical knowledge but it is not what we today call medical science.

Classical neuroscience
e Presocratics and the beginning of science

What we mean by ‘science’ today is the contribution of the Presocratic philosophers. ey were responsible for the idea that the physical and biological universe is governed by consistent and universal laws that are amenable to understanding by human rea- son. is was a revolutionary change from the previous prevailing view of the universe as a plaything of gods and ghosts who acted in an arbitrary and capricious fashion. e Presocratics lived from the sixth to the fourth centuries BCE in various Greek city-states. ey conceived their inquiries on the universe as demanding rational criticism and public debate and involving observation and meas- urement. (Systematic experimentation, especially in biology, was almost unknown for several centuries).5–11

Among the major Presocratics were ales, Anaximander, Anaximenes, Heraclitus, Pythagoras, Empedocles, Zeno, and Democritus. Many of them were interested in sensory processes as sources of knowledge and several were physicians. One such physi- cian was Alcmaeon (~570–500 BCE), head of a medical school in southern Italy. He was the rst writer to advocate the brain as the site of sensation and cognition. He is said to have written:

e seat of sensations is in the brain. is contains the governing faculty. All the senses are connected in some way with the brain;

4 SECTION 1 normal cognitive function

Fig. 1.1 Title page of Galen’s Omnia Opera published in 1541 in Venice by Junta. e eight scenes, clockwise from the top, are: Galen bowing to a wealthy patient; Galen predicting the crisis in a patient’s sickness; Galen diagnosing lovesickness; Galen bleeding a patient; Galen demonstrating the e ect of cutting the recurrent laryngeal nerve in a pig; Galen palpating the liver; Galen and his teachers; Aesculpaius in a dream urging Galen’s father to send him to medical school.
Reproduced from Gross CG, Brain, Vision, Memory: Tales in the History of Neuroscience, Copyright (1999), with permission from MIT Press.

very accurate, particularly with respect to the ventricles and cer- ebral circulation, both important in his physiological system. He usually presented his dissections as if they were of the human, but in fact, because of the taboo on dissecting the human body, they were invariably of animals, usually the ox in the case of brain anatomy.17

Galen’s truly revolutionary work was to carry out the rst system- atic experiments on the functions of the nervous system. He used piglets in his experiments on brain lesions. He found that anterior brain damage had less deleterious e ects than posterior. He viewed sensation as a central process since he knew from his clinical obser- vations and animal experiments that sensation could be impaired

by brain injury even when the sense organs were intact. Since ani- mals could survive lesions that penetrated to the ventricles, Galen thought the soul was not located there but rather in the cerebral sub- stance. He taught that all mental diseases were brain diseases.16,18,19

Galen’s most famous experiment was the public demonstration of the e ects of cutting the recurrent laryngeal nerve on squealing in a pig. Although the encephalocentric view that the brain con- trolled sensation, movement, and cognition remained strong in the Greco–Roman medical community, the opposing cardiocen- tric view, that the heart was the centre of sensation and cognition, was also active in Rome at this time, being advocated by the Stoic school and its leader Chrysippus (280–207 BCE). In order to refute the Stoics’ view that the heart and not the brain controlled cogni- tion, Galen arranged this public demonstration.16,19

He showed that cutting the recurrent laryngeal nerve would eliminate vocalization. Since vocalization was seen as re ecting the cognitive activity language, Galen’s demonstration that cutting a nerve originating in the brain would eliminate squealing in a pig was the rst, and most famous, demonstration that the brain con- trols cognition. e Renaissance edition of Galen’s works included an engraving of him carrying out the experiment on a huge pig in front of a very distinguished audience (Fig. 1.1).

Medieval and Renaissance neuroscience e medieval doctrine of brain function

At about the time of Galen’s death, classical science and medicine seem to disappear. People prefer to believe rather than to discuss, critical faculty gives way to dogma, interest in this world declines in favour of the world to come, and worldly remedies are replaced by prayer and exorcism. e world view of medieval Christendom found Galen’s teleology congenial to its own and by a smothering of critical facility froze Galen’s research and all biology into a sterile system for over 1500 years. Galen was not to blame. Rather than develop his discoveries and methods, the European medieval world chose to accept his views as xed and unchangeable facts in every branch of medicine.

e central feature of the medieval view of brain function was the localization of the mental faculties in the ventricles (Fig. 1.2). e faculties of the mind (derived from Aristotle) were distributed among the spaces within the brain (derived from the ventricles described by Galen). e anterior ventricle received input from the sense organs and was the site of the common sense, which integrated across modalities. e sensations yielded images and thus fantasy and imagination were also located in the anterior ventricle. e middle ventricle was the site of cognition: reasoning, judgement, and thought. e posterior ventricle was the site of memory. ese speci c localizations seem to have come from the fourth-century Byzantine physician Poseidon on the basis of his observations of human brain injury.20,21

e Islamic transmission

Greek medical learning was largely preserved in Islamic centres in the early Middle Ages. Hippocratic, Galenic, and other medical writings were largely lost to Europe both because of lack of familiar- ity with Greek and loss of the manuscripts themselves. is began to change in the tenth and eleventh centuries when translations from the Greek medical works into Syriac, Arabic, and Hebrew, and then into Latin nally reached Europe.21 With the birth of universities, rst in Bologna, anatomical dissections began, initially for forensic

Fig. 1.2 Ventricular doctrine. Messages from the nose, tongue, eye, and ear go to the rst ventricle in which common sense, fantasy, and imagination are found. e second ventricle contains thought and judgment; memory is in the third ventricle. Reproduced from Reish G, Margarita Philosophica (Pearls of Philosophy), Copyright (1503), Johannes Schott.

purposes and following translations of Galen. However, it was not until Vesalius (1514–1564) that anatomy became largely free from the dominance of Galen. His On the Fabric of the Human Body (Fig. 1.3) along with Copernicus’s (1473–1543) On the Revolutions of the Celestial Spheres mark the beginning of the scienti c revolution, the revival in Europe of science.

omas Willis and ‘neurology’

omas Willis (1621–74) wrote the rst comprehensive text on the brain, Cerebri Anatomie, which dealt not only with brain anatomy but also with neurophysiology, neurochemistry, and clinical neu- rology, and introduced, in its English translation, the term ‘neu- rology’.22 Cerebri Anatomie actually involved the collaboration of a group of savants known as the Virtuosi, such as Robert Boyle and Christopher Wren, who later became founding members of the new Royal Society (see Fig. 1.4).

Willis rejected the still pervasive belief in the ventricles as the seats of higher psychological functions and instead implicated ‘the critical and grey part of the cerebrum’ in memory and will. Sensory signals came along sensory pathways into the corpus striatum where common sense was located. ey were then elaborated into percep- tion and imagination in the overlying white matter (then called the corpus callosum), and nally passed onto the cortex where they were stored as memories. Willis ascribed voluntary movements to the cortex but involuntary ones to the cerebellum. His ideas on brain function came from his own experiments on brain lesions in animals, from the correlation of the e ects of human brain dam- age with post-mortem pathology, and from the comparison of the brains of various animals with those of humans.22–24

Although Willis was a major gure in his time, his ideas on the cerebral cortex soon fell out of favour and theories of the cortex

CHAPTER 1 historical aspects of neurology 5

6 SECTION 1 normal cognitive function

Fig. 1.3 Title page of Andreas Vesalius’s De Humani Corpori Fabrica (On the Structure of the Human Body), 2nd edn.1543 Basel: Oporinus. It shows a public dissection by Vesalius (centre). His assistant is relegated to sharpening knives (front). e bodies were from executions and usually males, unlike here. e dissection is being held outdoors with a wooden structure for spectators. For further details of the symbols and details in this famous woodcut from Titian’s workshop, see CG Gross, Brain, Vision, Memory: Tales in the History of Neuroscience 1998. Cambridge, MA: MIT Press.

Reproduced from Gross CG, Brain, Vision, Memory: Tales in the History of Neuroscience, Copyright (1999), with permission from MIT Press.

as glandular or vascular became dominant. Marcello Malpighi (1628–94), the discoverer of capillaries, was the rst to examine the cortex under the microscope.24–25 He saw it as made up of little glands or ‘globules’, and Antoni van Leewenhoek (1632–1723) and others followed suit. is was a common view in the seventeenth

and eighteenth centuries, perhaps because it t with the much earlier view of Aristotle that the brain was a cooling organ and the Hippocratic theory that it was the source of phlegm.5,15 e other common view was that the cortex was largely made up of blood vessels; as Frederik Rusch (1628–1731) put it: ‘[t]he cortical

Fig. 1.4 Ventral view of the brain.
Reproduced from Willis T, Cerebri Anatomie, Copyright (1664), Martyn and Allestry, drawn by Christopher Wren.

substance of the cerebrum is not glandular, as many anatomists have described it … but highly vascular’.26 Albrecht von Haller (1708–77), who dominated physiology in the eighteenth century, also held a vascular view of the cortex. He found mechanical and chemical stimulation to be without e ect throughout the cortex and declared it completely insensitive.27

e beginning of modern neuroscience

Gall and phrenology: Localization of function

in the cortex

e revolutionary idea that di erent regions of the cerebral cortex have di erent function began with Franz Joseph Gall (1748–1828) and his collaborator, JC Spurzheim (1776–1832) and their system of phrenology.28–30

e central aim of phrenology was to correlate brain structure and function. Phrenology had ve basic assumptions:

1. e brain is an elaborately wired machine for producing behav- iour, thought, and emotions

2. e cerebral cortex is a set of organs each corresponding to an a ective or intellectual function

3. Di erences in traits among people and within individuals depend on di erential development of di erent cortical areas

4. Development of a cortical area is re ected in its size

5. Size of a cortical area is correlated with the overlying skull (‘bumps’)

ese otherwise reasonable hypotheses had one fatal aw: the nature of the evidence. Gall and Spurzheim relied almost entirely on obtaining supportive or con rmatory evidence. ey collected large numbers of skulls of people whose traits and abilities were known, examined the heads of distinguished savants and inhabit- ants of mental hospitals and prisons, and studied portraits of the high and low born on various intellectual and a ective dimensions (Fig. 1.5). roughout, they were seeking con rmation of their ini- tial hypothesis usually deriving from a few cases. For example, the idea for a language organ in the frontal lobes comes from Gall’s experience of a classmate who had a prodigious verbal memory and protruding eyes (being pushed out by a well-developed frontal lobe, Gall thought). e idea for an organ of destructiveness came from the skulls of a parricide and of a murderer, from noticing its prominence in a fellow student ‘who was so fond of torturing ani- mals that he became a surgeon’, and from examining the head of a meat-loving dog he owned.28

ey sought con rmations; contradictions were dismissed. Gall and Spurzheim’s cortical localizations were of ‘higher’ intellectual and personality traits. ey accepted the prevailing view that the highest sensory functions were in the thalamus and the highest motor functions in the corpus striatum.29,30

Phrenology met with considerable opposition from political and religious authorities, particularly on the Continent, largely because it was viewed as implying materialism and determinism and denied the unity of the mind (and soul) and the existence of free will. On the other hand, phrenology spread widely particularly in the United States and Great Britain both as a medical doctrine and as a form of

CHAPTER 1 historical aspects of neurology 7

8 SECTION 1 normal cognitive function

Fig. 1.5 e phrenological organs.
Reproduced from Human Nature Library, New York, Copyright (1887).

‘pop’ psychology. It generated widespread interest both among the general populace and among such writers and savants as Honore de Balzac, Charles Baudelaire, George Eliot, August Comte, Horace Mann, Alfred Russell Wallace, and George Henry Lewis. It rapidly became a fad and drawing-room amusement, particularly in Great Britain and the US. Phrenological societies and journals continued to ourish in both countries well into the twentieth century.31

Gall’s mistaken assumption of a correlation between the skull and brain morphology was soon recognized, at least in the scien- ti c community. In spite of its absurdities and excesses, phrenology became a major spur for the development of modern neurosci- ence in a variety of ways. It generated an interest in the brain and behaviour. It directed attention to the cerebral cortex. It stimulated study of both human brain damage and of experimental lesions in animals. It inspired tracing pathways from sense organs and to the muscles in order to identify ‘organs’ of the cerebral cortex. It spurred the anatomical subdivision of the cerebral cortex (cyto- architectonics, myeloarchitectonics) to nd organs of the brain.29,30

e cytoarchitectonic, positron emission tomography (PET), func- tional magnetic resonance imaging (fMRI), and other maps of the cerebral cortex that are now ubiquitous in neuroanatomy, neurophysi- ology, and neuropsychology textbooks bear more than a coincidental resemblance to phrenological charts. ey are the direct descend- ants of the iconoclastic, ambitious, and heavily awed programme of phrenology seeking to relate brain structure and behaviour.

Language and the brain

In the middle of the nineteenth century, Gall’s theory of punc- tate localization of function in the cerebral cortex continued to be debated. Reports of correlations between the site of brain injury

and speci c psychological de cits in patients as well as experimen- tal animals were published and actively discussed in both phreno- logical and mainstream medical publications.

e debate about localization reached a climax at a series of meet- ings of the Paris Societé d’Anthropologie in 1861. At the April meet- ing, Paul Broca (1824–80), professor at the Sorbonne and founder of the society, announced that he had a critical case on this issue. A patient with long-standing language di culties—nicknamed ‘Tam’, because that was all he could say—had just died. e next day, Broca displayed Tam’s brain at the meeting and it had widespread damage in the le frontal lobe. Over the next few months Broca presented several similar cases of di culty in speaking, all with le frontal lesions. is discovery was the rst clear evidence for a spe- ci c psychological defect a er a speci c brain lesion. Not only did these cases nally establish the principle of discrete localization of function in the cortex, but in addition, the discovery was hailed as a vindication of Gall: both of his idea of punctate localization and his localization of language in the frontal lobes.29,30,32

By 1865, Broca had accumulated enough cases to notice that all his brains from aphasic patients had their frontal damage on the le side and he described the le hemisphere as dominant for lan- guage.32,34 (An obscure country doctor, Max Dax, apparently made the same observations in 1836, and his son Gustave Dax fought Broca over the priority for this claim.)33

In 1874, Carl Wernicke reported another type of language dis- turbance a er le hemisphere lesions in which speech is uent but nonsensical, o en known as sensory or Wernicke’s aphasia, as opposed to motor or Broca’s aphasia. Whereas Broca’s aphasia usu- ally followed lesions of the third frontal convolution or Broca’s area, Wernicke’s aphasia usually followed damage to the posterior temporal

lobe. Today a variety of aphasias have been described with more sophisticated descriptive analysis than ‘motor’ versus ‘sensory’.34

It was generally assumed that language localization in le -handed individuals was the opposite of that in right-handers; that is, that language was in the right hemisphere in le -handed individuals. However, as pointed out by Alexander Luria on the basis of his large sample of head injuries in the Second World War, language is pri- marily in the right hemisphere in roughly half of all le -handers. is was con rmed by the Wada test (unilateral hemispheric anaes- thesia), and fMRI and PET brain imaging. Today we know that lan- guage localization in le -handers is some kind of complex function of genetics and prenatal trauma, and that bilateral representation of language is much more common in le -handers (and females). Furthermore, even in right-handers, a variety of language functions exist in the right hemisphere. Finally, le hemisphere damage before puberty can be compensated by right hemisphere function.35–37

e discovery of motor cortex

Modern neurophysiology began with Gustav Fritsch (1838–1927) and Edmund Hitzig’s (1838–1907) discovery in 1870 that stimu- lation of the motor cortex produces movement. eir discovery was the rst experimental evidence that the cortex was involved in movement, the rst demonstration that the cortex was electri- cally excitable, the rst strong experimental evidence for functional localization in the cortex, and the rst experimental evidence for somatotopic representation in the brain.

In their now classic experiment, Fritsch and Hitzig strapped their dogs down on Frau Hitzig’s dressing table. ey stimulated the cortex with ‘galvanic stimulation’: brief pulses of monophasic dir- ect current from a battery. e usual response to this stimulation was a muscle twitch or spasm. eir central ndings were that: a) the stimulation evoked contralateral movements, b) only stimu- lation of the anterior cortex elicited movements, c) stimulation of speci c parts of the cortex consistently produced the activation of speci c muscles, and d) the excitable sites formed a repeatable, if rather sparse, map of movements of the body laid out on the cortical surface (Fig. 1.6). ey went on to show that lesion of a particular site impaired the movements produced by stimulation of that site. e loss of function was not complete, suggesting to them that there were other motor centres that had not been impaired by the lesion.39

Fritsch and Hitzig had no hesitation in announcing the general signi cance of their discovery:

By the results of our own investigations, the premises for many con- clusions about the basic properties of the brain are changed not a little . . . some psychological functions, and perhaps all of them . . . need circumscribed centers of the cerebral cortex.39

Soon a er their paper appeared, the young Scottish physician David Ferrier set out to follow up their work.40 Ferrier had been heavily in uenced by John Hughlings Jackson, and he realized that Fritsch and Hitzig had con rmed Jackson’s ideas. In a variety of species, including macaques, Ferrier replicated their basic ndings that stimulation of the cortex can produce speci c movements and that there is a topographic ‘motor map’ in the cerebral cortex.41–44

Both Fritsch and Hitzig’s and Ferrier’s papers on the motor cortex were initially greeted with considerable and equal scepticism. eir results went against the generally accepted views that the striatum was the highest motor centre and that the cortex was inexcitable. e critics usually interpreted the results of Fritsch and Hitzig and of Ferrier as artefactual due to ‘spread of current’ to the striatum, then considered the highest motor centre. To overcome these criticisms,

Fig. 1.6 Movements produced by electrical stimulation of the cerebral cortex of the dog.
Notes: Δ, twitching of neck muscles; +, abduction of foreleg; †, exion of foreleg; #, movement of foreleg; □, facial twitching.

Reproduced from Fritsch GT, and Hitzig E, On the electrical excitability of the cerebrum [1870]. In: von Bonin G, trans., Some Papers on the Cerebral Cortex, Copyright (1960), with permission from Charles C omas.

Victor Horsley, Charles S Sherrington, and others began meticu- lous ‘punctate’ mapping of the cortex using the minimum current to elicit the smallest discernable movement.e.g. 45–47 Sherrington’s map of the motor cortex in the chimpanzee, followed by Wilbur Pen eld’s human motor homunculus and Clinton Woolsey’s maps of monkeys and other animals, became the standard picture of the motor cortex.48–50 Ferrier’s maps of the motor cortex in the macaque were applied surprisingly quickly to human brain sur- gery. Starting in 1876, the Scottish surgeon William McEwen and the London surgeon RJ Godlee used Ferrier’s maps to successfully locate and remove tumours.51

Recently, Michael Graziano has revisited Ferrier’s idea that the motor cortex may control complex, highly integrated behaviour.52

e neuron doctrine

e neuron doctrine—the idea that the nervous system is made up of discrete nerve cells that are the anatomical, physiological, genetic, and metabolic bases of its functions—may be viewed as the single-most important development in the entire history of neuro- science. e work of two men was crucial to the nal acceptance of the doctrine: Camillo Golgi (1843–1926) and Santiago Ramón y Cajal (1852–1934).53

Although eodor Schwann suggested, in 1838, that all animal tissues are made up of cells, the nervous system resisted interpret- ation in terms of cell theory for about another 50 years. is was because with the stains and microscopes available, the nervous sys- tem o en looked like an anastomosing network or ‘reticulum’. e resolution of this enigma came, eventually, from the discovery by

CHAPTER 1 historical aspects of neurology 9

10 SECTION 1 normal cognitive function

Fig. 1.7 Golgi’s drawing of the reticulum formed by axon collaterals in the dentate gyrus of the hippocampus.
Reproduced from Golgi C, e neuron doctrine–theory and facts. Nobel Lecture, 11 December 1906. In: Nobel Lectures Physiology or Medicine 1901–1921. Copyright (1999), with permission from the Nobel Foundation.

Golgi in 1873 of a new silver stain that stained only a small propor- tion of cells but did so in their entirety.53

Using this stain, Golgi a) con rmed Otto Deiters’s earlier obser- vation of a single axon (‘axis cylinder’) coming from each nerve cell, b) found that dendrites (‘protoplasmic prolongations’) ended freely, c) discovered axon collaterals and thought they merged with the axon collaterals of other nerve cells to form a di use reticu- lum, and d) classi ed nerve cells by their processes. Golgi believed that the function of dendrites was nutritive and not the conducting of messages. He had a holistic view of brain function and thought that the reticulum, made up of anastomosing axon collaterals, was the basic mechanism of brain function (Fig. 1.7). is, he thought, accounted for such phenomena as recovery from brain damage. His holism led him to disbelieve the localization results of Fritsch and Hitzig and of Ferrier.53

Fourteen years later, Ramón y Cajal came across the Golgi sil- ver stain and immediately began making the o en-capricious Golgi method more reliable, particularly by working with younger ani- mals who have less myelin, since myelin is resistant to silver stain- ing. Unlike Golgi, Cajal concluded that axon collaterals did not anastomose but ended freely: neurons were separate independent units. Although microscopes were not able to visualize the gap between neurons, Cajal inferred (intuited might be a better term) its existence on several grounds. One was by using immature or even foetal animals where he observed axons growing out of cell bodies before approaching other neurons or muscles. Another was that when cutting a nerve bre it would degenerate, but only up to the border with the next cell.53 (See Fig. 1.8).

Beyond con rming the idea of the neuron as an independent unit, Cajal developed the ‘Law of Dynamic Polarization’, the idea

that information transmission was from the dendrites to the cell body and out along the axon. He then used this ‘law’ to work out several neural circuits that began with sensory receptors in the ret- ina or in the olfactory bulb.53

In 1906, Golgi and Cajal shared the Nobel Prize. Golgi’s Nobel address was a vigorous defense of the reticular theory with the claim that the neuron theory ‘is generally recognized as going out of favor’.53,54 Over 100 years later, the neuron doctrine still stands as the bedrock of neuroscience. Its fundamental tenet of the dis- continuity between neurons was nally con rmed by the electron microscope in the 1950s only to be soon modulated by the discov- ery of a very small number of gap junctions in which the cell mem- branes of adjacent neurons are immediately opposed and synaptic transmission is electrical.55,56 e Law of Dynamic Polarization is still considered to be a fundamental property of neural circuits, although the existence of axon-less neurons, dendro-dendritic and axon–axonal synapses has complicated the picture.53

Twentieth-century neuroscience Prefrontal cortex

e association of the prefrontal cortex with the higher intellec- tual faculties has a long history. Classical busts of gods, heroes, and famous writers and artists usually show a high forehead in contrast to both lower-class individuals and women, both of whom were usually depicted to have retreating foreheads.57 e eighteenth-century Swedish theoretical neuroscientist and philosopher, Emanuel Swedenborg, attributed imagination, memory, thought, and will to the anterior regions of the brain.58 Gall and Spurzheim placed the ‘intellectual’ faculties in the most anterior brain regions. When the

Fig. 1.8 Cajal’s drawing of the sensory-motor connections of the spinal cord according to his neuron theory (right) and to Golgi’s reticular theory (left). A: anterior roots; B; posterior roots. According to Golgi, collaterals of the motor axon (a) anastomose forming part of a di use interstitial network (c). According to Cajal, the axon collaterals (f) do not.
Reproduced from Cajal S Ramon y. Recollections of My Life, Trans. EH Craigie, Copyright (1937), American Philosophical Society.

systematic study of human brain injury and of experimental lesions in monkeys began in the nineteenth century, intellectual function was usually located in the prefrontal cortex. For example, from their observations of frontal lobe damage, the frontal lobes were thought by Hitzig to contain the highest intellectual centre, by Ferrier to be the centre of attention and therefore of ideation and perception, by Paul Flechsig to be the area for volition and the higher levels of personality, by Giovanni Bianchi to be the centre of centres, and by Wilhelm Wundt to be an ‘apperception’ centre.59

In 1848, one of the most notable cases of prefrontal injury occurred in a man working with explosives on the railroad, whose skull was accidentally pierced by an iron bar pierce. Remarkably, Phineas Gage survived the accident but his personality and behav- iour changed irrevocably. From being a considerate, responsible foreman, he became ‘ tful, indulging at times in the grossest pro- fanities … manifesting but little deference for his fellows, impatient of restraint or advice when it con icts with his desires, at times per- tinaciously obstinate, yet capricious and vacillating, devising many plans of future operation, which are no sooner arranged that they are abandoned’.60 Gage’s case was not widely reported and its true importance was not fully appreciated until much later, but it stands as a landmark case in the history of observations of human prefron- tal function.61

In the rst objective tests of prefrontal function in animals, a er prefrontal lesions, monkeys and chimpanzees were found to be severely and permanently impaired on performance of the ‘delayed response test’ in which the animal is required to remember, a er a brief delay, at which of two sites a bait is hidden.62 is was con- sidered to be a test of ‘recent memory’62 and later one of ‘working memory’.63 e dorsolateral prefrontal cortex was subsequently shown to be crucial for performance of this task.59,64

An incidental observation on a single chimpanzee’s behaviour- during this task led directly to the widespread clinical use of fron- tal lobe surgery to treat a variety of psychiatric disorders. Prior to lesion of its frontal lobe, this animal would have temper-tantrums whenever she made an error on the delayed response test. She no longer did so following the operation.62 When the Portuguese neu- rologist Egas Moniz heard of this observation at the International Congress of Neurology in London in 1935, he was inspired to initiate a series of frontal ‘leucotomies’ (cutting the white matter under the frontal cortex) to treat mental illness, and versions of the procedure technique were rapidly adopted elsewhere. In 1949, Moniz received the Nobel Prize for the introduction of frontal leu- cotomy. is and other psychosurgical procedures on the frontal lobe were carried out on an estimated 60 000 people in the US alone (Fig. 1.9). e practice radically declined in the 1980s largely

CHAPTER 1 historical aspects of neurology 11

12 SECTION 1 normal cognitive function

Fig. 1.9 W. Transorbital lobotomy used extensively by Walter Freeman: ‘A transorbital leucotome is inserted through the orbital roof into the brain and the handle is swung medially and laterally to sever bers at the base of the frontal lobe.’
Reproduced from Proc. R. Soc. Med. (Suppl.). 42, Freeman W, Transorbital leucotomy: the deep frontal cut. pp. 8–12, Copyright (1949), with permission from SAGE Publications.

because of the introduction of chlorpromazine and other psycho- active drugs.65–67

Assessment of the e ects of frontal lobotomies is di cult because very few patients were studied objectively before and a er surgery by independent investigators. Elliot Valenstein, who investigated the e cacy of the older lobotomies, summarized the situation as follows:

In general, there seems to be strong suggestive evidence (if not abso- lutely convincing) that some patients may have been signi cantly helped by psychosurgery. ere is certainly no grounds for either the position that all psychosurgery necessarily reduces people to a ‘veg- etable status’ or that is has a high probability of producing marvelous cures … ere is little doubt, however, that many abuses existed. Quite apart from the e ectiveness of the surgery there were always some risks. Patients did occasionally die from the operation, epilepsy was not an uncommon a ermath and various symptoms from infections and neurological damage could be attributed directly to the surgery.68

A small number of limited psychosurgical procedures are still car- ried out on the frontal lobe but they appear to be much more e ca- cious than the older procedures.65

Today, the prefrontal cortex is o en divided into several systems with di erent functions and damage to each system tending to pro- duce a di erent set of symptoms. To summarize (and simplify) one parcellation, damage to the dorsolateral system produces execu- tive dysfunction, to the orbitofrontal system, disinhibition, and to the medial frontal system, apathetic motivation.66 Another, more integrative theory has been o ered by Earl Miller and Jonathan Cohen69 (see also chapter 3).

Visual cortex

Bartolemo Panizza (1785–1867) was the rst individual to produce detailed experimental and clinicopathological evidence for a visual

area in posterior cerebral cortex. He carried out anatomical and lesion experiments on a variety of species as well as observations on brain-injured humans. His work was largely ignored, perhaps because it was published in Italian in a local journal, and because, following both Gall and Pierre Flourons, visual functions were con- sidered subcortical, the cortex being reserved for ‘higher psychic’ functions.70

Soon a er Fritsch and Hitzig’s publication on the motor cortex, David Ferrier con rmed their results (see section on discovery of motor cortex above). Ferrier then applied their electrical stimula- tion methods to search for sensory cortices in monkeys. He found that stimulation of the angular gyrus produced eye movements and inferred that this area was the seat of visual perception. He sup- ported this by showing that bilateral lesions of this area produced blindness (for the few post-operative days that the infected ani- mals lived). Apparently con rming this view, he found that large occipital lesions had no visual e ects unless they encroached on the angular gyrus.71

By contrast, soon a er, Hermann Munk found that large occipi- tal lesions produced blindness in both dogs and monkeys. Sanger Brown and Edward Schafer then con rmed Munk’s report of total blindness a er total occipital lesions in monkeys.72 (We now know that Ferrier’s failure to produce blindness a er occipital lesions was because his lesions spared the representation of the fovea, whereas those of Munk and Brown and Schae er did not.)

By the turn of the century, anatomical, clinico-pathological, and experimental data were converging on the identity of a visual area in the posterior cerebral cortex corresponding to the region of the stripe of Gennari, described by Francisco Gennari in 1782 and named by G Elliot Smith as area striata.72

In 1941, SA Talbot and Wade Marshall, using visually evoked responses, mapped the visual topography of striate cortex in

cats and monkeys (i.e. the projection or ‘map’ of the retina onto cortex). David Hubel and Torsten Wiesel, recording from sin- gle neurons, subsequently con rmed this retinotopic organiza- tion. rough the brilliant use of single neuron physiology, they revealed the functional architecture of striate cortex. ey showed that single striate cells integrated binocular input and were sen- sitive to oriented lines and edges. eir research promised the possibility of understanding perception in terms of neurons and became the model for subsequent explorations of the visual cor- tex and for all of contemporary neurophysiology. ey shared the Nobel Prize with Roger Sperry in 1961. Hubel and Wiesel then showed a second and third retinotopic area (V2 and V3) adjacent to striate cortex (V1) in the regions previously called para- and prestriate cortex.73

A new phase of cortical visual physiology began in the 1970s when John Allman and Jon Kass described a multiplicity of extra-striate visual areas in the squirrel monkey.74 Even more visual areas were subsequently discovered in the macaque and human by Semir Zeki, Van Essen, and Charles Gross and their colleagues, a total of over 30 having been found to date.75 Leslie Ungerleider and Mortimer Mishkin showed that these areas were organized into two main processing streams: a dorsal stream extended into posterior parietal cortex and was specialized for the analysis of space and movement, and a ventral stream extended into the temporal lobe and was specialized for pattern recognition, that is, for form and colour.76 Proceeding down each stream, the successive visual areas tend to have larger receptive elds, less topographic organization, and neurons with more spe- cialized properties.77–79

e inferior temporal cortex lies at the terminus of the ventral stream. Its neurons are no longer retinotopically organized and they respond selectively to complex shapes. In both monkeys and humans, the inferior temporal cortex contains several areas that selectively respond to images of faces.76,77 ere are also areas that specialize in representing locations and body parts. In both macaques and humans, these specialized areas were delineated with imaging methods.78 e later stages in both the dorsal and ventral hierarchy of visual areas send projections to the hippocam- pus by way of perirhinal and parahippocampal cortex.77,79

Brain laterality

Broca and Wernicke’s discoveries that le -hemisphere damage, at least in right-handers, resulted in de cits in producing and under- standing language respectively, led to the idea that the le hemi- sphere was the dominant hemisphere and the right hemisphere was the non-dominant or minor hemisphere. At rst, the dominant hemisphere was thought to be the most important hemisphere not only for language but also for other cognitive functions. For exam- ple, Hugo Liepmann (1863–1925) attributed ‘purposeful’ move- ments to the dominant hemisphere,57 and his classi cation of limb apraxia remains highly in uential to this day.

As early as 1865, John Hughlings Jackson, the ‘father’ of English neurology suggested that the so-called minor hemisphere might be more important than the major hemisphere for perceptual func- tions. However, it was not until the 1930s that evidence from the study of human patients showed that a variety of disorders in non-language functions were more common or more severe a er right- than a er le -hemisphere damage.79,80 ese sequleae of

right-hemisphere lesions included perceptual de cits (such as in object and face recognition and in visuo-constructive tasks), atten- tional de cits, and emotional disorders. us it became clear that the le hemisphere was the major one for language and related functions, whereas the right hemisphere was dominant for a var- iety of perpetual, attentional, and emotional functions. is lateral- ization of cognitive functions could also be shown in intact subjects by the unilateral anaesthetization of one hemisphere, a procedure know as the ‘Wada’ test, developed by the neurologist JA Wada in 1949.80

A new and powerful method of comparing the functions of the two hemispheres was developed by Roger Sperry and his colleagues in the 1950s. e clinical literature on patients with damage or agenesis of the corpus callosum had been contradictory, with many studies reporting no e ect of a damaged or absent callosum. For example, Andrew Akelatis had sectioned the corpus callosum for treatment of epilepsy in a number of patients and reported a total absence of any cognitive e ects of this surgery.57

By contrast, Sperry and his students showed, rst in cats and monkeys and then in human patients, that section of the corpus cal- losum resulted in each hemisphere having ‘its own mental sphere— that is, its own independent perceptual, learning, memory and other mental processes’.81 Suddenly, it became possible to compare the functions of the two hemispheres directly. e key to Sperry’s discovery was, in subjects with the corpus callosum sectioned, to direct sensory input into each hemisphere independently. For example, in the visual modality, he sectioned the optic chiasm sagitally so that information from the le eye went only to the le hemisphere and information from the right eye only to the right hemisphere. In humans, he achieved the same result by having the subject with sectioned corpus callosum xate so that information presented to each visual half- eld went to the contralateral hemi- sphere.82 Sperry received the Nobel Prize in Medicine/Physiology for this work in 1981.

It should be mentioned that this important work became rather distorted in the popular literature by its neglecting the fact that although the hemispheres have specialized functions, in fact they work together in the intact individual.

Functions of the hippocampus in memory

A major advance in the neurology of memory came from the study of Patient HM who received bilateral lesions of the hip- pocampus and adjacent tissues to alleviate epileptic seizures in frankly experimental surgery by William Scoville in 1953. A er the surgery, as studied primarily by Brenda Milner and later her student Suzanne Corkin, HM had very severe anterograde amne- sia: he appeared to be unable to store any new information for more than a few minutes, and his short-term memory never became long term.83

Subsequent research indicated that only his ‘declarative’ mem- ory (memory for facts and events) was impaired, whereas his ‘procedural’ memory (such as memory for motor and perceptual skills, and classical conditioning) was intact.84,85 Similar dissocia- tions between the two types of memory have been found in other patients a er hippocampal damage (but see also chapter 13). e hippocampus is necessary for the formation of long-term declara- tive memories, which appear to be stored in portions of the cerebral cortex.85

CHAPTER 1 historical aspects of neurology 13

14 SECTION 1 normal cognitive function Imaging

e most important advance in neurology in the last half-century has been the development of brain imaging, both structural (ana- tomical) and functional.

Structural imaging

CAT scanning (computed axial tomography), introduced in 1971, involves rst X-raying the brain (or other body part) at di erent angles from which is produced a three-dimensional image recon- structed by computer. is was a remarkable advance in neurology replacing inferior techniques for estimating brain lesions or tumours such as pneumoencephalography, cerebral angiography, and clinical examination. MRI (magnetic resonance imaging) of the brain was developed at about the same time as CAT scanning but has much higher resolution. It derives from a technique developed in chemis- try in the 1970s, ‘nuclear magnentic resonance’, involving the prop- erties of hydrogen atoms in a magnetic eld. MR techniques also permit visualization of white-matter connections in the brain using di usion-weighted imaging and tractography (see chapter 8).

Functional imaging

Functional imaging of the brain measures changes in local activity in di erent brain structures as functions of cognitive activity. e rst to do this was Angelo Mosso in 1881. He observed brain pul- sations through skull openings in human patients, noted that they increase locally during cognitive tasks, and inferred increased blood ow with increased brain function.86 A few years later, Charles C Roy and Sherrington, from their animal experiments, suggested ‘automatic mechanisms’ that regulated blood ow depending on variations in neural activity. In the 1920s, John Fulton studied a relationship of increased blood ow with the act of reading in a human patient.86

A er the Second World War, several techniques were developed that enabled blood ow to be locally measured as a function of


fMRI is also a method of measuring local blood ow in the brain. It is based on the same technique as MRI except that the imaging is focused on measuring the ratio of oxygenated to deoxygenated haemoglobin known as the ‘blood oxygenation level dependent’ or BOLD e ect. e BOLD response is a slightly delayed index of local brain activity. fMRI is today largely replacing PET for studies of brain activation because it is has much better spatial and temporal resolution, individuals can be safely studied repeatedly, activity on single trials can be measured, and it does not require a large medi- cal centre for its use.87

fMRI studies have provided numerous new insights into cogni- tive neuroscience and promise many more in the future.


1. Gross CG. A hole in the head: a history of trepanation. In: CG Gross, A Hole in the Head: More Tales in the History of Neuroscience. Cambridge, MA: MIT Press, 2009, pp. 1–23.

2. Arnott R, Finger S, and Smith CUM. Trepanation: Discovery, History, eory. Lisse: Swets & Zeitlinger, 2003.

3. Gross CG. Ancient Egyptian surgery and medicine. In: CG Gross Brain, Vision Memory: Tales in the History of Neuroscience. Cambridge, MA: MIT Press, 1998, pp. 1–7.

4. Breasted JH. e Edwin Smith Surgical Papyrus. Chicago, IL: e University of Chicago Press, 1930.

5. Gross CG. Greek Philosopher–Scientists and the Beginning of Brain Science. In: CG Gross, Brain, Vision, Memory: Tales in the History of Neuroscience. Cambridge, MA: MIT Press, 1998, pp. 8–29.

6. Freeman K. e Pre-Socratic Philosophers. Oxford: Blackwell, 1954. 7. Longrigg J. Greek Rational Medicine: Philosophy and Medicine from Alcmaeon to the Alexandrians. New York, NY: Routledge, 1993.

8. Lloyd GER. Early Greek Science: ales to Aristotle. London: Chatto & Windus, 1970.

9. Sigerist H. A History of Medicine, Vol. II: Early Greek, Hindu and Persian Medicine. New York, NY: Oxford University Press, 1961.

10. Farrington B. Greek Science, Its Meaning for Us. New York, NY: Penguin Books, 1994.

11. Schrödinger E. Nature and the Greeks. Cambridge: Cambridge University Press, 1954.

12. eophrastus [4th century BCE]. On the Senses. In: Stratton GM (trans.), eophrastus and the Greek Physiological Psychology Before Aristotle. London: Allen & Unwin, 1917.

13. Hippocrates [4th century BCE]). e Medical Works of Hippocrates. Chadwick J (trans.), Spring eld, IL: Charles C. omas, 1950.

14. Temkin O. Galenism: Rise and Decline of a Medical Philosophy. Ithaca, NY: Cornell University Press, 1973.

15. Gross CG. Aristotle on the Brain. Neuroscientist, 1:245–50, 1995.
16. Gross CG. Galen and the Squealing Pig. Neuroscientist.4:216–21, 1998. 17. Rocca J. Galen on the Brain: Anatomical Knowledge and Physiological

Speculation in the Second Century ad. Leiden: Brill, 2003.
18. Galen[2nd century]. On Anatomical Procedures: e Later Books.

Duckworth WLH, Towers B (trans.), Cambridge: Cambridge University

Press, 1962.
19. Galen [2nd century]. Galen On the Usefulness of the Parts of the Body.

May M.T. (trans.), Ithaca, NY: Cornell University Press, 1968.
20. Gross CG. e medieval cell doctrine of brain function. In: CG Gross,

Brain, Vision, Memory: Tales in the History of Neuroscience. Cambridge,

MA: MIT Press, 1998, pp. 30–5.
21. Russell GA. A er Galen: late antiquity and the islamic world. In:

S Finger, F Boller, and KL Tyler (eds).History of Neurology. New York,

NY: Elsevier, 2010, pp. 61–78.
22. Willis T. Cerebri anatomie. London: Dring, 1664.
23. Isler H. e development of neurology and the neurological sciences in

the 17th century. In: S Finger, F Boller, and KL Tyler (eds). History of

Neurology. New York, NY: Elsevier, 2009, pp. 91–106.
24. Gross CG. e rebirth of brain science. In: CG Gross, Brain, Vision, Memory: Tales in the History of Neuroscience. Cambridge, MA: MIT

Press, 1998, pp. 36–51.
25. Malpighi M (quotation). In: E Clarke and CD O’Malley (eds). e

Human Brain and Spinal Cord: A Historical Study Illustrated by Writings from Antiquity to the Twentieth Century. San Francisco, CA: Norman, 1996, pp. 417.

26. Rusch F (quotation). In: E Clarke and CD O’Malley (eds). e Human Brain and Spinal Cord: A Historical Study Illustrated by Writings from Antiquity to the Twentieth Century. San Francisco, CA: Norman, 1996, p. 420.

27. Neuberger M. e Historical Development of Experimental Brain and Spinal Cord Physiology Before Flourens. Baltimore, MD: Johns Hopkins University Press, 1981.

28. Gall FJ and Spurzheim JC. On the Function of the Brain and Each of Its Parts: With Observations on the Possibility of Determining the Instincts, Propensities and Talents, or the Moral and Intellectual Disposition of Men and Animals, by the Con guration of the Brain and Head. Boston, MA: Marsh, Capen and Lyon, 1835.

29. Young RM. Mind, Brain and Adaptation in the Nineteenth Century, Cerebral Localization and Its Biological Context from Gall to Ferrier. Oxford: Clarendon Press, 1970.

brain activity. In PET, a radioactive isotope such as
duced into the bloodstream and its emitted gamma rays can be detected by the PET scanner. A reconstructed image will then show the distribution of blood ow and, presumably, regional di erence in brain activity.87

O is intro-

30. Gross CG. e beginning of the modern era of cortical localization. In: CG Gross, Brain, Vision, Memory: More Tales in the History of Neuroscience. Cambridge, MA: MIT Press, 1998, pp. 52–64.

31. Cooter RS. e Cultural Meaning of Popular Science: Phrenology and the Organization of Consent in Nineteenth-Century Britain. Cambridge: Cambridge University Press, 1985.

32. Broca P [1861]. Remarks on the seat of the faculty of articulate lan- guage, followed by an observation of aphemia. In: G Von Bonin (ed.). Some Papers on the Cerebral Cortex. Spring eld, IL: Charles C omas, 1960, pp. 49–72.

33. Finger S and Roe D. Does Gustave Dax deserve to be forgotten?
e temporal lobe theory and other contributions of an overlooked gure in the history of language and cerebral dominance. Brain Lang. 1999;69:16–30.

34. Eling P and Whitaker H. History of aphasia: from brain to language. In: S Finger, F Boller, and KL Tyler (eds). History of Neurology.
New York, NY: Elsevier, 2010, pp. 571–82.

35. Luria AR. Basic Problems in Neurolinguistics. e Hague: Mouton, 1976.

36. Knecht S, Drager B, Deppe M, et al. Handedness and hemispheric language dominance in healthy humans. Brain. 2000;123:2512–18.

37. Springer SP and Deutsch G. Le Brain, Right Brain: Perspectives from Cognitive Neuroscience. New York, NY: Freeman, 1997.

38. Magner LN. A History of Medicine. New York, NY: Dekker, 1992.

39. Fritsch GT and Hitzig E [1870]. On the electrical excitability of the
cerberum. In: G Von Bonin (ed.). Some Papers on the Cerebral Cortex.
Spring eld, IL: Charles C omas, 1960, pp. 73–96.

40. Viets HR. West Riding, 1871–1876. Bull. Hist. Med. 1938;6:477–87.

41. Ferrier D. Experimental Researches in Cerebral Physiology and
Pathology. West Riding Lunatic Asylum Medical Reports. 1873;3:30–96.

42. Ferrier D. Experiments on the brain of monkeys: No. 1. Phil Trans R Soc
Lond. 1874–75;23:409–30.

43. Ferrier D. e Croonian lecture: experiments on the brain of monkeys
(Second Series). Phil Trans R Soc Lond. 1875;165:433–88.

44. Taylor CS and Gross CG. Twitches versus movements: a story of motor
cortex. Neuroscientist. 2003;9:332–42.

45. Horsley V and Schäfer EA. A record of experiments upon the functions
of the cerebral cortex. Phil Trans R Soc Lond B. 1888;179:1–45.

46. Beevor CE and Horsley V. A minute analysis (experimental) of the
various movements produced by stimulating in the monkey di erent regions of the cortical centre for the upper limb, as de ned by Professor Ferrier. Phil Trans R Soc Lond B. 1887;178:153–67.

47. Brown TG and Sherrington CS. Studies in the physiology of the nervous System. XXII. On the phenomenon of facilitation. 1. its occurrence in reactions induced by stimulation of the ‘motor’ cortex of the cerebrum in monkeys. Quart J Exp Physiol. 1915;9:81–100.

48. Leyton ASF and Sherrington CS. Observations on the excitable cortex of the chimpanzee, orang-utan, and gorilla. Q J Exp Physiol. 1916;11:135–222.

49. Pen eld W and Rasmussen T. e Cerebral Cortex of Man: A Clinical Study of Localization of Function. New York, NY: MacMillan, 1950.

50. Woolsey CN, Settlage PH, Meyer DR, et al. Pattern of localization in precentral and ‘supplementary’ motor cortex and their relation to the concept of a premotor area. In: Association for Research in Nervous and Mental Disease, Vol 30. New York, NY: Raven Press, 1952, pp. 238–64.

51. Finger S. Minds Behind the Brain: e Pioneers and eir Discoveries. New York, NY: Oxford University Press, 2000.

52. Graziano MSA. e organization of behavioral repertoire in motor cortex. Ann Rev Neurosci. 2006;29:105–34.

53. Shepherd GM. Foundations of the Neuron Doctrine, 1991. New York, NY: Oxford University Press, 1991.

54. Golgi C. e neuron doctrine—theory and facts. Nobel Lecture, 11 December 1906. In: Nobel Lectures Physiology or Medicine 1901–1921, 1967. New York, NY: Elsevier, 1906, pp. 189–217.

55. Robertson JD. Recent electron microscope observations on the ultras- tructure of the cray sh median-to-motor giant Synapse. Exp Cell Res. 1955;8:226–29.

56. Furshpan EJ and Potter DD. Transmission at the giant motor synapses of the cray sh. J Physiol. 1959;145:289–325.

57. Finger S. Origins of Neuroscience: A History of Explorations Into Brain Function. New York, NY: Oxford University Press, 1994.

58. Gross CG. Emanuel Swedenborg: a neuroscientist before his time. Neuroscientist. 1997;3:142–47.

59. Gross CG and Weiskrantz L. Some changes in behavior produced by lat- eral frontal lesions in the macaque. In: JM Warren and K. Akert (eds). e Frontal Granular Cortex and Behavior. New York, NY: McGraw- Hill, 1964, pp. 74–98.

60. Harlow JM. Recovery from the passage of an iron bar through the head. Publications of the Massachusetts Medical Society. 1868;2:327–47.

61. Damasio A. Descarte’s Error. London: Vintage Books, 2006.
62. Jacobsen CF, Wolfe JB, and Jackson TA. An experimental analysis of the functions of the frontal association areas in primates. J Nerv Mental Dis.

63. Pribram KH, Ahumada A, Hartog J, et al. A progress report on the

neurological processes disturbed by frontal lesions in primates. In: EE Walker and K Akert (eds). e Frontal Granular Cortex and Behavior. New York, NY: McGraw-Hill, 1964, pp. 28–55.

64. Mishkin M. E ects of small frontal lesions on delayed alternation in monkeys. J. Neurophysiol. 1957;20:615–22.

65. Anderson CA and Arciniegas DB. Neurosurgical interventions for neuropsychiatric syndromes. Curr Psychiat Rep. 2004;6:355–63.

66. Filley CM. e frontal lobes. In: S Finger, F Boller, and KL Tyler (eds). History of Neurology. New York, NY: Elsevier, 2010, pp. 557–70.

67. Valenstein ES. Great and Desperate Cures: e Rise and Decline of Psychosurgery and Other Radical Treatments for Mental Illness. New York, NY: Basic Books, 1986.

68. Valenstein ES. Brain Control. New York, NY: John Wiley & Sons, 1973. 69. Miller EK and Cohen JD. An integrative theory of prefrontal cortex

function. Ann Rev Neurosci. 2001;24:167–202.
70. Colombo M, Colombo A, and Gross CG. Bartolomeo Panizza’s

Observations on the Optic Nerve (1855). Beh Brain Res Bull.

71. Ferrier D. Functions of the Brain, 2nd edn, London: Smith and

Elder, 1886.
72. Gross CG. Beyond striate cortex: how large portions of the temporal

and parietal cortex became visual areas. In: CG Gross. Brain, Vision, Memory: Tales in the History of Neuroscience. Cambridge, MA: MIT Press, 1998, pp. 180–210.

73. Hubel DH.Eye, Brain and Vision. New York, NY: Freeman, 1988.
74. Kaas JH. eories of extrastriate cortex. In: JH Kaas, K Rockland, and

A Peters (eds).Cerebral Cortex, Vol. 12, Extrastriate Cortex in Primates.

New York, NY: Plenum Press, 1997, pp. 91–125.
75. Van Essen D. Organization of visual areas in macaque and human

cerebral cortex. In: LM Chalupa and JS Werner (eds). e Visual

Neurosciences, Vol. 1. Cambridge, MA: MIT Press, 2003, pp. 507–21. 76. Ungerleider LG and Mishkin M. Two cortical visual systems. In: D

Ingle, M Goodale, and R Mans eld (eds). Analysis of Visual Behavior.

Cambridge, MA: MIT Press, 1982, pp. 549–86.
77. Gross CG, Rodman HR, Gochin PM, et al. Inferior temporal cor-

tex as a pattern recognition device. In: Computational Learning and Cognition: Proceedings of the ird NEC Research Symposium. EB Baum (ed.). Philadelphia, PA: SIAM, 1993, pp. 44–73.

78. Gross CG. (2007). Single Neuron Studies of Inferior Temporal Cortex. Neuropsychologia. 2007;45:841–52.

79. Kravitz DJ, Saleem KS, Baker CI, et al. e ventral visual pathway: an expanded neural framework for the processing of object quality. Trends Cogn Sci. 2013;17:26–49.

80. Hecaen H and Albert ML. Human Neuropsychology. New York, NY: Wiley, 1978.

81. Sperry RW. Cerebral organization and behavior. Science. 1961;133: 1749–57.

82. Sperry RW. Hemisphere deconnection and unity in conscious aware- ness. Am Psychol. 1968;23:723–33.

CHAPTER 1 historical aspects of neurology 15

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83. Corkin S. Permanent Present Tense: e Unforgettable Life of the Amnesic Patient, H.M. New York, NY: Basic Books, 2013.

84. Corkin S. What’s new with the amnesic patient H.M.? Nat Rev Neurosci. 2002;3:153–60.

85. Squire LR. Memory and the hippocampus: a synthesis from ndings with rats, monkeys, and humans. Psychol Rev. 1992;99:195–231.

86. Posner MI and Raichle ME. Images of Mind. New York, NY: Scienti c American Library, 1994.

87. Raichle ME. e Origins of Functional Brain Imaging in Humans. In: S Finger, F Boller, and KL Tyler (eds). History of Neurology. New York, NY: Elsevier, 2010, pp. 257–70.


Functional specialization and network connectivity in brain function
Giovanna Zamboni

Do mental processes depend from ‘localized’ brain regions or are they ‘global’ resulting from the integrated functioning of the brain as a whole? Brain lesion studies and neuroimaging methods have given evidence of both interpretations, allowing contempo- rary neuroscience to reach the conclusion that localized regions of the brain do carry out speci c cognitive functions but they do so through multiple and complex interactions with many other brain regions forming large-scale networks.

Focal nature of cognitive functions

Evidence for functional specialization

from lesion cases

Historically, the notion that di erent cognitive abilities are related to the function of speci c brain regions took a relatively long time to become widely accepted by the scienti c community (see chapter 1). Such a concept was long resisted by ‘holistic’ perspec- tives of the brain which viewed each part as contributing to all functions. It was only with the anatomo-clinical works of Broca and Wernicke on language disorders in the 1860s and 1870s that that the concept of functional specialization was put on a sure footing.1 Prior to this, the rst intuition that mental functions were based in the brain had been advanced by Franz Joseph Gall in his controver- sial doctrine of phrenology.2

In 1861, Broca described a patient who lost the ability to speak following a stroke. Although able to understand language and repeat single words, and free of signi cant limb weakness, this individual could not articulate sentences or express himself in writ- ing. Post-mortem examination revealed a lesion in the le posterior lateral region of the frontal lobe, subsequently termed Broca’s area.3 Broca described other similar cases, and by inferring the correla- tion between post-mortem anatomical lesions and language dis- orders (anatomo-clinical correlation method), he concluded that language is localized in the le hemisphere.

About a decade later, Carl Wernicke described another case of language disturbances following a stroke. is patient could speak uently but in a meaningless way and could not understand spoken or written language. A er his death, the damaged area was found to be in the posterior le temporal lobe at the junction with the parietal lobe, subsequently termed Wernicke’s area. On the basis of his and Broca’s ndings, Wernicke proposed a model of language as a multi-component process, in which each component would have

a speci c, distinct anatomical localization.4 He distinguished a cen- tre for motor–verbal functions, localized in the le frontal regions, responsible for language articulation and production, from a centre for auditory–verbal functions, localized in the le temporal region, responsible for language perception. Lesions to the former would cause a non- uent aphasia with intact comprehension (Broca’s aphasia), while lesions to the latter would cause a uent aphasia with impaired comprehension (Wernicke’s aphasia).

In the same decades, studies by Fritsch and Hitzig in dogs further reinforced the notion that di erent functions are localized in di er- ent cortical regions by demonstrating that the stimulation of anterior regions of the cerebral cortex causes contralateral movements, and that their disruption causes contralateral paralysis.5 Functional specializa- tion was further supported by animal studies identifying oculor-motor centres in the frontal lobes,6 auditory centres in the temporal lobes,7 and visual centres in the occipital lobes (see also chapter 1).8

Many other cognitive functions were localized by investigat- ing patients who had su ered from focal brain lesions. One of the most famous cases was reported by Harlow in 1848 who described Phineas Gage who, a er having sustained a frontal lobe injury, presented profoundly altered social and interpersonal skills, to the point that people who knew him beforehand described him as ‘no longer being Gage’. is rst suggested that frontal brain regions are involved in social behaviour.9

Another landmark case was described by Scoville and Milner in 1957. Following bilateral temporal lobe resection in the attempt to treat his epilepsy, a patient named Henry Molaison (famously known as HM) became severely amnesic. He had permanently lost the ability to acquire new information (anterograde amnesia) and recall memories of the years immediately prior to surgery (retro- grade amnesia), despite having normal reasoning skills, language, and short-term/working memory.10 HM provided the rst evi- dence that the hippocampus and surrounding medial temporal structures are essential for the consolidation of information in long-term memory.11

Following these single case studies, the study of lesions in humans evolved and expanded. Large groups of patients were assessed to establish correspondences between the brain and symptoms in a more quantitative, robust way, permitting statistical inference at the level of population.12,13 Standardized scales to measure cogni- tive abilities were developed and used to compare patients’ perfor- mance to healthy controls.14

18 SECTION 1 normal cognitive function

e lesion method is based on the assumption that if a certain brain region is necessary for a certain function, then a lesion to that area should lead to a de cit in that function, whereas this should not occur when the brain region is undamaged (simple dissociation). Further expansion of the lesion method came with the concept of double dissociation, considered to be the strongest evidence for functional specialization and segregation. It requires the comparison between two patients (or groups of patients) dif- ferent in terms of lesion localization: if one patient is signi cantly more impaired in function A, while the other is signi cantly more impaired in function B, then it is concluded that the two functions are independently associated with the two damaged areas.

Using the double dissociation technique, several investigators including Ennio De Renzi in stroke-lesioned patients,14,15 Freda Newcombe in soldiers who had sustained focal and stable brain wounds during the Second World War,16 Brenda Milner in surgi- cal patients who had had lobectomies,17 Gazzaniga in patients who had undergone callosotomy,18 all demonstrated di erential de – cits following le and right hemisphere lesions and specialization of the right hemisphere for visual–perceptual and spatial tasks and le hemisphere for speech and skilled movements. Newcombe, for example, provided the rst evidence of dissociated visual–perceptual and spatial de cits following, respectively, temporal-posterior lesions and dorsal-parietal lesions of the right hemisphere,19 sup- porting the concept of a dorsal and ventral visual stream.

rough the study of lesion cases, the concept of functional speciali- zation became a dominant theme in neuroscience. It is mainly thanks to this approach that today we are able to localize de cits such as apha- sia, unilateral neglect, and impaired executive function at the bedside.

Evidence for functional specialization

from structural imaging

e need to study large groups of patients together with the advent of computer tomography (CT) and magnetic resonance imaging (MRI) encouraged development of methods that allow compari- son of lesions across di erent patients,20 including transposition of brains into common, stereotactic spaces.21 One common method consisted of identifying regions of lesion overlap. e extent and location of damage in a group of patients could be visualized in a colour-coded ‘lesion density map’, in which the region damaged in the highest number of patients would be surrounded by regions damaged by a progressively decreasing numbers of patients.22,23

Two approaches have been used to relate symptoms to lesions. One groups patients by location of their brain lesions and then examines di erences in symptoms. For example, a study by Grafman and colleagues on veterans who su ered penetrating head injuries in Vietnam showed that soldiers with lesions in the ventro- medial regions of the frontal lobes were more aggressive and violent than those with lesions in other brain areas.24 e second approach groups patients by symptoms and then examines lesion location. For example, Damasio and colleagues classi ed patients with focal brain lesions according to whether they had selective de cits in naming famous persons, animals, or tools. By using lesion density maps, they showed that each of these category-speci c de cits was associated with overlapping of lesions in di erent temporal lobe regions, arguing for a role of higher-order association areas outside of classic language areas in word retrieval.25

MRI o ers a higher spatial resolution than CT and allows for more comprehensive characterization of lesions by ‘dividing’ the

brain into three-dimensional units of volume (voxels). In one of the rst studies that used a voxel-based approach, Adolphs and colleagues demonstrated involvement of somatosensory cortices as well as the amygdala in emotion recognition, by comparing the voxel-based lesion density map of patients with impaired emotion recognition with that of unimpaired cases. e resulting di erence map revealed that voxels within the somatosensory cortex were sig- ni cantly associated with impairment.26

Building on statistical approaches used in functional imaging (see next section), recently developed techniques such as voxel-based lesion symptom mapping (VLSM)27,28 allow for improved symp- tom mapping by computing statistical tests iteratively for each and every voxel. e technique relies on comparison of continuous or discrete behavioural variables on patients grouped according to whether they have damage in that given voxel and then correcting for multiple comparisons. is is an example of a ‘mass-univariate’ approach because each voxel is assumed to be independent of another. Importantly, VLSM does not require patients to be grouped a priori according to lesion location or performance cut-o s, but produces statistical values for each given voxel indicating whether damage to that voxel has a signi cant e ect on the cognitive variable of interest.29–33

Although fundamental to study symptom–lesion associations, voxel-based symptoms mapping methods are limited by their assump- tion that each voxel can be damaged independently of other voxels. It has been recently argued that this assumption is not biologically valid, as lesions in the human brain tend to follow patterns depending, for example, on vascular supply in the case of stroke. It is possible that ‘collaterally damaged’ voxels may be always associated with voxels that are instead critical for a certain de cit and therefore may systemati- cally confound lesion–symptom associations, suggesting that multi- variate rather than mass-univariate approaches may be better suited to identify true anatomical correlates of de cits/symptoms.34

Structural MRI data can also be analysed with procedures that provide subject-speci c estimated maps of grey matter volume or thickness,35–38 which are more suitable for studying subtle struc- tural changes and, di erently from VLMS, do not rely on ‘radio- logically visible’ and discrete lesions. Among them, voxel-based morphometry (VBM) involves segmentation of the grey matter, spatial transposition of all the subjects’ images to the same stereo- tactic space, and ‘modulation’ to obtain voxel-speci c values of grey matter density (or volume). ese values can then be used in regression analyses to compare groups of individuals or perform correlations with continuous variables of behavioural/cognitive performance. is is achieved with voxel-based statistical analysis aimed at identifying, for example, distribution of voxels of signi – cant volumetric di erences between two groups, or voxels whose grey matter density signi cantly correlates with performance.

VBM has been particularly useful in identifying brain–symptom associations in neurodegenerative diseases, in which pathologi- cal processes causing grey matter loss or atrophy are widespread and involve di erent brain regions to a variable degree. ey are therefore are better represented by continuous variables rather than binary measurements, which are more suited to de ne dis- crete lesions. In patients with dementia or other neurodegenera- tive diseases, VBM has been reliably used to identify patterns of grey matter atrophy. For example, several VBM studies39–41 have found that patients with Alzheimer’s disease (AD) have focal atro- phy in the medial temporal lobes, posterior cingulate/precuneus,

and other association areas in a pattern that mirrors the spread of neuro brillary tangles,42 while the behavioural variant of fronto- temporal dementia (FTD) is associated with atrophy in the fron- tal lobes.43,44 Semantic dementia is associated with asymmetrical anterior temporal lobe atrophy. By contrast, progressive non uent aphasia is associated with le perisylvian atrophy.45 In addition, VBM has also been extensively used to make inferences on the association of focal atrophy with speci c cognitive de cits.46–49 As an example, a VBM correlational analysis in patients with frontotemporal dementia reported that severity of apathy cor- related with atrophy in the right dorsolateral prefrontal cortex, whereas severity of disinhibition correlated with atrophy in mes- olimbic structures.50

Several other MRI-based tools have been used to study volumes of a priori de ned regions of interest (ROIs) or rates of atrophy over time in neurodegenerative diseases. In AD, ROI-based measures of hippocampal volumes are signi cantly reduced compared to age-matched controls,51–54 and the rate of change measured from serial MRIs obtained six months or one year apart signi cantly increased.55–58

By the use of correlational analyses, VBM and ROI-based meth- ods allow for indirect inferences about the localization of speci c symptoms in patients with dementia. However, di erently from lesion–symptom mapping techniques, they do not prove the neces- sity of a brain region for a speci c cognitive function.

Evidence for functional specialization from functional

imaging in healthy subjects

Functional imaging has revolutionized the eld of brain function mapping over the last 20 years. Activation-based positron emis- sion tomography (PET) and task-based functional MRI (task fMRI) detect changes in metabolism or blood ow while subjects are engaged in sensorimotor or cognitive tasks and can be used to produce activation maps revealing which parts of the brain are engaged. ese functional techniques have allowed extension of the concept of functional localization from the study of brain-injured patients to the study of healthy people.

PET activation studies measure focal variations in cerebral blood ow. A radiotracer is injected in the bloodstream while the subject is engaged in di erent tasks (usually an experimen- tal condition and a control condition), with the assumption that blood ow will increase in brain regions where there is increased neural activity.59 Task-based fMRI relies on the Blood Oxygen Level Dependent (BOLD) contrast, which is dependent on local changes in cerebral blood ow, cerebral blood volume, deoxyhae- moglobin concentration, local haematocrit, and changes in oxy- gen consumption. When a brain area is more active, it consumes more oxygen, causing an increase of blood ow and a change in the BOLD signal.60,61 PET activation studies and task-based fMRI do not directly measure neural activity, but instead measure changes in parameters (metabolism and BOLD) correlated with neural activity that occur with a delay, limiting the temporal reso- lution of these techniques.

PET activation studies and task-based fMRI studies do not provide absolute measurements of physiological parameters but measure changes that occur in response to a task relative to another task, used as a control condition. By subtracting signal changes occurring during the control task from those occurring during the experimental task, it is possible to identify areas of

increased activation associated with the task of interest, assum- ing that areas active in both control and experimental conditions have been cancelled out. To establish localization and strength of the association between the experimental condition and the meas- ured brain changes, the functional images that have been acquired over time during di erent conditions and across di erent subjects need to be realigned and mapped into standard stereotactic, voxel- based spaces. en, methods allowing statistical inference need to be used.

e most commonly used method to identify functionally spe- cialized brain responses is statistical parametric mapping (SPM), which allows use of standard statistical tests on each voxel and assembles the resulting statistical parameters into images.62 ese are then used to compare di erent conditions and to identify regionally speci c changes of signal attributable to the experi- mental task (Fig. 2.1).63 Importantly, if a signi cant associations is found, this does not mean that the identi ed area is necessary for the speci c function or cognitive process, nor that it is speci c for it, because it may also be involved in other functions or tasks.

Since the advent of functional imaging techniques in the late 1980s and early 1990s, a huge number of studies have reported focal activations in response to speci c tasks across a range of cog- nitive domains,64 providing striking evidence for the concept of functional specialization. A review of these studies is outside the focus of the present chapter but a few early studies are worth con- sidering as examples.

In a PET activation experiment, Zeki and colleagues showed that occipital area V4 is speci c for colour vision, by comparing activations obtained during presentation of multicolour abstract images with those obtained during presentation of the same images in black and white, and that V5 or area MT is speci c for motion perception, by comparing activations obtained during presentation of moving relative to stationary black and white patterns (see also chapter 6 for further examples).65

One important limitation of the subtraction method used in the early functional activation studies is that it depends on the assumption of ‘pure insertion’, that is, that a component process can be added into a task without a ecting other processes. To modu- late possible interactions between di erent cognitive components in neuroimaging experiments and disentangle the e ect that one component has on the other, more sophisticated experimental techniques such as factorial design were implemented.66 For lan- guage, a factorial design was used, as an example, to compare object naming with colour naming. It allowed identi cation of modality- independent naming areas in prefrontal and posterior temporal regions, and areas involved in object recognition in bilateral ante- rior temporal regions.67

e results of several functional imaging studies have chal- lenged the traditional view of a one-to-one correspondence between brain regions and cognitive processes. On the one hand, single cognitive processes frequently elicit activation of several brain regions or distributed patterns of activations.64,68 On the other hand, activations of single brain regions are frequently elic- ited by a wide range of cognitive tasks, even when these have been carefully modulated with factorial experimental designs.68,69 us, although extensively supported by lesion cases and func- tional imaging studies, the concept of functional specialization alone may not be su cient to explain brain functioning and organization in human.

CHAPTER 2 functional specialization, network connectivity 19


normal cognitive function

FMRI data Time

Motion correction High-pass filtering Spatial smoothing

Preprocessed data

Voxel-wise single-subject analysis Design matrix

Effect size statistics




Voxel time-series data

Statistic image


Significant voxels/clusters

Single-subject effect size statistics

Stimulus/task timings

Fig. 2.1 Schematic representation of single-session analysis of fMRI data. fMRI data are acquired while stimuli are presented to the subject, who performs a task in the scanner. Data are then pre-processed (including motion correction, temporal ltering, and spatial smoothing) and entered into a regression model (general linear model, GLM) that expresses the observed BOLD response in terms of a linear combination of explanatory variables (in the design matrix) derived from stimulus/task timings and the haemodynamic response function (HRF), together with an error term. Voxel-speci c e ect-size statistics describe how well the modelled responses to the stimulus/task (explanatory variables) explain the continuous data. resholding is performed in a way that accounts for multiple comparison correction.

Courtesy of the Analysis Group of the Centre for Functional MRI of the Brain (FMRIB) from the FSL (FMRIB Software Library) course.

Network organization of cognitive


Towards the concept of distributed

functional networks

Wernicke had rst suggested that complex cognitive functions such as language result from distributed systems of linked focal brain regions. He proposed a model of language as a multi-component process, in which each component has a speci c anatomical locali- zation but is connected to the other components, reconciling evi- dence for functional specialization that he and others had provided with the notion that cognitive functions depend on integrated functioning across brain regions.4 He even hypothesized the exist- ence of a conduction aphasia that would be associated with a lesion of the pathways connecting the le hemisphere frontal and tempo- ral lobe centres, characterized by preserved uency and compre- hension but impaired repetition and paraphasic speech (the use of incorrect words or phonemes while speaking).

In addition to conduction aphasia, other ‘disconnection syn- dromes’ resulting from damage of white matter tracts between cor- tical areas were described. As an example, alexia without agraphia, in which patients are able to write and speak but cannot read, was rst described by Dejerine 1891 and associated with lesions to the white matter in proximity of the angular gyrus that interrupt the

connections between the visual cortex and language areas. In 1965, the anatomical bases of disconnection syndromes were reviewed by Geschwind70,71 who provided a theoretical framework that paved the road for modern concepts of distributed brain networks.72 Around the same time, Alexander Luria, one of the founders of neuropsychology, proposed a model of human mental processes based on complex functional systems or ‘functional units’ that involved groups of brain areas working in a coordinated, hierarchi- cal, and organized way.73

Related to this ideas is the notion that a lesion can cause func- tional damage ‘remote’ from the anatomical site of the lesion. is concept was extensively studied by Monakow who coined the term diaschisis—loss of function due to transient, indirect damage to remote parts of the brain not anatomically close to the site of the primary injury but functionally connected to it.74 His work fostered the view of the brain as a complex, dynamic system in which func- tion could be lost transiently. Evidence for diaschisis comes from functional imaging studies that show hypometabolism in regions remote from the cortical lesion,75 demonstrating directly the exist- ence of remote functional e ects.76

ese ideas led to the refutation of functional localization as the sole and su cient explanation of brain function. Brain–symptom correlations started to be searched not only in speci c, single brain regions but also in larger-scale networks connecting di erent

regions across the brain. With the additional bene t of knowledge about anatomical structural connections from tracing methods in the autopsied brain, Mesulam proposed a model of brain func- tion based on distinct, multifocal large-scale functional systems.77 In his scheme, there is a spatial attention network anchored in the posterior parietal and dorsolateral frontal regions, a language net- work involving Wernicke’s and Broca’s areas, a memory network linking the hippocampus and inferior parietal cortex, a face/object recognition network anchored in temporal cortices, and a working- memory/executive-function network connecting prefrontal and inferior parietal cortices.78

Subsequently, McIntosh demonstrated the existence of net- works by measuring the covariance of activity between regions in PET activation studies, thus identifying patterns of co-variation or functional connectivity.79 For example, he studied people who had learned that an auditory stimulus signalled a visual event and found activation in le occipital visual areas when auditory stimuli were presented alone. He then showed that this occipital activation cor- related with activation in the prefrontal cortex and that it accounted for most of the change in occipital activity.80

It is now widely accepted that the brain functions through large-

scale networks including multiple specialized cortical areas recip-

rocally connected with parallel, bidirectional, and multisynaptic

pathways. us de cits can be caused either by damage to special-

ized cortical areas, by damage to their connecting pathways, or both.72,81,82

Neuroimaging methods to study brain connectivity

Several methodological advances have allowed study of brain con- nectivity and large-scale brain networks from di erent perspec- tives. Functional connectivity refers to the functional relationship between brain regions inferred by searching for correlations in the fMRI signal between two or more brain regions (functional covariance). e structural bases of this relationship are ultimately assumed to exist through mono- or multisynaptic pathways.83,84

Correlations in the fMRI signal (BOLD signal) can be studied among regional changes occurring in response to cognitive tasks but also among regional changes that occur in the absence of tasks,

while participants are simply at rest (resting fMRI). In fact, it has been shown that the BOLD signal not only changes as a conse- quence of cognitive or ‘task-related’ demand, but also shows low frequency spontaneous uctuations (0.01–0.1 Hz) that are tempo- rally correlated and organized within speci c spatial patterns in the brain.85,86 e networks of brain regions whose spontaneous activity rises and falls coherently have been termed resting state networks.

To study functional correlation, a ‘seed’ voxel or anatomical ROI is ‘seeded’ to generate a correlation map showing all other regions in which signal changes signi cantly correlate with those within the seed region (seed-based correlation analysis). is approach is hypothesis-driven and requires a priori selection of the ROI or ‘seed’. Alternatively, a more exploratory, data-driven approach can be used to create a matrix of correlations across each voxel/region with all other voxels/regions in the brain. Correlation matrices can be decomposed into spatial modes using, for instance, principal component analysis (PCA) or independent component analysis (ICA) to identify large-scale networks or maps of spatially inde- pendent and temporally correlated functional signals.87–89

Among the several resting state networks identi ed with ICA- based approaches, the default mode network (DMN, Fig. 2.2A)— which includes posterior cingulate cortex and precuneus, the medial prefrontal cortex, and lateral parietal regions—is considered to be speci cally engaged during task-independent introspection or self-referential thought. e DMN was st identi ed in task- related fMRI by studying task-induced deactivations (i.e. decreases in BOLD signal during experimental conditions compared to base- line or resting conditions).90 It can also be identi ed with ‘seed- based’ methods examining correlations from regions such as the posterior cingulate.91,92

In addition to the DMN, other commonly identi ed networks are the ‘executive control’ networks linking dorsofrontal and pari- etal regions, the ‘salience’ network linking anterior cingulate to insular and limbic regions, and networks related to primary visual, auditory, and sensorimotor regions (Fig. 2.2).86,88,89,93,94 Resting state networks (RSN) have been shown to be consistent across subjects95 and to match activations found in task-based fMRI

CHAPTER 2 functional specialization, network connectivity 21


x = 2

y = 58

z = 26

x = –10

y = –80

z = –6

x = –10

y = –72

z = 16

x = 50

y = –32

z = 14

x = –6

y = 26

z = –14

x = –48

y = 10

z = 28

x = 44

y = 8

z = 34

Fig. 2.2 Resting state networks (RSNs). Spatial maps of resting state networks (RSNs) obtained using independent component analysis (ICA). e three most informative orthogonal slices for each RSN are shown. A) DMN; B) ventromedial visual RSN; C) dorsolateral visual RSN; D) auditory RSN; E) orbitofrontal RSN; F) left frontoparietal RSN; G) right frontoparietal RSN. Coordinates are in MNI.
Reproduced from Biological Psychiatry, 74(5), Zamboni G, Wilcock GK, Douaud G, et al. Resting functional connectivity reveals residual functional activity in Alzheimer’s disease, pp. 375–83, Copyright (2013), with permission from Elsevier.

22 SECTION 1 normal cognitive function

studies, suggesting that they re ect functionally signi cant brain networks.96–98

E ective connectivity represents another way to study functional correlations and network function. Di erent from functional con- nectivity, this method incorporates additional information such as anatomical constraints and considers interactions of several brain regions simultaneously. It is aimed at explicitly quantifying the in uence that one region has on another and establish whether their connections are causal and have a speci c directionality (from region A to area B rather than B to A).100 E ective connectivity approaches include dynamic causal modelling (DCM) that allows testing of speci c models of how di erent parts of a functional net- work are dynamically linked and coupled. DCM is less ‘model-free’ and more hypothesis-driven (and more computationally sophisti- cated) than functional connectivity. It tests dynamic interactions and is therefore task-dependent and condition-speci c, and has been mainly applied to task-based fMRI studies, although it has been recently extended to modelling of resting-state data and com- paring multiple di erent models.101,102

e principles used to investigate functional and e ective con- nectivity from fMRI data can also be applied to data obtained with neurophysiological techniques such as electro-encephalography (EEG) and magnetoencephalography (MEG), allowing mapping of networks at high temporal resolution as well as studying frequency band-speci c interactions.103,104

Structural connectivity refers to the white matter connections between brain regions. ese can be visualized with tracing meth- ods in animals or ex vivo methods in autopsied human brains, or inferred in vivo with structural imaging techniques such as di u- sion tensor imaging (DTI). DTI can be used to estimate the struc- tural integrity of brain connections (i.e. axons and bre tracts) by measuring di usion of water molecules through tissues.105 It pro- vides measures of fractional anisotropy (FA), a particularly sensi- tive index of microstructural integrity of cerebral white matter, and of radial and axial di usivity, which give indications of axonal dam- age and demyelination, respectively. Common methods to assess structural disruption are voxel-wise106 or di usion tensor imaging tractography (see chapter 8).107 Structural connectivity can also be estimated by studying the correlation among regional structural measures such as local cortical thickness and volume across sub- jects (anatomical covariance), in a way similar to functional con- nectivity.108,109 Structural covariance does not demand existence of a direct anatomical connection between the regions whose struc- tural measures are correlated. As with functional covariance, the identi ed connections might not re ect axonal pathways and cau- tion is required in interpreting the results. Nevertheless, networks identi ed using this approach have been found to re ect genetic in uences as well as experience-related plasticity reliably.110

Brain networks derived from all the methods described above can be examined using graph theory in which connectivity ele- ments (single brain regions or maps of resting state networks) are de ned as network nodes and their mutual relationships as network edges. In this way, brain networks can be mathematically described as graphs which, in their simplest form, correspond to correla- tions matrices representing the strength of edges between pairs of nodes. At the highest level of abstraction, even the whole brain can be de ned as a network and its properties described in terms of number of edges per node, resistance to damage, e ciency, hierar- chy, and sub-networks, among other graph theory measures.111,112

Although graph-theoretical approaches have several limitations, including the high dependence on how nodes are initially de ned (with structural atlas-based or functional parcellations) and their high degree of abstraction, they have the potential of becoming more meaningful and interpretable in the near future.113

Large-networks abnormalities

in neurodegenerative diseases

Connectivity methods have now been applied to neurological diseases. is has been particularly promising in the context of neurodegenerative diseases, which are associated with gradual and speci c patterns of progression of pathology across the brain. Indeed, it has been increasingly suggested that di erent pathologies target speci c large-scale networks.114,115

Since its identi cation, the DMN has been shown to be particu- larly relevant for AD, since it includes regions know to be vulner- able to atrophy, amyloid deposition, and reduced metabolism in patients with AD.116 DMN functional connectivity is reduced in patients with AD compared to healthy controls.117 Similarly, ROI- based studies using the hippocampus or the posterior cingulate as ‘seeds’ show decreased functional connectivity with regions of the DMN such as the medial prefrontal cortex, but increased func- tional connectivity with frontal and frontoparietal regions.118–121

More recent studies that used ICA-based methods con rm that patients with AD have signi cant decreased functional integrity and connectivity in regions of the DMN.122–125 Among them, the few studies that also explored other resting state networks99 found that that functional connectivity within frontal and frontoparietal networks is increased in patients with AD relative to controls, thus having the opposite connectivity e ect than the DMN.99,123,124,126 Importantly, these most recent studies examined changes in func- tional connectivity occurring over and above the structural changes that occur in neurodegenerative diseases by including VBM meas- ures of atrophy as a covariate of no interest.

A number of resting-state fMRI studies have explored functional connectivity in other neurodegenerative diseases. For example, in patients with behavioural variant of frontotemporal dementia, functional connectivity was decreased in the salience network and increased in the DMN, a pattern opposite to the one found in patients with AD.127 In patients with Parkinson’s disease, functional connectivity is reduced in a network involving basal ganglia, and normalizes upon administration of dopaminergic medication.128

Do resting state networks identi ed with resting fMRI relate to actual brain functioning in response to cognitive demand? In healthy people, it has been increasingly shown that functional net- works at rest re ect those utilized ‘actively’ during execution of tasks.96–98 A recent study which combined resting and task-based fMRI also showed that this is true in patients, suggesting changes in functional connectivity secondary to neurodegenerative disease might directly re ect residual cognitive functioning in patients.99 E ective connectivity has also been used in neurodegenerative diseases.129

In a seminal study combining anatomical covariance and func- tional connectivity,130 Seeley and colleagues investigated pat- terns of atrophy of ve di erent neurodegenerative syndromes (Alzheimer’s disease, corticobasal degeneration, and the three variants of frontotemporal dementia) shown in blue in Figure 2.3). Using the identi ed regions of greater atrophy in each disease as a ‘seed’, they then showed that in healthy people, seed-based


Syndrome-specific regional atrophy patterns: patients vs. controls

Atrophy max = seed ROI

R PMC +40 6



R Ang

RFI 4.4 L TPole


bvFTD SD +35 +11



CHAPTER 2 functional specialization, network connectivity 23



Intrinsic functional connectivity networks: healthy controls

Structural covariance networks: healthy controls





Fig. 2.3 Results of the study from Seeley, et al.130 Syndrome-speci c atrophy patterns (in blue), whose cortical maxima (circled) provided seed ROIs for functional
(in yellow) and structural (in green) covariance analyses in a group of healthy controls.
Reproduced from Neuron, 62(1), Seeley WW, Crawford RK, Zhou J, Miller BL, Greicius MD, Neurodegenerative diseases target large-scale human brain networks, pp. 42–52, Copyright (2009), with permission from Elsevier.

covariance patterns of structural (Fig. 2.3, green) and functional (Fig. 2.3, yellow) measures mirrored syndrome-speci c patterns of atrophy. is suggested that networks of functional and structural connectivity in the healthy brain are di erentially vulnerable to speci c neurodegenerative disease. More precisely, AD a ects the DMN, the behavioural variant of frontotemporal dementia a ects the salience network, semantic dementia targets the le temporal polar network, progressive non- uent aphasia the le frontopa- rietal network, and corticobasal degeneration the sensory-motor network.

In a subsequent study, the same authors further explored network properties of each region found to be atrophic in the ve neuro- degenerative diseases to identify regions whose normal functional connectivity pro le best overlapped with disease-speci c patterns of atrophy (which they termed ‘epicentres’). ey then used graph- theoretical methods to explore possible models of disease spread and reported evidence for a model of trans-neuronal spread from highly vulnerable disease epicentres that, in healthy people, repre- sent highly connected nodes or network hubs.131

Graph theory principles have also been applied to measures of cortical thickness covariance to explore network properties in patients with AD. Patients with AD have increased local connectiv- ity of nodes (increased clustering) but decreased global e ciency (increased edges length between connected nodes), suggesting that AD is characterized by a de cit in long-range connectivity and associated with a reversion to less optimal connectivity and more localized connections.132 AD patients also showed changes in the e ciency of speci c nodes, with signi cant decreased e ciency in heteromodal temporal and parietal regions, and increased e – ciency in frontal and occipital regions, in line with ndings from functional connectivity.

One recent study speci cally tested if network hubs, identi ed using DTI, in the normal brain are indeed vulnerable to speci c brain disorders.133 Analysis of data from published MRI studies

suggests these hubs are atrophic across twenty-six di erent neu- rological and psychiatric conditions. More precisely, nine diseases including AD and schizophrenia have atrophy located in speci c highly connected regions; that is, temporal lobe hubs were spe- ci cally associated with AD, whereas frontal and temporal corti- cal hubs were associated with schizophrenia. Similar results were obtained when highly connected hubs were derived from func- tional connectivity calculated from a meta-analysis of task-related functional imaging studies, rather than from DTI. e authors concluded that highly connected regions within networks identi- ed with di erent connectivity modalities are more likely to be ana- tomically a ected by brain disorders.

Future directions

e contraposition between the concepts of functional speciali- zation and connectivity has been a major theme in the history of neuroscience. While evidence discussed in the rst part of this chapter demonstrates the existence of functionally special- ized areas, a growing body of knowledge discussed in the second part shows the importance of connections for brain function- ing. Network approaches account for connectivity and nodal or regional specialization, o ering the promise to reconcile these seemingly opposing perspectives.134 Several worldwide initiatives have been recently set up with the aim of describing comprehen- sively all macroscopic functional and structural connections of the healthy brain, by mapping what has been termed ‘human con- nectomes’135 (for a complete list of current research projects into macroscale connectomics, see reference 136). Some argue that this will help to attain a fundamental understanding of brain architec- ture and its relation with cognition and behaviour. Ultimately, it is hoped that it will be clinically useful to obtain individual-relevant reliable indices that can be used for identi cation of people at risk of speci c diseases, prognostication, and measurement of treat- ment response.

24 SECTION 1 normal cognitive function References

1. Broca P. Localisations des fonctions cérébrales. Siège de la faculté du langage articulé. Bulletin de la Société d’Anthropologie. 1863; tome IV:200–08.

2. Gall FJ and Spurzheim G. Anatomie et Physiologie du Système nerveux en général et du cerveau en particulier avec des observations sur la possibilité de reconnaître plusieurs dispositions intellectuelles et morales de l’homme et des animaux par la con guration de leur têtes. Paris: Schoell, 1810.

3. Broca P. Perte de la parole, ramollissement chronique et destruction partielle du lobe antérieur gauche [Sur le siège de la faculté du langage.] Bulletin de la Société d’Anthropologie. 1861;tome II:235–8.

4. Wernicke C. Der aphasische Symptomencomplex: Eine psychologische Studie auf anatomischer Basis. Breslau: Cohn und Weigert, 1874.

5. Fritsch G and Hitzig E. Über die elektrische Erregbarkeit des Grosshirn. Archive für Anatomie, Physiologie und wissenscha liche Medicin. 1870:300–32.

6. Ferrier D. Experimental researches in cerebral physiology and path- ology. West Riding Lunatic Asylum Med Rep. 1973:30–96.

7. Luciani L. On the sensorial localization in the cortex cerebri. Brain. 1884;26:145–61.

8. Munk H. Weitere Mittheilungen zur Physiologie der Grosshirnrinde. Verhandlungen der Physiologischen Gesellscha zu Berlin. 1878.

9. Damasio H, Grabowski T, Frank R, et al. e return of Phineas
Gage: Clues about the brain from the skull of a famous patient. Science.

10. Scoville WB and Milner B. Loss of recent memory a er bilateral hip-
pocampal lesions. J Neurol Neurosur Ps. 1957;20:11–21.

11. Squire LR and Zola-Morgan S. e medial temporal lobe memory
system. Science. 1991;253:1380–6.

12. De Renzi E. Caratteristiche e problemi della neuropsicologia. Archivio
di psicologia, neurologia e psichiatria. 1967;28:422–40.

13. Benton AL. e Fiction of the ‘Gerstmann Syndrome’. J Neurol Neurosur
Ps. 1961;24:176–81.

14. De Renzi E and Nichelli P. Verbal and non-verbal short-term
memory impairment following hemispheric damage. Cortex.

15. De Renzi E. Asimmetrie emisferiche nella rappresentazione non verbali.
Atti del XVI Congresso Nazionale di Neurologi. Rome 1967.

16. Newcombe F. Missile Wounds of the Brain: A Study of Psychological
De cits. London: Oxford University Press, 1969.

17. Milner B. Interhemispheric di erences in the localization of psycho-
logical processes in man. Brit Med Bull. 1971;27:272–7.

18. Gazzaniga MS and Sperry RW. Language a er section of the cerebral
commissures. Brain. 1967;90:131–48.

19. Newcombe F. Dissociated visual perceptual and spatial de cits in focal
lesions of the right hemisphere. J Neurol Neurosur Ps. 1969;32:73–81.

20. Damasio H and Damasio AR. Lesion Analysis in Neuropsychology.
Oxford: Oxford University Press, 1989.

21. Talairach J and Tournoux P. Co-planar stereotaxic atlas of the human
brain: 3-dimensional proportional system: An approach to medical cere-
bral imaging. Stuttgart: ieme Medical, 1988.

22. Frank RJ, Damasio H, and Grabowski TJ. Brainvox: An interactive, mul-
timodal visualization and analysis system for neuroanatomical imaging.
Neuroimage. 1997;5:13–30.

23. Damasio H and Frank R. ree-dimensional in vivo mapping of brain
lesions in humans. Arch Neurol–Chicago. 1992;49:137–43.

24. Grafman J, Schwab K, Warden D, et al. Frontal lobe injuries, violence,
and aggression: a report of the Vietnam Head Injury Study. Neurology.

25. Damasio H, Grabowski TJ, Tranel D, et al. A neural basis for lexical
retrieval. Nature. 1996;380:499–505.

26. Adolphs R, Damasio H, Tranel D, et al. A role for somatosensory
cortices in the visual recognition of emotion as revealed by three- dimensional lesion mapping. J Neurosci. 2000;20:2683–90.

27. Bates E, Wilson SM, and Saygin AP, et al. Voxel-based lesion-symptom mapping. Nature Neurosci. 2003;6:448–50.

28. Karnath HO, Fruhmann Berger M, Kuker W, et al. e anatomy of spatial neglect based on voxelwise statistical analysis: A study of 140 patients. Cereb Cortex. 2004;14:1164–72.

29. Walker GM, Schwartz MF, Kimberg DY, et al. Support for anterior temporal involvement in semantic error production in aphasia: New evidence from VLSM. Brain and Lang. 2011;117:110–22.

30. Baldo JV, Katse S, and Dronkers NF. Brain Regions Underlying Repetition and Auditory-Verbal Short-term Memory De cits in Aphasia: evidence from Voxel-based Lesion Symptom Mapping. Aphasiology. 2012;26:338–54.

31. van Asselen M, Kessels RP, Frijns CJ, et al. Object-location mem- ory: A lesion-behavior mapping study in stroke patients. Brain Cognition. 2009;71:287–94.

32. Barbey AK, Colom R, Solomon J, et al. An integrative architecture for general intelligence and executive function revealed by lesion mapping. Brain. 2012;135:1154–64.

33. Knutson KM, Rakowsky ST, Solomon J, et al. Injured brain regions associated with anxiety in Vietnam veterans. Neuropsychologia. 2013;51:686–94.

34. Mah YH, Husain M, Rees G, et al. Human brain lesion-de cit inference remapped. Brain. 2014;137:2522–31.

35. ompson PM, Mega MS, Woods RP, et al. Cortical change in Alzheimer’s disease detected with a disease-speci c population-based brain atlas. Cereb Cortex. 2001;11:1–16.

36. Ashburner J and Friston KJ. Voxel-based morphometry—the methods. Neuroimage. 2000;11:805–21.

37. Ashburner J and Friston KJ. Why voxel-based morphometry should be used. Neuroimage. 2001;14:1238–43.

38. MacDonald D, Kabani N, Avis D, et al. Automated 3-D extraction of inner and outer surfaces of cerebral cortex from MRI. Neuroimage. 2000;12:340–56.

39. Scahill RI, Schott JM, Stevens JM, et al. Mapping the evolution of regional atrophy in Alzheimer’s disease: Unbiased analysis of uid- registered serial MRI. Proc Natl Acad Sci USA. 2002;99:4703–07.

40. Busatto GF, Diniz BS, and Zanetti MV. Voxel-based morphometry in Alzheimer’s disease. Expert Rev Neurother. 2008;8:1691–702.

41. Fennema-Notestine C, Hagler DJ, Jr, et al. Structural MRI biomark- ers for preclinical and mild Alzheimer’s disease. Hum Brain Mapp. 2009;30:3238–53.

42. Braak H and Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 1991;82:239–59.

43. Rosen HJ, Gorno-Tempini ML, Goldman WP, et al. Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology. 2002;58:198–208.

44. Rosen HJ, Kramer JH, Gorno-Tempini ML, et al. Patterns of cer- ebral atrophy in primary progressive aphasia. Am J Geriatr Psychiat. 2002;10:89–97.

45. Gorno-Tempini ML, Dronkers NF, Rankin KP, et al. Cognition and anatomy in three variants of primary progressive aphasia. Ann Neurol. 2004;55:335–46.

46. Rosen HJ, Allison SC, Schauer GF, et al. Neuroanatomical correlates of behavioural disorders in dementia. Brain. 2005;128:2612–25.

47. Whitwell JL, Sampson EL, Loy CT, et al. VBM signatures of abnormal eating behaviours in frontotemporal lobar degeneration. Neuroimage. 2007;35:207–13.

48. Sarazin M, Chauvire V, Gerardin E, et al. e amnestic syndrome of hippocampal type in Alzheimer’s disease: an MRI study. J Alzheimers Dis. 2010;22:285–94.

49. Boddaert N, Chabane N, Gervais H, et al. Superior temporal sulcus anatomical abnormalities in childhood autism: a voxel-based morpho- metry MRI study. Neuroimage. 2004;23:364–9.

50. Zamboni G, Huey ED, Krueger F, et al. Apathy and disinhibition in frontotemporal dementia: Insights into their neural correlates. Neurology. 2008;71:736–42.

51. Kesslak JP, Nalcioglu O, and Cotman CW. Quanti cation of magnetic 76. resonance scans for hippocampal and parahippocampal atrophy in
Alzheimer’s disease. Neurology. 1991;41:51–4. 77.

52. Jack CR, Jr., Petersen RC, O’Brien PC, et al. MR-based hippocam-
pal volumetry in the diagnosis of Alzheimer’s disease. Neurology.
1992;42:183–8. 78.

Carrera E and Tononi G. Diaschisis: past, present, future. Brain. 2014;137:2408–22.
Mesulam MM. Large-scale neurocognitive networks and distrib- uted processing for attention, language, and memory. Ann Neurol. 1990;28:597–613.

Mesulam MM. From sensation to cognition. Brain. 1998;121

53. Jack CR, Jr, Petersen RC, Xu YC, et al. Medial temporal atrophy on MRI in normal aging and very mild Alzheimer’s disease. Neurology. 1997;49:786–94.

54. Chan D, Fox NC, Scahill RI, et al. Patterns of temporal lobe atro- phy in semantic dementia and Alzheimer’s disease. Ann Neurol. 2001;49:433–42.

55. Fox NC, Freeborough PA, and Rossor MN. Visualisation and quanti – cation of rates of atrophy in Alzheimer’s disease. Lancet. 1996;348:94–7.

56. Jack CR, Jr., Petersen RC, Xu Y, et al. Rates of hippocampal atrophy correlate with change in clinical status in aging and AD. Neurology. 2000;55:484–9.

57. Barnes J, Boyes RG, Lewis EB, et al. Automatic calculation of hippocam- pal atrophy rates using a hippocampal template and the boundary shi integral. Neurobiol Aging. 2007;28:1657–63.

58. Barnes J, Foster J, Boyes RG, et al. A comparison of methods for the automated calculation of volumes and atrophy rates in the hippocam- pus. Neuroimage. 2008;40:1655–71.

59. Fox PT and Mintun MA. Noninvasive functional brain mapping by change-distribution analysis of averaged PET images of H215O tissue activity. J Nucl Med. 1989;30:141–9.

60. Ogawa S, Menon RS, Tank DW, et al. Functional brain mapping by blood oxygenation level-dependent contrast magnetic resonance imaging. A comparison of signal characteristics with a biophysical model. Biophys J. 1993;64:803–12.

61. Ogawa S, Tank DW, Menon R, et al. Intrinsic signal changes accom- panying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc Natl Acad Sci USA. 1992;89:5951–5.

62. Friston KJ, Ashburner JT, Stefan JK, et al. Statistical Parametric Mapping: e Analysis of Functional Brain Images, 1st edn. London: Academic Press, 2007.

63. Friston KJ, Holmes A, Poline JB, et al. Detecting activations in PET and fMRI: levels of inference and power. Neuroimage. 1996;4:223–35.

64. Cabeza R and Nyberg L. Imaging cognition II: An empirical review of 275 PET and fMRI studies. J Cognitive Neurosci. 2000;12:1–47.

65. Zeki S, Watson JD, Lueck CJ, et al. A direct demonstration of functional specialization in human visual cortex. J Neurosci. 1991;11:641–9.

66. Friston KJ, Price CJ, Fletcher P, et al. e trouble with cognitive subtrac- tion. Neuroimage. 1996;4:97–104.

67. Price CJ, Moore CJ, Humphreys GW, et al. e neural regions sustaining object recognition and naming. Proc Roy Soc Lond (Biol). 1996;263:1501–07.

68. Price CJ and Friston KJ. Functional ontologies for cognition: e systematic de nition of structure and function. Cognitive Neuropsych. 2005;22:262–75.

69. Fedorenko E, Duncan J, and Kanwisher N. Broad domain generality in focal regions of frontal and parietal cortex. Proc Natl Acad Sci USA. 2013;110:16616–21.

70. Geschwind N. Disconnexion syndromes in animals and man. II. Brain. 1965;88:585–644.

71. Geschwind N. Disconnexion syndromes in animals and man. I. Brain. 1965;88:237–94.

72. Catani M and Ffytche DH. e rises and falls of disconnection syn- dromes. Brain. 2005;128:2224–39.

73. Lurii͡a AR and Haigh B. e Working Brain: An Introduction to Neuropsychology. New York: Basic Books, 1973.

74. Monakow CV. Die Lokalisation im Grosshirn und der Abbau der Funktion durch kortikale Herde. Wiesbaden: J.F. Bergmann, 1914.

75. Price CJ, Warburton EA, Moore CJ, et al. Dynamic diaschisis: anatom- ically remote and context-sensitive human brain lesions. J Cognitive Neurosc. 2001;13:419–29.

(Pt 6):1013–52.

79. McIntosh AR, Grady CL, Ungerleider LG, et al. Network ana-
lysis of cortical visual pathways mapped with PET. J Neurosci.

80. McIntosh AR, Cabeza RE, and Lobaugh NJ. Analysis of neural
interactions explains the activation of occipital cortex by an auditory
stimulus. J Neurophysiol. 1998;80:2790–6.

81. Sporns O, Chialvo DR, Kaiser M, et al. Organization, development and
function of complex brain networks. Trends Cogn Sci. 2004;8:418–25.

82. Bressler SL and Menon V. Large-scale brain networks in cognition:
Emerging methods and principles. Trends Cogn Sci. 2010;14:277–90.

83. Honey CJ, Sporns O, Cammoun L, et al. Predicting human resting- state functional connectivity from structural connectivity. Proc Natl
Acad Sci USA. 2009;106:2035–40.

84. Greicius MD, Supekar K, Menon V, et al. Resting-state functional con-
nectivity re ects structural connectivity in the default mode network.
Cereb Cortex. 2009;19:72–8.

85. Gusnard DA and Raichle ME. Searching for a baseline: functional imaging
and the resting human brain. Nature Rev Neurosci. 2001;2:685–94.

86. Fox MD and Raichle ME. Spontaneous uctuations in brain activity
observed with functional magnetic resonance imaging. Nature Rev
Neurosci. 2007;8:700–11.

87. Beckmann CF and Smith SM. Probabilistic independent component
analysis for functional magnetic resonance imaging. IEEE T Med
Imaging. 2004;23:137–52.

88. Beckmann CF, DeLuca M, Devlin JT, et al. Investigations into resting-
state connectivity using independent component analysis. Philos
Trans R Soc Lond B Biol Sci. 2005;360:1001–13.

89. De Luca M, Beckmann CF, De Stefano N, et al. fMRI resting state
networks de ne distinct modes of long-distance interactions in the
human brain. Neuroimage. 2006;29:1359–67.

90. Raichle ME, MacLeod AM, Snyder AZ, et al. A default mode of brain
function. Proc Natl Acad Sci USA. 2001;98:676–82.

91. Greicius MD, Krasnow B, Reiss AL, et al. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis.
Proc Natl Acad Sci USA. 2003;100:253–8.

92. Andrews-Hanna JR, Reidler JS, Sepulcre J, et al. Functional-anatomic
fractionation of the brain’s default network. Neuron. 65:550–62.

93. Seeley WW, Menon V, Schatzberg AF, et al. Dissociable intrinsic
connectivity networks for salience processing and executive control.
J Neurosci. 2007;27:2349–56.

94. Damoiseaux JS, Beckmann CF, Arigita EJ, et al. Reduced resting-state
brain activity in the ‘default network’ in normal aging. Cereb Cortex.

95. Yeo BT, Krienen FM, Sepulcre J, et al. e organization of the human
cerebral cortex estimated by intrinsic functional connectivity. J
Neurophysiol. 2011;106:1125–65.

96. Smith SM, Fox PT, Miller KL, et al. Correspondence of the brain’s
functional architecture during activation and rest. Proc Natl Acad Sci
USA. 2009;106:13040–5.

97. Laird AR, Eickho SB, Rottschy C, et al. Networks of task co-
activations. Neuroimage. 2013;80:505–14.

98. Laird AR, Fox PM, Eickho SB, et al. Behavioral interpreta-
tions of intrinsic connectivity networks. J Cognitive Neurosci.

99. Zamboni G, Wilcock GK, Douaud G, et al. Resting functional con-
nectivity reveals residual functional activity in Alzheimer’s disease.
Biol Psychiat. 2013;74:375–83.

100. Friston KJ. Functional and e ective connectivity: a review. Brain
Connectivity. 2011;1:13–36.

CHAPTER 2 functional specialization, network connectivity 25

26 SECTION 1 normal cognitive function

101. Friston KJ, Li B, Daunizeau J, et al. Network discovery with DCM. Neuroimage. 2011;56:1202–21.

102. Stephan KE, Weiskopf N, Drysdale PM, et al. Comparing hemody- namic models with DCM. Neuroimage. 2007;38:387–401.

103. Varela F, Lachaux JP, Rodriguez E, et al. e brainweb: phase synchroni- zation and large-scale integration. Nature Rev Neurosci. 2001;2:229–39.

104. Stam CJ. Use of magnetoencephalography (MEG) to study func- tional brain networks in neurodegenerative disorders. J Neuro Sci. 2010;289:128–34.

105. Moseley ME, Cohen Y, Kucharczyk J, et al. Di usion-weighted MR imaging of anisotropic water di usion in cat central nervous system. Radiology. 1990;176:439–45.

106. Smith SM, Jenkinson M, Johansen-Berg H, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject di usion data. Neuroimage. 2006;31:1487–505.

107. Catani M and iebaut de Schotten M. A di usion tensor imag- ing tractography atlas for virtual in vivo dissections. Cortex. 2008;44:1105–32.

108. He Y, Chen ZJ, and Evans AC. Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. Cereb Cortex. 2007;17:2407–19.

109. Mechelli A, Friston KJ, Frackowiak RS, et al. Structural covariance in the human cortex. J Neurosci. 2005;25:8303–10.

110. Evans AC. Networks of anatomical covariance. Neuroimage. 2013;80:489–504.

111. Bullmore E and Sporns O. Complex brain networks: Graph theoreti- cal analysis of structural and functional systems. Nature Rev Neurosci. 2009;10:186–98.

112. Rubinov M and Sporns O. Complex network measures of brain con- nectivity: Uses and interpretations. Neuroimage. 2010;52:1059–69.

113. Smith SM, Vidaurre D, Beckmann CF, et al. Functional connectomics from resting-state fMRI. Trends Cogn Sci. 2013;17:666–82.

114. Pievani M, de Haan W, Wu T, et al. Functional network disruption in the degenerative dementias. Lancet Neurol. 2011;10:829–43.

115. Rowe JB. Connectivity Analysis is Essential to Understand Neurological Disorders. Frontiers in Systems Neuroscience. 2010;4.

116. Buckner RL, Snyder AZ, Shannon BJ, et al. Molecular, structural, and functional characterization of Alzheimer’s disease: Evidence for a rela- tionship between default activity, amyloid, and memory. J Neurosci. 2005;25:7709–17.

117. Greicius MD, Srivastava G, Reiss AL, et al. Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proc Natl Acad Sci USA. 2004;101:4637–42.

118. Wang L, Zang Y, He Y, et al. Changes in hippocampal connectivity in the early stages of Alzheimer’s disease: evidence from resting state fMRI. Neuroimage. 2006;31:496–504.

119. Allen G, Barnard H, McColl R, et al. Reduced hippocampal func- tional connectivity in Alzheimer disease. Arch Neurol–Chicago. 2007;64:1482–7.

120. Zhang HY, Wang SJ, Xing J, et al. Detection of PCC functional con- nectivity characteristics in resting-state fMRI in mild Alzheimer’s disease. Behav Brain Res. 2009;197:103–8.

121. Zhang HY, Wang SJ, Liu B, et al. Resting brain connectiv-
ity: changes during the progress of Alzheimer disease. Radiology. 2010;256:598–606.

122. Gili T, Cercignani M, Serra L, et al. Regional brain atrophy and func- tional disconnection across Alzheimer’s disease evolution. J Neurol Neurosur Ps. 2011;82:58–66.

123. Agosta F, Pievani M, Geroldi C, et al. Resting state fMRI in Alzheimer’s disease: Beyond the default mode network. Neurobiol Aging. 2012; Aug;33(8):1564–78.

124. Damoiseaux JS, Prater KE, Miller BL, et al. Functional connectivity tracks clinical deterioration in Alzheimer’s disease. Neurobiol Aging. 2012 Apr;33(4):828.e19–30.

125. Binnewijzend MA, Schoonheim MM, Sanz-Arigita E, et al. Resting- state fMRI changes in Alzheimer’s disease and mild cognitive impair- ment. Neurobiol Aging. 2011;33:2018–28.

126. Jones DT, Machulda MM, Vemuri P, et al. Age-related changes in the default mode network are more advanced in Alzheimer disease. Neurology. 2011;77:1524–31.

127. Zhou J, Greicius MD, Gennatas ED, et al. Divergent network con- nectivity changes in behavioural variant frontotemporal dementia and Alzheimer’s disease. Brain. 2010;133:1352–67.

128. Szewczyk-Krolikowski K, Menke RA, Rolinski M, et al. Functional connectivity in the basal ganglia network di erentiates PD patients from controls. Neurology. 2014 Jul 15;83(3):208–14.

129. Rowe JB, Hughes LE, Barker RA, et al. Dynamic causal model- ling of e ective connectivity from fMRI: Are results reproducible and sensitive to Parkinson’s disease and its treatment? Neuroimage. 2010;52:1015–26.

130. Seeley WW, Crawford RK, Zhou J, et al. Neurodegenerative diseases target large-scale human brain networks. Neuron. 2009;62:42–52.

131. Zhou J, Gennatas ED, Kramer JH, et al. Predicting regional neurode- generation from the healthy brain functional connectome. Neuron. 2012;73:1216–27.

132. He Y, Chen Z, and Evans A. Structural insights into aberrant topologi- cal patterns of large-scale cortical networks in Alzheimer’s disease.
J Neurosci. 2008;28:4756–66.

133. Crossley NA, Mechelli A, Scott J, et al. e hubs of the human con- nectome are generally implicated in the anatomy of brain disorders. Brain. 2014;137:2382–95.

134. Sporns O. Structure and function of complex brain networks. Dialogues in Clinical Neuroscience. 2013;15:247–62.

135. Sporns O, Tononi G, and Kotter R. e human connectome: A struc- tural description of the human brain. PLoS Computational Biology. 2005;1:e42.

136. Craddock RC, Jbabdi S, Yan CG, et al. Imaging human connectomes at the macroscale. Nature Methods. 2013;10:524–39.


e frontal lobes

Teresa Torralva, Ezequiel Gleichgerrcht, Agustin Ibañez, and Facundo Manes

e frontal lobes are pivotal in the management of higher-level behavioural functions, such as the planning and execution of inten- tional motor behaviour including but not limited to limb and eye movements and speech articulation. ey are also responsible for major information-processing operations, such as mnemonic func- tions. Among these are the short term, on-line maintenance and manipulation of information in working memory, which allows for an idea to be weighed up against alternatives,1 the organization of information for encoding and retrieval within long-term memory,2 and the establishment of abstract relationships and mental exibil- ity.3 Furthermore, the frontal lobes have a role in various compo- nents of attention,4 the processing of emotions,5 social cognition,6 and future-oriented thought.7

In light of the plethora of important functions mediated by the frontal lobes, impairment of frontal functions can be found, although in varying degrees, in many neurological and psychiat- ric disorders, predominantly in traumatic brain injury,8 fronto- temporal dementia,9,10 bipolar disorder,11,12 schizophrenia,13 and depression.14

An exceptionally large area of the brain, the frontal lobes account for approximately one-third of the human cerebral cortex. While it has been classically accepted that this area is larger in humans than in non-human primates, more recent studies suggest the frontal lobes are of comparable size throughout the primate line- age.15 Instead, it is proposed that the human neural architecture is more sophisticated or perhaps organized di erently than among non-human primates, thus allowing for a similarly sized cerebral cortex to accommodate the more advanced cognitive processes that characterize human but not other primates.16 In particular, Semendeferi and colleagues supported this assumption by sug- gesting higher-level cognition in humans may be attributed to dif- ferences in individual cortical areas and a richer interconnectivity rather than a greater overall size (Fig. 3.1a and b).17

Besides sharing cerebral cortices that may be proportionally simi- lar in size, humans and monkeys have distinct architectonic regions within their prefrontal cortex. Experimental and anatomical stud- ies in monkeys have identi ed that each region is distinct in its con- nections with cortical and subcortical structures.18 Connections are classi ed as either a erent or e erent and are mediated via speci c bre pathways. Critical information about perceptual and mne- monic processes occurring in posterior association cortical areas and subcortical structures is passed to particular prefrontal regions by means of a erent connections. E erent connections deliver information from the prefrontal cortical areas to post-Rolandic

cortical association areas and subcortical structures, thus enabling selective information processing.19

Each frontal lobe takes the form of a pyramid, with the frontal pole, central sulcus, and lateral, medial, and orbital walls contribut- ing to its shape. All functional types of cortex are represented within the frontal lobes. e limbic cortex is represented in the form of an inconspicuous sliver of pyriform cortex at the most caudal end of the orbital surface, primary motor and motor association areas are located on the lateral and dorsomedial surfaces, the heteromodal cortex covers most of the lateral surfaces, and the paralimbic cortex is located on the caudal regions of the medial and orbital surfaces. e paralimbic component of the frontal lobe is continuous with the cingulate gyrus on the medial surface and with the insula and temporal pole on the orbital surface.20

e prefrontal cortex (PFC) occupying the rostral pole of the brain was once described as the area responsible for intelligence; however, damage to this part of the cortex does not result in intel- lectual de cits but, rather, PFC lesions have detrimental e ects on executive and social functioning. e prefrontal cortex has been identi ed as an action-orientated region which plays an important role in the decision to carry out an action, the type of action to be carried out, and appropriate timing for such action.21

Frontal lobe functions can be grouped into five cortical- subcortical circuits, based on their function and anatomical makeup (Fig. 3.2). Each circuit is made up of equal component structures, including the cerebral cortex, a portion of the striatum, a station in the globus pallidum or substantia nigra, and, nally, the thala- mus. ese circuits project from and to the frontal lobes.22 Each circuit contains a direct and indirect pathway that includes the sub- thalamic nucleus. is chapter will focus on three of these circuits, those principally related to non-motor cognition and behaviour.

e dorsolateral prefrontal circuit (DL-PFC)

is circuit originates in Brodmann’s areas 9 and 46 on the dor- solateral surface of the anterior frontal lobe. e mid-dorsolateral prefrontal region is considered to be critical for the monitoring of information in working memory, which is necessary for high level planning and manipulation of information. is function may be exercised via the dorsal limbic pathways that link this region to the PFC with the hippocampal system via the posterior cingulate ros- trosplenial region. e posterior dorsolateral frontal cortex appears to underlie what are sometimes referred to as attentional processes. ese areas receive input from medial and lateral parieto-occipital

28 SECTION 1 normal cognitive function




globus palllidus externa (GPe) and the ventromedial subthalmic nucleus (STN) preserves some anatomical segregation from the motor and limbic circuits. e mediodorsal thalamus closes this loop by connecting back to areas 9 and 46 of the dorsolateral frontal lobe. Projections from the ventralis anterior nucleus also terminate in the inferotemporal cortex.25

e dorsolateral circuit is principally considered to subserve executive functions (EF), which include the mental capacities nec- essary for goal formulation, as well as the planning and achievement of these goals.26 is circuit also plays a part in guiding behaviour, set-shi ing, motor planning, strategy generation, and activation of remote memories.27

Lesions to the aforementioned frontal lobe circuit o en result in a recognizable and distinct frontal lobe syndrome: the dor- solateral frontal syndrome (executive dysfunction syndrome). is syndrome speci cally results in the impairment of execu- tive functions with patients presenting with poor organizational strategies (e.g. Tower tests), reduced inhibition (e.g. Hayling test), lack of planning and motor programming de cits (e.g. frontal assessment battery or INECO frontal screening). Furthermore, damage to this area can result in di culties generating hypoth- eses and impaired exibly for maintaining or shi ing sets, among others.28

e orbitofrontal circuit (OFC)

Originating in Brodmann’s areas 10 and 11, the orbitofrontal circuit consists of medial and lateral sub-circuits. e medial orbitofron- tal circuit sends bres to the ventral striatum and to the dorsal part of the nucleus accumbens.29 e lateral orbitofrontal circuit sends projections to the ventromedial caudate. ese sub-circuits con- tinue to the most medial portion of the caudomedial GPi and to the rostromedial SNr. Axons are sent from the GPi/SNr to the medial area of the magnocellular parts of the ventralis anterior thalamic nucleus. e circuit closes with projections back to the medial or lateral orbitofrontal cortex.30 e orbitofrontal cortex has extensive connections with other cortical areas, especially in the inferior tem- poral and insular cortices, with the amygdala and hippocampus. It also receives auditory information from the secondary and tertiary auditory areas, somatosensory information from the secondary somatosensory and parietal cortex, and heteromodal inputs from the superior temporal cortex.31

(b) 450,000 400,000 350,000 300,000 250,000 200,000 150,000 100,000 50,000


Fig. 3.1 (a) Relative size of the prefrontal cortex in di erent primates. (b) Volume of the frontal lobe across species. Values include both hemispheres.
(a) Adapted from Journal of Human Evolution, 32(4), Semendeferi K, Damasio H, Frank R,
and Van Hoesen GW, e evolution of the frontal lobes: a volumetric analysis based on three-dimensional reconstructions of magnetic resonance scans of human and ape brains,

pp. 375–88, Copyright (1997), with permission from Elsevier. (b) Adapted from Nat Neurosci, 5(3), Semendeferi K, Lu A, Schenker N, and Damasio H, Humans and great apes share a large frontal cortex, pp. 272– 6, Copyright (2002), with permission from Nature Publishing Group.

cortical regions, as well as from the adjacent caudal superior tem- poral gyrus via the superior longitudinal, the occipito-frontal. and the arcuate fasciculi.23

Sequential connections are to the striosomes of the dorsolateral head of the caudate nucleus,24 lateral aspect of the dorsomedial glo- bus pallidus interna (Gpi), and rostrolateral sustancia nigra (SNr) via the direct pathway. e indirect pathway through the dorsal



Gorilla Orangutan

40 35 30 25 20 15 10 5



Pallidum S. Nigra







rl-Gpi, VP rd-SNr





vi-Gpi cl-SNr

vlo vlm




Cdm-Gpi vl-SNr



dl-CAUD (h)

idm-Gpi rl-SNr

VApc MDpc




mdm-Gpi rm-SNr

m-VAmc MDmc


Fig. 3.2 Cortical-subcortical circuits of the frontal lobes.

Human Chimpanzee Gorilla

Orangutan Gibbon Macaque

Frontal lobe volume (mm3)

Volume in percent of hemisphere

Lesions to this circuit o en result in the typically called orbito- frontal syndrome which is linked to personality changes, includ- ing emotional lability, irritability, outspokenness, reduced concerns or worries, and, at times, presenting with imitation and utilization behaviours (the act of grasping objects that are within reach or in the eld of vision in a context that is inappropriate),32 Eslinger and Damasio5 used the term ‘acquired sociopathy’ when describing patients with previously normal personalities who, following dam- age to the ventromedial frontal cortex, developed decision-making and planning di culties, which presented in the form of challeng- ing, inappropriate, or maladaptive social behaviours. is was also observed in the famous case of the young man called Phineas Gage (Fig. 3.3).

Lesions to this circuit o en result in a syndrome, the anterior cin- gulate syndrome, characterized by reduced spontaneous activity, evident in disorders such as akinetic mutism and transient abulic hypokinesia or abulia.37 A typical presentation of this syndrome is that of an apathetic individual with reduced emotional responses. e patient may require prompting to initiate verbal communication and, when verbal responses are elicited, they are likely to be monosyl- labic in form. Assistance with feeding is o en required due to lack of spontaneous movement, which may also lead to incontinence and other problems typically caused by lesions to areas outside the PFC.

Neurotransmitter circuits

Neurotransmitters modulate the signaling in neural networks and a ects cognition and behaviour (see also chapter 9). Di erent neu- rotransmitter circuits are involved in the frontal lobes, given their dense interconnectivity with the rest of the brain. In particular, the PFC projections to subcortical arousal systems modulate monoam- ine and cholinergic inputs to other regions as well as onto itself.38 Glutamatergic excitatory circuits project from frontal cortex to speci c regions of the striatum. GABAergic inhibitory bres pro- ject to the globus pallidus/substantia nigra, then to thalamus, and nally from the thalamus back to the prefrontal cortex. As such, the fast-acting transmitters of the frontal-subcortical circuits, namely GABA and glutamate, a ects frontostriatal connections.

In addition to these projections, executive functions are a ected by major ascending monoamines (dopamine, norepinephrine, ser- otonin, histamine, orexin, as well as acetylcholine), spread out to several forebrain regions (hippocampus, striatum, amygdala, and thalamus), as well as to the neocortex.39 For instance, it comes as no surprise that several neuropsychiatric conditions associated with abnormal catecholaminergic (dopamine, serotonin, and noradren- alin) and cholinergic modulation40 present with widespread frontal de cits. Monoamine modulators have strong in uences on prefron- tal cognitive functioning (Fig. 3.4). Several of these in uences seem to a ect cognitive functioning and self-control in healthy normal individuals, and more evidently so in neuropsychiatric conditions.

Asymmetries of the frontal lobes

In this section, we will brie y revise the few ndings that have been reported in the literature about structural and functional

CHAPTER 3 the frontal lobes 29

is is one of the most famous cases in behavioural neurology, neuropsychiatry, and neuropsychology. It was pivotal in iden- tifying a link between brain damage and behavioural de cits. Gage sustained a frontal lobe injury in a railroad construction accident while he was using explosives to excavate rocks. A er an unplanned explosion, a large tamping iron used to pack sand over the explosive charge entered through the le side of his skull. is injury surprisingly did not cause immediate death and Gage survived, but sustained profound behavioural changes: a man previously described as proper, well organized, responsible, and serious now exhibited poor judgment, di culties with decision- making, planning, and organizational skills, inappropriate emo- tional outbursts, and lack of inhibitory control.

Fig. 3.3 Passage of the bar through the skull of Phineas Gage, as reconstructed by Harlow in 1868.
Reproduced from Publication of the Massachusetts Medical Society, 2, Harlow JM, Recovery after severe injury to the head, pp. 327–46, Copyright (1868), Massachusetts Medical Society.


e anterior cingulate circuit (ACC)

Neurons in the anterior cingulate cortex (Brodmann’s area 24) serve as the origin of the anterior cingulate-subcortical circuit. E erent projections include those to the ventral striatum, involving the ven- tromedial caudate, ventral putamen, nucleus accumbens, and olfac- tory tubercle, usually named limbic striatum. Fibres from the ventral striatum project to the rostromedial GPi, rostrodorsal SNr, and ven- tral pallidus inferior to the anterior commisure. e GPe connects to the medial STN, which returns to the ventral pallidum, which connects to the magnocellular mediodorsal thalamus. e circuit closes with projections to the anterior cingulate. is circuit is con- sidered to mediate motivated behaviour, reversal learning,34 reward processes and evaluation,35 and it also functions, in part, to signal the occurrence of con icts in information processing, thereby trig- gering compensatory adjustments in cognitive control.36




Spatial working memory

Attentional set-shifting


Ventral tegmental area (dopamine)

Locus coeruleus (norepinephrine)

Dorsal raphé (serotonin)



learning/ extinction

Fig. 3.4 Schematic summary of the di erential impact of ascending monoamine systems on di erent tasks mediated by di erent sectors of the PFC. SSRT: stop- signal reaction time task.
Source data from Annu Rev Neurosci., 32, Robbins TW, Arnsten AF, e neuropsychopharmacology of fronto-executive function: monoaminergic modulation,

pp. 267–87, Copyright (2009), Annual Reviews.

30 SECTION 1 normal cognitive function

asymmetries of the frontal lobes. It is o en assumed that anatomi- cal asymmetries invariably re ect functional asymmetries, but this may not always the case. Language functions have been the most widely studied asymmetries of the frontal lobes, with a le – hemisphere superiority and pro ciency for the majority of vocal, motor, and language production functions.41 Nevertheless, some language capacities exist in most right hemispheres42 such as pros- ody, as well as the expression of the emotional content of language. In patients with brain injury, le frontal lobe damage also typically leads to more profound verbal uency and working memory de – cits than right-sided damage whereas right frontal damage causes de cits primarily in the use and representation of visuospatial data in a variety of tasks.

It has been also reported that the right prefrontal cortex has a predominant role in attentional mechanisms,43 with studies show- ing a striking increase in blood ow and metabolic activity in the right prefrontal cortex including Brodman areas 8, 9, 44, and 46 during selective attention tasks in di erent sensory modalities (e.g. see reference 44). In relation to memory, Tulving and his colleagues proposed that the le and right frontal lobes may play di erent roles in memory processing: encoding information into memory seems to be ‘the’ role of the le prefrontal cortex whereas retrieval is related to the right prefrontal cortex.45 One of the most remark- able asymmetries in the anterior cingulate is at the morphological level: there are two cerebral sulci in the le hemisphere and some- times only one in the right hemisphere. is has been related to cer- tain aspects of e ortful versus automatic vocalization.46 In spite of the large numbers of frontal functions that appear to be lateralized, the only functional asymmetry related strongly to an anatomical asymmetry is that of language and Broca’s area in particular.

Frontal lobe functions

Executive functions (EF)

EF refers to a complex set of processes consisting of various higher- level cognitive functions. ere is a general consensus regarding the type of functions that are grouped under this term. Welsh and Pennington47 de ne EF as ‘the ability to maintain an appropriate problem solving set for attainment of a future goal’, comprising the capacity to inhibit a response, to plan future actions strategically, and to maintain a mental representation of the desired goal stated and the information presented. Furthermore, the EF has also been implicated in emotional and behavioural processes.48 Zelazo, Qu, and Muller49 have conceptualized the involvement of the EF in either ‘cool’, purely cognitive executive processes, or ‘hot’ executive processes, which involve a ect and motivation. Mitchell and Phillips50 suggest that not only does the PFC have a role in cognition and emotion, but that it is also responsible for coordinating the two processes. Laboratory- based executive functions tests have been criticized as lacking in eco- logical validity since the coordination between the two processes is poorly measured in any currently available test.

Executive dysfunction or impaired EF may involve cognitive def- icits such as an inability to focus or maintain attention, impulsiv- ity, disinhibition, reduced working memory, di culties regulating performance, di culties with advanced planning, poor reasoning ability, di culties generating or implementing strategies, perse- verative behaviour, in exibility, and failure to learn from mistakes. Furthermore, in regards to behaviour, maladaptive a ect, poor decision-making, and social behavioural problems have also been identi ed.51

Working memory

is process is essential for e ective executive functioning and engagement in everyday activity.52 Within Baddeley’s model of working memory, working memory is de ned as a limited capac- ity system that allows the temporary storage and manipulation of information necessary for such complex tasks as comprehension, learning, and reasoning. An integrated neural network consisting of the dorsolateral prefrontal cortex, anterior cingulate, parietal and temporal cortices, hippocampus, and basal ganglia all have a role in working memory.53 Patients with working memory de cits can have di culties in remembering information presented only a few minutes earlier and tend to lose track of what they are doing. ey can miss important information during a conversation and can feel overwhelmed and frustrated. e most widely used tests to evaluate this function are the reverse digits span test and the ‘let- ters and numbers’ subtest of the Wechsler Adult Intelligence Scale (WAIS),54 among others (for more information, see chapter 11).

Selective and sustained attention

Selective attention is the ability to attend solely to one type of stimuli while ignoring competing, non-essential stimuli. Sustained attention or vigilance refers to the ability to maintain concentra- tion on a task. e frontal lobes in collaboration with the posterior parietal system and the anterior cingulate gyrus play a role in both types of attention.55 Many researchers use simple tests that measure performance over time to detect sustained attention de cits.

Inhibitory control

is term refers to the ability to suppress or interrupt a previously activated response and resist distraction from external stimuli,56 therefore patients with poor inhibitory control can be impulsive, careless, and intrusive. A network, which includes the lateral PFC, anterior cingulate, and basal ganglia, are responsible for this func- tion.57 Go–no go tests and the Hayling test58 are the most widely used measures for detecting de cits in the inhibitory control domain. e Stroop test59 is also used for measuring this capacity.

Mental exibility

is refers to the ability to respond to di erential environmental demands and to implement di erent problem-solving strategies by switching between thoughts and actions.60 e lateral PFC, the orbitofrontal and parietal cortices, basal ganglia, and cerebellum


Planning is the ability to set future goals, to plan, problem solve, and organize time and resources in order to achieve a task.60 e dorsolateral PFC, anterior cingulate, and caudate nucleus all have a role in planning.63 Frontal lobe lesions can result in planning de cits, di culties initiating activity, and di culty coping with complex situations. e most frequently used tests for detecting planning abilities are the tower tests64 and more ecological valid tests such as the hotel task.65


e term ‘multitasking’ refers to an individual’s ability to simulta- neously perform tasks in order to achieve goals and sub goals. e

are areas associated with this function.
in this domain may appear in exible and rigid, with di culties changing between activities and adapting to new situations. e well-known WCST (Wisconsin Card Sorting Test)62 is the test for measuring mental exibility.

Planning abilities

Patients with problems

anterior PFC, speci cally Brodmann’s area 10, is associated with the abilities necessary for a ective multitasking. Damage to the fron- topolar cortex has been linked to severe disruption of multitask- ing ability and this disruption is exacerbated by a greater degree of damage.66 Several studies have also demonstrated the presence of anterior frontal activity during multitasking67,68 and when switch- ing between di erent cognitive contexts.69 A recent study supports the idea of the potential pivotal role of BA10 in higher order cogni- tive functions.68


is is another important frontal lobe function and refers to the ability to think about one’s own mental processes and state of knowledge. Patients with frontal lobe lesions can demonstrate metacognitive de cits, such as overestimating their performance and capacity to learn.70

Memory systems

Memory refers to the acquisition, storage, retention, and retrieval of information. Within memory, there are three major pro- cesses: encoding, storage, and retrieval. Memory is fundamental for learning as it allows an individual to retain knowledge in order to form associations between behaviour and outcome. Although it has generally been associated with the temporal lobes and speci cally the hippocampus, later research studies focused on the involve- ment of the PFC in memory. Wheeler and colleagues71 performed a meta-analysis of existing memory studies concerned with recall, cued recall, and recognition. is research indicated that frontal lobe damage disrupted performance in all three areas of memory, with the greatest impairment found in free recall, followed by cued recall and then recognition. Furthermore, investigators found that frontal lobe patients have di culties encoding semantic informa- tion,72 determining the temporal order of remembered events,73 and identifying the source of the encoded information.74

It is generally agreed that the frontal lobes do not play a sub- stantial role in the consolidation, storage, and retention of new information,75,76 however they are considered important in the organizational and strategic aspects of episodic memory, essen- tial in encoding, retrieval, and veri cation of memory output.76 Typically, frontal lobe patients have trouble utilizing encoding strategies, which results in a weaker memory trace and subsequent retrieval de cits.

Time travel or chronestaesia

e ability to link the past and the future is known as time travel,77 or chronestaesia.78 It is an important frontal lobe function, essen- tial for autobiographical and prospective memory, and planning. Autobiographical memory is an awareness of the self, held as con- tinuous over time, with an awareness of the past and future. It is mediated by a neural system that includes the anteromedial PFC, which integrates sensory and speci c information.79 Prospective memory is the recall of the intention to act at a certain time or in a certain situation. Planning requires a consideration of present and future actions in order to achieve a goal. Planning activates PFC areas 9, 46, and 10.80 From visual perception to social cognition, the frontal regions of the brain make predictions about incoming actions based on contextual information available and on previ- ous experiences.81,82 Frontal regions provide early feed forward- feedback integration with temporal and visual areas.83 us, the frontal lobes integrate experiences and memory stored in temporal

regions in order to make predictions. For instance, the frontal prediction of actions and thoughts can become memories for the future.84


In 1861, Paul Broca performed a post-mortem examination on a patient who had su ered severe speech/language problems for many years, with speech output limited to the word ‘tan’. At post- mortem, a lesion centred in the le posterior-inferior frontal cortex was detected.85 is case led to an acceptance of the correlation between inferior lateral frontal lobe damage and language disor- der. Certain connections are considered to play a speci c role in language, particularly Brodmann areas 6 and 4 are responsible for motor output and areas 44, 46, and 6, and their subcortical con- nections integrate motor output. It has been proposed that the dorsal lateral frontal and sensory association interconnections are involved in controlling cognition, and the prefrontal and medial frontal connections to the limbic system are involved in response to internal drives.86

Alexander87 suggested that di erent types of language disorders could emerge from frontal lobe lesions:

1. With medial frontal lobe lesions but predominantly to the le lobe, reduction in speech activation or reduced overall ability to utilize speech can be observed. e severity can range from mut- ism, or delayed verbal initiations, to brief, unsustain responses.

2. Following le frontal injury speci cally in the dorsolateral area, disorders such as transcortical motor aphasia (TCMA) can result. is type of lesion leads to imprecise, unconstrained lan- guage with limited, repetitive word use.

3. Lesions to the anterior le frontal lobes can result in more sim- plistic verbal abilities.

4. Finally, with right lateral and anterior frontal lesions, de cits can include poor organization of language, with socially inappropri- ate confabulations.

Although abnormal verbal output can result from lesions in either the right or le frontal lobes, the type of de cits reported di er widely. Damage to the right hemisphere does not cause aphasia, word nding, or grammatical de cits. Lexical, syntactic compre- hension, and articulation are intact. Impairment, instead, is related to prosody, such as in the intonations used when asking a question, or making a statement.88

In addition to the role in cognitive processes, the frontal lobes play a critical role in mediating social behaviour. Some of the fol- lowing abilities are central to developing and maintaining interper- sonal relationships and have been strongly associated with the PFC.

Decision-making (DM)

DM involves weighing up possible positive and negative outcomes associated with a speci c choice of action. A speci c option can then be selected dependent on what the individual considers most bene cial. e Iowa Gambling Task (IGT) was developed to assess how individuals make decisions when faced with real-life situa- tions89 and to detect orbitofrontal cortex dysfunction. However, recent research90,91,92 has further associated performance of this task with other regions, including the dorsolateral prefrontal cor- tex, the amygdala, the basal ganglia, and the anterior cingulate cor- tex, among others. Classical frontal lobe patients favour decisions related to high immediate rewards with longer-term punishments.89

CHAPTER 3 the frontal lobes 31

32 SECTION 1 normal cognitive function

e performance of frontal lobe patients on this assessment has been linked to an impairment of somatic markers, which results in an ‘insensitivity to future rewards’ and therefore instant grati ca- tion is preferred even when paired with longer-term negative con- sequences.93 Torralva and colleagues94 demonstrated that a group of early behavioural-variant frontotemporal dementia patients pre- sented with abnormal decision-making as measured speci cally by the IGT, despite a normal performance on standard cognitive tasks. Consistently, patients with behavioural variant FTD (bvFTD) as well as other diseases including Alzheimer’s, primary progressive aphasia, Parkinson’s, and Huntington’s disease patients can exhibit disadvantageous DM due to involvement of di erent portions of the complex circuitry feeding DM.95–97

eory of mind (ToM)

eory of mind refers to the ability to account for the thoughts, beliefs, intentions, and desires of others while understanding that they may di er from our own. is information is used to form judgments about the likely behaviour and response of another per- son.98 It has been suggested, although not without controversy,99 that ToM is a cognitive module in its own, with an innate neural basis,100 which may in fact be dissociated from other higher func- tions of the PFC such as decision-making.10,94 Studies indicate that patients with orbitofrontal lesions perform worse than those with dorsolateral prefrontal lesions when attempting to identify decep- tion, cheating, faux pas, and empathy.101–103

Moral behaviour

is refers to the ideals of human behaviour based on shared soci- etal values, incorporating concepts of deed and duty, fairness, and self-control.104 Previous studies105 have suggested that the orbital and medial regions of the PFC are responsible for moral judg- ment. Furthermore, a ‘morality network’ consisting of the right ventromedial PFC, orbitofrontal cortex, and amygdala has been suggested (for a review see reference 106). e right ventromedial PFC was included in this morality network for its role in linking external stimuli with socio-emotional value, which in turn could a ect moral judgment. e orbitofrontal cortex appears to inhibit immediate/automatic responses and enables consideration of social prompts, and the amygdala is involved in moral learning and threat response (for review see reference 106). Moll, de Oliveira- Souza, and Eslinger107 expanded on these structures and proposed a brain–behaviour relationships model focused on the interac- tions between emotional, behavioural, and cognitive components. Accordingly, the authors suggested, amongst other structures, the importance of the anterior cingulate cortex, the superior tempo- ral sulcus, the insula, the precuneus, the thalamus, and the basal forebrain. Consistently, studies both in neurodegenerative (e.g. reference 95) and neuropsychiatric populations (e.g. reference 97) a ecting OFC functions, namely empathy/ToM, show patterns of moral judgment that deviate from the norm.


Empathy is a means of demonstrating appropriate social behav- iours and responses in complex or di cult situations. ere are dozens of de nitions of empathy. Baron-Cohen108 de ned empathy as ‘our ability to identify what someone else is thinking or feeling, and to respond to their thoughts and feelings with an appropriate behaviour’. is de nition suggests two stages in the empathy pro- cess: recognition phase and the response action. Empathy therefore

requires not only identifying another person’s feeling or thoughts (which overlaps for many authors with the concept of ToM), but providing an emotional response to it. One of the most important regions involved in the empathy circuit is the medial prefrontal cor- tex, which appears to play an important role for social information processing and for comparing our own perspective to that of oth- ers. Damage to this area, as well as other regions involved in this circuit, such as the inferior frontal gyrus, the frontal operculum, the anterior cingulated, the anterior insula, and the temporo-parietal junction, amongst others, can cause a lower degree of empathy.108

Personality changes

Changes in personality and psychosocial function following pre- frontal lesions have been reported from Gage (see Fig. 3.3) to the present. Damage to the orbital and medial PFC leads to emotional lability as well as to de cits in social and emotional functioning.109

eories of frontal lobe function

Many theories about the functioning of the frontal lobes have been developed with the intention of gaining a better understanding of this complex region. ere is no consensus on which of these theo- ries best captures frontal function. Indeed, many of them are not mutually incompatible. Some of the main PFC models are brie y addressed in this chapter in an attempt to introduce some of the most prominent contemporary models and frameworks to under- stand frontal lobe functions.

Multiple demand system and adaptative coding model

Based on functional neuroimaging (fMRI) and lesion studies that have shown that large parts of the frontal lobe are involved in very diverse cognitive task, some authors have proposed the existence of a multiple-demand (MD) system,110 which comprises circum- scribed regions of lateral and dorsomedial frontal cortex, anterior insula, and the intraparietal sulcus. Following results from single- cell electrophysiology studies in the behaving monkey, this model proposes that neurons of the MD system have the ability to adapt to the current task in order to code the speci c information required for that task.111 Also, recent evidence coming from human neu- roimaging studies have supported this view, demonstrating an adaptive change in the patterns of activation coding task-relevant stimulus distinctions in the frontoparietal. ese and other results have led some authors to suggest that the main function of the MD system is to construct the mental control programmes of organized behaviour.110

Attentional control model

is model112 proposes the existence of two major mechanisms involved in behavioural regulation: the contention scheduler (CS) and the supervisory attentional system (SAS). e CS is concerned with automatic or well-learnt/well-established responses. is pro- cess schedules action while also inhibiting con icting schemata, which structure and organize routine tasks. However, with novel or complex tasks, schemata are unlikely to have developed and, therefore, additional attentional control is required, hence initiat- ing the SAS. e SAS sets priority for actions and brings conscious awareness and re ection to the forefront, rather than solely relying on simple automatic responses originated in the CS. In a three-step process, a strategy is generated: rst, it incorporates a temporary schema for this complex or novel task; second, the schema is imple- mented and monitored; and nally, the schema is either rejected or

modi ed. e SAS is proposed to be located in the PFC and the CS has been linked to the basal ganglia.

Somatic marker hypothesis

Although not without controversy, this model speci cally focuses on the role of emotion in decision-making.113 It proposes that when a di cult situation is encountered, in order to make a choice or decision, somatic markers stored as memories of past speci c behavioural experiences and outcomes are activated. is system can be in e ect even without the conscious awareness of the past event. Somatic markers are proposed to be stored in the ventro- medial PFC and the model surmises that damage to this area can result in an inability to access somatic markers, which thus results in decision-making skill de cits.114

Temporal organization model

is model proposes that the PFC temporally organizes behaviour with that process constrained by short-term memory, motor atten- tion, and the inhibition control of interference.115 e framework describes mechanisms for monitoring and memory and atten- tional selection that prioritize goals and ensure that behavioural sequences are performed in the correct order. Temporal integration is mediated by the activity of PFC neurons and also by interactions between the PFC and posterior cortex—the speci c posterior corti- cal areas that are involved in these interactions are determined by the modalities of the sensory and motor information. is model emphasizes processes of attention, short-term memory, and inhibi- tory control, however, the author also describes PFC function in terms of ‘motor memory’ (schemata), with a hierarchy of motor representations within the PFC. Attention and working memory are properties of the representations (neural networks), rather than explicit ‘processes’ in terms of computational procedures. Fuster’s model is a hybrid of the representational and processing approaches and is consistent with the evolution and neurophysiol- ogy of the PFC. Motor memories that are stored in the PFC become more complex or abstract in anterior frontal regions. Fuster pro- poses that the functions of the ventromedial PFC parallel those of the dorsolateral PFC, but with the addition of emotional informa- tion, given the connectivity between ventromedial PFC and limbic regions (such as the amygdala). He supports the idea that automatic actions are stored in the basal ganglia and the premotor cortex, with PFC representation reserved for actions or behaviours that are not habitual or well learned. Consistent with this viewpoint, the premotor cortex and basal ganglia are known to be important in movement preparation; however, the PFC has been implicated in both novel and well-learned tasks.

Anterior attentional functions

Stuss4 further developed Fuster’s115 model regarding the associa- tion between the frontal lobe and basic schemas, by incorporating a theory of the executive system. According to Stuss, a schema is a network of multiple, connected neurons that can be activated by sensory input, by other schemata, or by the executive control system (Fig. 3.5). Also, it has been suggested that schemata pro- vide feedback to the executive system and compete to control of thought and behaviour. is process is governed by the conten- tion scheduling process described in Norman and Shallice’s atten- tional control model. Once activated, schemas can remain active for varying periods of time depending on the goal and whether further input is received from the executive control system. is

Fig. 3.5 Supervisory systems in human attention.
Adapted from Annals of the New York Academy of Science, 769, Stuss DT, Shallice T, Alexander M, and Picton T, A multidisciplinary approach to anterior attentional functions, pp. 191–211, Copyright (1995), with permission from John Wiley and Sons.

might be seconds sometimes or for longer periods, and activation has to be maintained by repeated input from the executive control system. Attention is the main focus in Stuss’s theory. is theory proposed seven types of attentional functions, each of which has its neural correlates: sustaining (right frontal), concentrating (cingu- late), sharing (cingulate plus orbitofrontal), suppressing (DL-PFC), switching (DL-PFC plus medial frontal), preparing (DL-PFC), and setting (le DL-PFC).

Working memory model

When an individual engages in complex cognitive tasks such as lan- guage comprehension, learning, and reasoning, the information is simultaneously and temporarily stored and manipulated within the brain in a system that has been termed working memory. Originally, according to the model advanced by Baddeley and Hitch,116 there were three components to working memory, the most important of which was the central executive, accompanied by the visuos- patial sketchpad and the phonological loop as ‘slave’ subsystems. Recently, in response to criticisms of the model, a fourth system named the episodic bu er was incorporated.52 e central execu- tive is capable of controlling the attention a orded to two or more activities occurring simultaneously, whilst also controlling the access to information in long-term memory store. e visuospatial sketchpad holds visual images whilst the phonological loop con- tains information about speech-based information (Fig. 3.6).

CHAPTER 3 the frontal lobes 33

Supervisory System







Perceptual Information



Effector System


Central executive


Visuospatial sketchpad

Episodic buffer

Phonological loop


Visual Episodic semantics LTM



Fluid systems

Crystallized systems

Fig. 3.6 Working memory model.
Reproduced from Trends Cogn Sci., 4(11), Baddeley A, e episodic bu er: a new component of working memory? pp. 417–23, Copyright (2000), with permission from Elsevier.

34 SECTION 1 normal cognitive function

Structured event complex (SEC) framework

a ‘gateway’ between the internal mental life that occurs independ- ently of environmental stimuli and the mental life that is associated with interaction with the external world.


Given the complexity of the human frontal lobes and their intri- cate, expansive neural connections, a complete appreciation of the wide range of functions associated with these areas is fundamental in order to understand human cognition fully in both health and disease conditions.

New approaches have been developed from disciplines such as social cognition and studies of decision-making, theory of mind, empathy and moral behaviour providing a broader and ecologically valid approach to the understanding of the frontal lobe functions.

Our identity as autonomous human beings, our drives, ambitions, and essence are greatly dependent on our frontal lobes and further research is required to deepen our understanding of such complex cerebral region. With this in mind, the near future is likely to be an exciting time for the eld of cognitive and social neurosciences, as our knowledge continues to develop in regards to perhaps the most uniquely human of all brain structures, our frontal lobes.


We appreciate the assistance of Clara Pinasco in formatting and ref- erencing the manuscript.

is research was partially supported by grants CONICYT/ FONDECYT Regular (1130920 and 1140114), Foncyt-PICT 2012-0412, Foncyt-PICT 2012-1309, CONICET, and INECO Foundation.


1. Mesulam M. e human frontal lobes: Transcending the default mode through contingent encoding. In: D Stuss and R Knight (eds). Principles of Frontal Lobe Function. New York, NY: Oxford University Press, 2002, pp. 8–30.

2. Fletcher PC and Henson RN. Frontal lobes and human mem-
ory: insights from functional neuroimaging. Brain. 2001;124:849–81.

3. Dias R, Robbins TW, and Roberts AC. Dissociation in prefrontal cortex of a ective and attentional shi s. Nature. 1996;380:69–72.

4. Stuss DT, Shallice T, Alexander M, et al. A multidisciplinary approach to anterior attentional functions. Ann NY Acad Sci. 1995;769:191–211.

5. Eslinger PJ and Damasio AR. Severe disturbance of higher cogni- tion a er bilateral frontal lobe ablation: patient EVR. Neurology. 1985;35:1731–41.

6. Iacoboni M and Dapretto M. e mirror neuron system and the conse- quences of its dysfunction. Nature Neurosci. 2006;7(12):942–51.

7. Schacter DL, Addis DR, and Buckner RL. Remembering the past to imagine the future. Nature Neurosci. 2007;8(9):657–61.

8. Stuss DT and Gow CA. ‘Frontal dysfunction’ a er traumatic brain injury. Neuropsy, Neuropsy Be. 1992;5(4):272–82.

9. Neary D, Snowden JS, Gustafson L, et al. Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology. 1998;51(6):1546–54.

10. Torralva T, Roca M, Gleichgerrcht E, et al. A neuropsychological battery to detect speci c executive and social cognitive impairments in early frontotemporal dementia. Brain. 2009;132:1299–309.

11. Townsend JD, Sugar CA, Walshaw PD, et al. Frontostriatal neuroimag- ing ndings di er in patients with bipolar disorder who have or do not have ADHD comorbidity. J A ect Disord. 2013;147:389–96.

e SEC is considered a sequential set of events that are goal ori- entated and represent the performance of a functional activity.117 e SEC contains a set of linked memories that represent thematic knowledge, morals, abstractions, concepts, and social rules, among others. e SEC has been described as a ‘memory engine’. Although the di erent components within a SEC are stored in di erent parts of the PFC and are represented uniquely, they are encoded and retrieved in unison. Anatomically, SEC components have connec- tions to the posterior (temporal-parietal) or subcortical regions (basal ganglia, hippocampus, amygdala). e model proposes that damage to the SEC results in behavioural problems, as the indi- vidual has di culty processing behavioural and social informa- tion, and thus in anticipating future episodes. Damage to speci c areas of the PFC would result in speci c di culties. For example, with ventromedial PFC damage, social behavioural problems can arise,118 whereas with dorsolateral PFC damage, impairment of re ective and mechanistic behaviour has been reported.119

Hierarchical organization of the prefrontal cortex

e PFC enables us to select speci c actions or thoughts in rela- tion to internal goals, which is the underlying core process behind executive control. For this reason, PFC functions are usually under- stood from the point of view of phenomenological events, including concepts such as goals, tasks, or intentions. Based on neuroimag- ing data, however, Koechlin and Summer eld120 propose a quanti- tative model in which action selection is guided by hierarchically ordered control signals and processed in a network of brain regions organized along the anterior–posterior axis of the lateral prefrontal cortex. e theory clari es how executive control can operate as a unitary function, despite the requirement that information be inte- grated across multiple distinct, functionally specialized prefrontal regions.

e ‘gateway’ hypothesis

e ‘gateway’ hypothesis121 of rostral PFC developed by Burgess and collaborators proposes that lateral and medial regions of ros- tral PFC are di erentially sensitive to changes in demands for stimulus-oriented (SO) or stimulus-independent (SI) attending. According to this model, four interlinked propositions support its central idea: rst, some forms of cognition are triggered by percep- tual experience (i.e. input through basic sensory systems), whereas other forms of cognition occur in the absence of sensory input; sec- ond, some central representations are activated both when a person witnesses an external stimulus and when they merely imagine it; third, if the rst and second are true, then it is plausible that there is some brain system that can determine, when required, the source of activation of the central representations, which they refer to as the ‘supervisory attentional gateway’ (SAG). Proposition four is that rostral PFC plays a part in this mechanism.

is hypothesis assumes that there is, normally, continuous com- petition for activation of central representations between (i) input from sensory systems, (ii) reciprocal or associative activation from within the system, and (iii) ‘top-down’ in uence from other super- visory systems. us many well-speci ed and/or familiar situations will require minimal operation of the SAG system. e proposal suggests that the SAG system a ects the coordination of SI and SO cognition, speci cally in situations where selection by this compe- tition fails or is producing maladaptive behaviour and operates as

12. Torralva T, Strejilevich S, Gleichgerrcht E, et al. De cits in tasks of executive functioning that mimic real-life scenarios in bipolar disorder. Bipolar Disord. 2012;14(1):118–25.

13. Cohen JD and Servan-Schreiber D. A theory of dopamine function and its role in cognitive de cits in schizophrenia. Schizophrenia Bulletin. 1993;19(1):85–104.

14. Mayberg HS, Liotti M, Brannan SK, et al. Reciprocal limbic-cortical function and negative mood: Converging PET ndings in depression and normal sadness. Am J Psychiatry. 1999;156(5):675–82.

15. Semendeferi K, Lu A, Schenker N, et al. Humans and great apes share a large frontal cortex. Nature Neurosci. 2002;5:272–6.

16. Rilling JK and Insel TR. e primate neocortex in compara- tive perspective using magnetic resonance imaging. J Hum Evol. 1999;37(2):191–223.

17. Semendeferi K, Damasio H, Frank R, et al. e evolution of the frontal lobes: a volumetric analysis based on three-dimensional reconstructions of magnetic resonance scans of human and ape brains. J Hum Evol. 1997;32:375–88

18. Jones EG. e alamus. New York: Plenum Press, 1985.

19. Yeterian EH, Pandya DN, Tomaiuolo F, et al. e cortical connec-
tivity of the prefrontal cortex in the monkey brain. Cortex. 2012;

20. Petrides M and Pandya DN. Comparative architectonic analysis of
the human and macaque frontal cortex. In: F Boller and J Grafman (eds). Handbook of Neuropsychology, Vol 8. Amsterdam: Elsevier, 1994, pp. 17–57.

21. Barbas H. Organization of the principal pathways of prefrontal lateral, medial, and orbitofrontal cortices in primates and implications for
the collaborative interaction in executive functions. In: J Risberg
and J Grafman (eds). e Frontal Lobes. Development, Function
and Pathology. New York, NY: Cambridge University Press; 2006,
pp. 21–68.

22. Cummings JL. Anatomic and behavioral aspects of frontal-subcortical
circuits. In: J. Grafman, KJ Holyoak, and F Boller (eds). Structure and Functions of the Human Prefrontal Cortex, Vol 769. New York, NY: New York Academy of Sciences, 1995, pp. 1–13.

23. Petrides M and Pandya D. Association Pathways of the Prefrontal Cortex and Functional Observations. In: D Stuss and R Knight (ed.). Principles of Frontal Lobe Functions. Oxford: Oxford University Press, 2002, pp. 31–50.

24. Selemon LD, Rajkowska G, and Goldman-Rakic PS. Abnormally high neuronal density in the schizophrenic cortex: A morphometric analysis of prefrontal area 9 and occipital area 17. Archiv Gen Psychiat. 1995; 52:805–18.

25. Middleton FA and Strick PL. Basal ganglia and cerebellar loops: Motor and cognitive circuits. Brain Res. 2000;31(2–3):236–50.

26. Lezak MD. e problem of assessing executive functions. Int J Psychol. 1982; 17(2–3): 281–97.

27. Stuss DT and Alexander MP. Executive functions and the frontal lobes: a conceptual view. Psychol Res. 2000;63(3–4):289–98. Review.

28. Saint-Cyr JA, Bronstein YL, and Cummings J. Neurobehavioral Consequences of Neurosurgical Treatments and Focal Lesions of Frontal-Subcortical Circuits. In: D Stuss and R Knight (eds). Principles of Frontal Lobe Functions. Oxford: Oxford University Press, 2002,
pp. 408–27.

29. Haber SN, Kunishio K, Mizobuchi M, et al. e orbital and medial pre-
frontal circuit through the primate basal ganglia. J Neurosci. 1995;15(7
Pt 1):4851–67.

30. Ilinsky LA, Jouandet ML, and Goldman-Rakic PS. Organization of the
nigrothalamocortical system in the rhesus monkey. Journ Comp Neurol.

31. Price JL. Architectonic structure of the orbital and medial prefrontal
cortex. In: DH Zald and SL Rauch (eds). e Orbitofrontal Cortex.
New York, NY: Oxford University Press, 2006, pp. 3–17.

32. Cummings JL. Frontal-subcortical circuits and human behaviour.
Archiv Neurol. 1993;50:873–80.

33. Harlow JM. Recovery a er severe injury to the head. Publication of the
Massachussetts Medical Society. 1868;2:327–46.

34. Hampshire A, Chaudhry AM, Owen AM, et al. Dissociable roles for lat- eral orbitofrontal cortex and lateral prefrontal cortex during preference driven reversal learning. Neuroimage. 2012;59(4):4102–12.

35. Baker TE and Holroyd CB. Dissociated roles of the anterior cingulate cortex in reward and con ict processing as revealed by the feedback error-related negativity and N200. Biol Psychol. 2011;87(1):25–34.

36. Botvinick M, Cohen JD, and Carter CS. Con ict monitoring and ante- rior cingulate cortex: an update. Trends Cogn Sci. 2004;8(12):539–46.

37. Holroyd CB and Yeung N. Motivation of extended behaviors by anterior cingulate cortex. Trends Cogn Sci. 2012 Feb;16(2):122–8.

38. Gamo NJ and Arnsten AF. Molecular modulation of prefrontal cortex: rational development of treatments for psychiatric disorders. Behav Neurosci. 2011;125(3):282–96.

39. Robbins TW and Arnsten AF. e neuropsychopharmacology of fronto-executive function: monoaminergic modulation. Annu Rev Neurosci. 2009;32:267–87.

40. Chudasama Y and Robbins TW. Functions of frontostriatal systems incognition: comparative neuropsychopharmacological studies in rats, monkeys and humans. Biol Psychol. 2006;73(1):19–38.

41. Geschwind N. e organization of language and the brain. Science. 1970 Nov 27;170(3961):940–4.

42. Iacoboni M and Zaidel E. Hemispheric independence in word recogni- tion: evidence from unilateral and bilateral presentations. Brain Lang. 1996 Apr;53(1):121–40.

43. Heilman KM, Bowers D, Valenstein E, et al. Disorders of visual atten- tion. Baillieres Clin Neurol. 1993 Aug;2(2):389–413.

44. Lewin JS, Friedman L, Wu D, et al. Cortical localization of human sus- tained attention: detection with functional MR using a visual vigilance paradigm. J Comput Assist Tomogr. 1996 Sep–Oct;20(5):695–701.

45. Tulving E. Episodic memory: from mind to brain. Annu Rev Psychol. 2002;53:1–25.

46. Paus T, Koski L, Caramanos Z, et al. Regional di erences in the e ects of task di culty and motor output on blood ow response in the human anterior cingulate cortex: a review of 107 PET activation studies. Neuroreport. 1998 Jun 22;9(9):R37–47. Review.

47. Welsh MC and Pennington BF. Assessing frontal lobe function-
ing in children: views from developmental psychology. Dev Psychol. 1988;4(3):199–230.

48. Gioia GA, Isquith PK, and Guy SC. Assessment of executive functions in children with neurological impairment. In: RJ Simeonsson and
L Rosenthal (eds). Children with Disabilities and Chronic Conditions. New York, NY: Guilford Press, 2001, pp. 317–56.

49. Zelazo PD, Qu L, and Muller U. Hot and cool aspects of execu-
tive function: Relations in early development. In: W Shneider, R Schumann-Hengsteler, and B Sodian (eds). Young Children’s Cognitive Development: Interrelationships among Executive Functioning, Working Memory, Verbal Ability, and eory of the Mind. Mahwah, NJ: Lawrence Erlbaum Associates Publishers, 2004, pp. 71–93.

50. Mitchell RL, and Phillips LH. e psychological, neurochemical and functional neuroanatomical mediators of the e ects of posi- tive and negative mood on executive functions. Neuropsychologia. 2007;45(4):617–29. Review.

51. Muscara F, Catroppa C, and Anderson V. e impact of injury severity on executive function 7–10 years following pediatric traumatic brain injury. Dev Neuropsychol. 2008;33(5):623–36.

52. Baddley A. Fractioning the central executive. In: D Stuss and R Knight, (eds). Principles of the Frontal Lobe Function. New York, NY: Oxford University Press, 2002, pp. 246–60.

53. Curtis CE, Zald DH, and Pardo JV. Organization of working memory within the human prefrontal cortex: a PET study of self-ordered object morking memory. Neuropsychologia. 2000;38(11):1503–10.

54. Wechsler D. Wechsler Intelligence Scales for Children, 3rd edn. San Antonio, TX: e Psychological Corporation, 1991.

55. Fan J, McCandliss BD, Fossella J, et al. e activation of attentional networks. Neuroimage. 2005;26(2):471–9.

56. Barkley RA. Behavioral inhibition, sustained attention, and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin. 1997;121(1):65–94.

CHAPTER 3 the frontal lobes 35

36 SECTION 1 normal cognitive function

57. Tamm L, Menon V, and Reiss AL. Maturation of brain func-
tion assosiated with response inhibition. J Am Acad Child Psy.

58. Burgess PW and Shallice T. e Hayling Test and Brixton Tests.
urston, Su olk: ames Valley Test Company, 1997.

59. Golden CJ. Stroop Color and Word Test. A Manual for Clinical and
Experiemental Uses. Wood Dale, IL: Stoelting Co, 1978.

60. Lezak M. Neuropsychological Assesment. New York, NY: Oxford
University Press, 1993.

61. Buchsbaum BR, Creer S, Wei-Li C, et al. Meta-analisys of neuroimaging
studies of the Wisconsin Card-Sorting Task and component processes.
Hum Brain Mapp. 2005;25:35–45.

62. Nelson H. A modi ed card sorting response sensitive to frontal lobe
defects. Cortex. 1976;12:313–24.

63. Dagher A, Owen AM, Boecker H, et al. Mapping the network for plan-
ning: A correlational PET activation study with the Tower of London
task. Brain. 1999;122:1973–87.

64. Shallice T. Speci c impairments of planning. Philos Trans R Soc Lond B
Biol Sci. 1982;298(1989):199–209.

65. Manly T, Hawkins K, Evans J, et al. Rehabilitation of executive func-
tion: A facilitation of e ective goal management on complex tasks using
periodic auditory alerts. Neuropsychologia. 2002;40:2671–81.

66. Dreher JC, Koechlin E, Tierney M, et al. Damage of the frontal-
polar cortex is associated with impaired multitasking. PLoS One.

67. Burgess PW, Quayle A, and Frith CD. Brain regions involved in
prospective memory as determined by positron emission tomography.
Neuropsychologia. 2001;39:545–55.

68. Badre D and D’Esposito M. Functional magnetic resonance imag-
ing evidence for a hierarchical organization of the prefrontal cortex.
J Cognitive Neurosci. 2007;19:2082–99.

69. Roca M, Torralva T, Gleichgerrcht E, et al. e role of Area 10
(BA10) in human multitasking and in social cognition: a lesion study.
Neuropsychologia. 2011;49 (13):3525–31

70. Shimamura AP and Squire LR. Memory and metamemory: a study of
the feeling-of-knowing phenomenon in amnesic patients. J Exp Psychol
Learn Mem Cogn. 1986;12(3):452–60.

71. Wheeler MA, Stuss DT, and Tulving E. Frontal lobe damage pro-
duces episodic memory impairment. J Int Neuropsychol Soc.

72. Moscovitch M. Multiple dissociations of function in amnesia.
In: L Cermak (ed.). Human Memory and Amnesia. Hillsdale,
NJ: Erlbaum, 1982, pp. 337–70.

73. Shimamura AP. Memory and amnesia. West J Med. 1990;152(2):177–8.

74. Janowsky JS, Shimamura AP, and Squire LR. Source memory
impairment in patients with frontal lobe lesions. Neuropsychologia.

75. Petrides M. Dissociable roles of mid-dorsolateral prefrontal and
anterior inferotemporal cortex in visual working memory. J Neurosci.


84. 85.

86. 87.




91. 92. 93.




97. 98. 99.



Kveraga K, Ghuman AS, Kassam KS, et al. Early onset of neural syn- chronization in the contextual associations network. Proc Natl Acad Sci USA. 2011;108(8):3389–94.
Fuster JM. e prefrontal cortex—an update: time is of the essence. Neuron. 2001;30(2):319–33.

Signoret JL, Castaigne P, Lhermitte F, et al. Rediscovery of
Leborgne’s brain: anatomical description with CT scan. Brain Lang. 1984;22(2):303–19.
Alexander MP, Benson DF, and Stuss DT. Frontal lobes and language. Brain Lang. 1989;37(4):656–91.
Alexander MP. Disorders of language a er frontal lobe
injury: Evidence of the neural mechanisms of assembling language. In: D Stuss and R Knight (eds). Principles of Frontal Lobe Function. New York, NY: Oxford University Press, 2002, pp. 159–67.
Weintraub S, Mesulam MM, and Kramer L. Disturbances in
prosody. A right-hemisphere contribution to language. Arch Neurol. 1981;38(12):742–44.
Bechara A, Damasio AR, Damasio H, et al. Insensitivity to future con- sequences following damage to human prefrontal cortex. Cognition. 1994;50:7–15.
Clark L, Manes F, Antoun N, et al. e contributions of lesion lateral- ity and lesion volume to decision-making impairment following frontal lobe damage. Neuropsychologia. 2003;41(11):1474–83. Seymour B and Dolan R. Emotion, decision making, and the amyg- dala. Neuron. 2008;58(5):662–71.
Kable JW and Glimcher PW. e neurobiology of decision: consensus and controversy. Neuron. 2009;63(6):733–45.
Bechara A, Damasio H, and Damasio AR. Emotion, decision mak- ing and the orbitofrontal cortex. Cereb Cortex. 2000;10(3):295–307. Review.
Torralva T, Kipps CM, Hodges JR, et al. e relationship between a ective decision-making and theory of mind in the frontal variant of fronto-temporal dementia. Neuropsychologia. 2007;45:342–9. Gleichgerrcht E, Ibáñez A, Roca M, et al. Decision-making cognition in neurodegenerative diseases. Nat Rev Neurol. 2010;6(11):611–23. Epub 2010 Oct 12. Review.
Manes F, Torralva T, Ibáñez A, et al. Decision-making in frontotem- poral dementia: clinical, theoretical and legal implications. Dement Geriatr Cogn. 2011;32(1):11–17.
Gleichgerrcht E, Torralva T, Roca M, et al. Decision making cognition in primary progressive aphasia. Behav Neurol. 2012; 25(1):45–52. Bibby H and McDonald S. eory of mind a er traumatic brain injury, Neuropsychologia. 2005;43:99–114.
Mar RA. e neural bases of social cognition and story comprehen- sion. Annu Rev Psychol. 2011;62:103–34.
Happe F, Brownwell H, and Winner E. Acquired ‘theory of mind’ impairments following stroke. Cognition. 1999;70(3):211–40.
Stuss DT, Gallup GG, and Alexander MP. e frontal lobes are neces- sary for ‘theory of mind’. Brain. 2001;124:279–86.
Shamay-Tsoory SG, Tomer R, Berger BD, et al. Characterization of empathy deficits following prefrontal brian damage: the
role of the right ventromedial prefrontal cortex. J Cogn Sci. 2003;15:324–37.
Stone V, Baron-Cohen S, Calder A, et al. Acquired theory of
mind impairments in individuals with bilateral amigdala lesions. Neuropsychologia. 2003;41(2):209–20.
Wilson MS. Social dominance and ethical ideology: the end justi es the means? J Soc Psychol. 2003;143(5):549–58.
Moll J, de Oliveira-Souza, R, Eslinger PJ, et al. e neural correlates of moral sensivity: a functional magnetic resonance imaging investiga- tion of basic and moral emotions. J Neurosci. 2002; 22:2730–6. Mendez MF. What frontotemporal dementia reveals about the neuro- biological basis of morality. Med Hypotheses. 2006;67(2):411–8.
Moll J, de Oliveira-Souza R, and Eslinger PJ. Morals and the human brain: a working model. NeuroReport. 2003;14:299–305. Baron-Cohen, S. Zero Degrees of Empathy: A New eory of Human Cruelty. London: Clays Ltd., 2011.

2000;20:7496–503. 102. 76. Wincour G, McDonald RM, and Moscovitch M. Anterograde and retro-

grade amnesia in rats with large hippocampal lesions. Hippocampus.


77. Fuster JM. Executive frontal functions. Exp Brain Res.
2000;133(1):66–70. Review.

78. Tulving E. Chronestesia: Conscious awareness of subjective time. In: D
Stuss and R Knight (eds). Principles of Frontal Lobe Function. New York,
NY: Oxford University Press, 2002, pp. 311–25

79. Levine B. Autobiographical memory and the self in time: brain lesion
e ects, functional neuroanatomy, and lifespan development. Brain
Cognition. 2004;55:54–68.

80. Cabeza R and Nyberg L. Imaging cognition II: an empirical review of
275 PET and fMRI studies. J Cognitive Neurosci. 2000;12:1–47.

81. Bar M. e proactive brain: memory for predictions. Philos Trans R
SocLond B Biol Sci. 2009;364(1521):1235–43.

82. Ibañez A and Manes F. Contextual social cognition and the behavioral
variant of frontotemporal dementia. Neurology. 2012;78(17):1354–62.


104. 105.

106. 107. 108.

109. Eslinger PJ, Flaherty-Craig CV, and Benton AL. Developmental out- comes a er prefrontal cortex damage. Brain Cognition. 2004; 22:84–103.

110. Duncan J. e multiple-demand (MD) system of the primate brain: mental programs for intelligent behaviour. Trends Cogn Sci. 2010 Apr;14(4):172–9.

111. Freedman DJ, Riesenhuber M, Poggio T, et al. Categorical representa- tion of visual stimuli in the primate prefrontal cortex. Science. 2001 Jan 12;291(5502):312–6.

112. Norman DA and Shallice T. Attention to action: Willed and automatic control of behaviour. In: RJ Davidson, GE Schwartz, and DE Shapiro (eds). Conciousness and Self-Regulation, Vol 4. New York, NY: Plenum Press, 1986, pp. 1–14.

113. Damasio AR. e somatic marker hypothesis and the possible func- tions of the prefrontal cortex. Philos Trans R Soc Lond B Biol Sci. 1996;351(1346):1413–20. Review.

114. Bechara A, Damasio H, and Damasio AR. e somatic marker hypothesis and Decision Making. In: F Boller, J Grafman (eds). Handbook of Neuropsychology: Frontal Lobes, 2nd edn. Amsterdam: Elsevier, 2002, pp. 117–43.

115. Fuster JM. Network Memory. Trends Neurosci. 1997;20(10):451–9. Review.

116. Baddeley A. e episodic bu er: a new component of working memory? Trends Cogn Sci. 2000;4(11):417–23.

117. Grafman J. e human prefronal cortex has evolved to represent com- ponents of structured event complexes. In: J Grafman (ed.). Handbook of Neuropsychology. Amsterdam: Elsevier, 2002, pp. 157–74.

118. Grafman J, Schwab K, Warden D, et al. Frontal lobe injuries, violence and agression: A report of the Vietnam head injury study. Neurology. 1996;46:1231–8.

119. Burgess PW, Veitch E, De Lacy Costello A, et al. e cognitive and neuroanatomical correlates of multitasking. Neuropsychologia. 2000;38:848–63.

120. Koechlin E and Summer eld C. An information theoretical approach to prefrontal executive function. Trends Cogn Sci. 2007 Jun;11(6):229–35.

121. Burgess PW, Dumontheil I, and Gilbert SJ. e gateway hypothesis of rostral prefrontal cortex (area 10) function. Trends Cogn Sci. 2007 Jul;11(7):290–8.

CHAPTER 3 the frontal lobes 37


e temporal lobes

Morgan D. Barense, Jason D. Warren, Timothy J. Bussey, and Lisa M. Saksida

Introduction to the temporal lobes

e temporal lobes are essential for our memory and understand- ing of the world, including our knowledge about our very selves, and our ability to communicate e ectively with other human beings. As a result, the consequences of damage to the temporal lobes—as can occur following insults including surgery, stroke, viral infection, or Alzheimer’s disease—can be devastating (see Boxes 4.1 and 4.2 for some key historical examples). As we will see, however, the temporal lobe is not a unitary structure with a single function. How therefore can we understand how these dif- ferent functions are organized within the temporal lobes? We start by considering the anatomy.

Temporal lobe circuitry

e temporal lobe is the region of cerebral cortex that lies inferior to the Sylvian (lateral) ssure (Fig. 4.2a). Posteriorly, the temporal lobe is bounded by the ventral edge of the parietal lobe and the anterior edge of the occipital lobe. e temporal lobes comprise approximately 20 per cent5,6 of total cerebral cortex volume in humans. Regions on the lateral surface can be divided into those that represent auditory information (Brodmann areas 41, 42, 22) and those that represent visual information (Brodmann areas 20, 21, 37, 38) (Fig. 4.2b and c).

e rst sulcus inferior to the Sylvian ssure is the superior temporal sulcus (STS), which contains multimodal cortex receiv- ing inputs from visual, auditory, and somatic regions in addition

Box 4.1 Case study 1: Dense global amnesia

In 1953, a 27-year-old man, known to researchers by the initials HM, underwent experimental brain surgery—bilateral removal of his medial temporal lobes (MTL) (Fig. 4.1)—to treat his severe epilepsy. HM emerged from the surgery profoundly, and irrevocably, amne- sic. Until his death in 2008, each new experience he had and each new person he met was destined to be forgotten, leaving his existence in an eternal present. In the words of HM himself, ‘Every day is alone in itself, whatever enjoyment I’ve had and whatever sorrow I’ve had.’1

During neuropsychological examination he would look up between tests and anxiously say, ‘Right now, I’m wondering. Have I done or said anything amiss? You see, at this moment everything looks clear to me, but what happened just before? at’s what worries me. It’s like waking from a dream; I just don’t remember.’2

HM did not know that decades had elapsed since his surgery, he did not know his age, or whether he had grey hair.3 He knew about the Second World War and the crash of the stock market in 1929, but he could not remember the scientists that worked with him continu- ously until his death. Mercifully, his personality and intellect were unchanged, and he was a gracious and patient man who generously devoted himself to a life as an object of intensive scienti c study, making him likely the most important single case study in the history of brain science.




Fig. 4.1 HM’s medial temporal lobe lesion. (a) Coronal image depicting the temporal lobe of HM (shown on left) and an age-matched control (shown on right).
A = amygdala; H = hippocampus; cs = collateral sulcus; PR = perirhinal cortex; EC = entorhinal cortex. (b) Sagital section from the left side of HM’s brain. e asterisk depicts the resected portion of the anterior temporal lobes. e arrow depicts the remaining intraventricular portion of the hippocampus.
Reproduced from J Neurosci, 17(10), Corkin S, Amaral DG, Gonzalez RG, et al. HM’s Medial Temporal Lobe Lesion: Findings from Magnetic Resonance Imaging, pp. 3964–979, Copyright (1997), with permission from the Society for Neuroscience.


normal cognitive function

Box 4.2 Case study 2: Wernicke’s aphasia

In 1874, a young psychiatrist, Carl Wernicke, working in Breslau, recorded the clinical details of his patient, SA, a 59-year-old woman who had suddenly lost all ability to understand speech.4 She gave ‘completely absurd’ answers to questions, and her con- versation (though grammatical) was frequently garbled and marred by neologisms. She had di culty naming familiar items, even though she remained able to use them competently.

A er a more detailed assessment, Wernicke found that she had no other evidence of ‘profound mental deterioration’: he concluded instead that she had a selective impairment in com- prehending speech signals, a ‘sensory aphasia’. SA’s language dis- turbance resolved steadily over the next few months, but her case prompted Wernicke to review the clinical records of his previous patients. ese included one patient with a similar language syn- drome who had come to post-mortem showing focal infarction of the rst and second temporal convolutions within the le cer- ebral hemisphere.

Wernicke proposed that the culprit lesion in such cases, involving temporal lobe areas in proximity to auditory cortex, produces a fundamental defect of the ‘sound images’ for words. is insight led him to develop the rst coherent model of a dis- tributed, dominant hemisphere language circuit, linking speech perception ultimately with speech output. Wernicke’s model pro- vided a framework for understanding various selective disorders of language due to acute brain lesions or focal cerebral degen- erations. ough rst clearly described over a century ago, these disorders continue to inspire debate today.

to polymodal input from frontal and parietal regions. e middle and inferior temporal gyri (corresponding to Brodmann areas 20 and 21; also called area TE) comprise inferotemporal (IT) cortex, a region critical for visual object recognition. e medial temporal lobes (MTL) are a collection of heavily interconnected structures, which include allocortical structures such as the hippocampus and adjacent entorhinal, perirhinal, and parahippocampal cortex (Fig. 4.2d), and are traditionally believed to form a system devoted to long-term memory. At the tip of the temporal lobe is the temporal pole, a region critical for conceptual knowledge and social concep- tual information processing.

However, brain regions do not operate in isolation but are inter- connected in functional circuits comprising a number of cortical and allocortical regions. Of course, the connectivity between brain regions is rich and complex, and the temporal lobes are no excep- tion in this regard. Nevertheless, when considering function it is useful to think in terms of three major pathways associated with this region (Fig. 4.3).

1. Cortical modality-speci c sensory streams (devoted to only one sensory modality). Although the temporal lobes receive inputs from all modalities, for the present purposes we will focus on the visual and auditory pathways (Fig. 4.3a).

2. e continuation of these streams into cortical regions of the superior temporal sulcus (STS) and middle temporal gyrus (MTG) (Fig. 4.3b).

3. e continuation of these streams into the structures within the medial portion of the temporal lobes (MTL) (Fig. 4.3c).

Functions of the temporal lobes

Circuit 1. Cortical modality-speci c sensory streams for vision and audition

e ventral visual stream (VVS)

As visual information leaves the striate cortex in the occipital lobes, it is organized into two functionally specialized hierarchical pro- cessing pathways. e ‘dorsal stream’ courses dorsally towards parietal regions and is crucial for processing the spatial locations of objects, as well for visually guiding actions towards objects in space.7 e ‘ventral visual stream’ (VVS) extends ventrally through IT cortex towards anterior temporal regions and is crucial for the visual identi cation of objects (8) (Fig. 4.4a). ese pathways have been dubbed the ‘where/how’ (dorsal) and ‘what’ (ventral) path- ways. is section will focus on the ventral stream, the dorsal stream is discussed further in chapter 5.

e organization of the ventral stream is hierarchical, such that low-level inputs are transformed into more complex representations through successive stages of processing. As information progresses through the stream, receptive eld size and neuronal response laten- cies increase, and the neurons increase the complexity of their tun- ing, with neurons in posterior regions of the stream ring in response to relatively simple stimuli and anterior regions of the stream ring to more complex and speci c stimuli. For example, whereas neurons in V1 and V2 re in response to simpler stimulus properties such as colour, orientation, and spatial frequency (Fig. 4.4b), cells in IT cor- tex respond to much more complex stimuli.9 Indeed, cells in IT cor- tex are usually selective for a very speci c stimulus, such as a hand (Fig. 4.4c).10,11 Moreover, this selectivity is usually invariant over changes in stimulus size, orientation, contrast, and colour, that is, neural responses are not altered by changes in these parameters. Not surprisingly, lesions to this area of the brain lead to severe de cits in identifying and naming di erent categories of objects, a condition known as visual agnosia.

Evidence from neuroimaging indicates that distinct areas within the ventral temporal cortex may be specialized for spe- ci c categories of stimuli. e fusiform face area (FFA) responds more strongly to faces than to other non-face objects,12 whereas the parahippocampal place area (PPA) responds more to images of buildings and scenes than to faces and other objects.13 Other category-speci c regions have been identi ed for inanimate objects, body parts, and letter strings,14–16 ere is currently a debate regarding whether these regions should be treated as mod- ules for the representation of speci c categories17 or whether they should be considered as parts of a more general object-recognition system critical for recognizing ne-grained distinctions among well-known objects.18,19

In the context of memory systems, the structures of the VVS have been considered to comprise a ‘perceptual representation system’ which mediates perceptual priming, discrimination, and categori- zation of stimuli.20 is so-called non-declarative memory system is contrasted with a declarative memory system for facts and events, thought to reside in the temporal lobe proper. ese putative mem- ory systems will be discussed in more detail below.

e cortical auditory stream

e organization of the human cortical auditory system is less well understood than the cortical visual system and much information has been obtained from animal models, in particular the macaque

Frontal lobe

Parietal lobe

CHAPTER 4 the temporal lobes 41



Temporal lobe (c)

Sylvian (lateral) fissure

Superior temporal sulcus

42 22
38 21 37



Occipital lobe








–4 10 17 25

Hippocampus Perirhinal cortex

Entorhinal cortex Parahippocampal cortex

Fusiform cortex
Inferior temporal cortex

Middle temporal cortex Superior temporal cortex Temporal polar cortex

Fig. 4.2 Temporal lobe anatomy. (a) Lateral view of the left hemisphere depicting the four lobes of the cerebral cortex and major gyri and sulci. (b) Lateral view of the left hemisphere showing Brodmann’s areas in the temporal lobes. (c) Medial view of the right hemisphere showing Brodmann’s areas in the temporal lobes. (d) Coronal sections depicting di erent temporal lobe regions, superimposed on a Montreal Neurological Institute average brain template.
(a) Reproduced from Gazzaniga, Ivry, Mangun Eds, Cognitive Neuroscience: e biology of the mind, 3rd edition, Copyright (2008), with permission from W. W. Norton & Company.

(b&c) Reproduced from Catani, Marco, iebaut de Schotten, Michel, Atlas of Human Brain Connections: Sectional Neuroanatomy, Copyright (2015), with permission from Oxford University Press. (d) Reproduced from Journal of Neuroscience, 26(19), Lee AC, Buckley MJ, Ga an D, et al. Di erentiating the Roles of the Hippocampus and Perirhinal Cortex in Processes beyond Long-Term Declarative Memory: A Double Dissociation in Dementia, pp. 5198–203, Copyright (2006), with permission from the Society for Neuroscience.

monkey.21 However, certain basic principles of auditory cortical ana- tomical and functional organization have been identi ed. As is the case for visual information, cortical analysis of auditory information is distributed among multiple cortical areas, hierarchically organ- ized into overlapping but separable processing streams (Fig. 4.5).

Primary auditory cortex is located in the medial portion of each Heschl’s gyrus and can be identi ed from histoanatomical features and to some extent by functional properties such as tonotopic cod- ing of pitch information. Higher-order areas relatively specialized for auditory processing are located in the surrounding superior

Superior temporal gyrus Middle temporal gyrus

Inferior temporal gyrus

normal cognitive function



Fig. 4.3 Major functional circuits in the temporal lobes of the rhesus monkey.
(a) Modality-speci c streams devoted to either audition or vision progress
from primary sensory regions towards the temporal pole. (b) Modality-speci c auditory, visual, and somatic information inputs to multimodal regions of the superior temporal sulcus. (c) Auditory and visual information inputs to the medial temporal lobe.

Reproduced from Kolb B and Whishaw IQ, Fundamentals of Human Neuropsychology, 7th edn, Copyright (2015), with permission from Macmillan Higher Education.

temporal gyrus (STG), extending anteriorly to the temporal pole and posteriorly into planum temporale, posterior STG, and the temporoparietal junction (TPJ). Candidate homologues of these areas in the macaque and other species can be di erentiated on anatomical and electrophysiological grounds; however, informa- tion about human auditory cortical subregions remains limited.

Analogous with the ‘what/where’ cortical processing streams in the visual system, auditory cortical organization appears to be broadly dichotomous, comprising a ventral stream directed along anterior STG, and a dorsal stream directed into the TPJ and pro- jecting to parietal and frontal cortical areas. e ventral stream is concerned chie y with representing information about auditory object identity whereas the dorsal stream is concerned with repre- senting sound location and movement.21,22

Successive stages within these processing hierarchies are associ- ated with increasing integration and abstraction of auditory infor- mation and the streams communicate widely with higher-order multimodal cortical areas in STS, MTG, and parietal lobe. Again analogous with the visual cortical system, fundamental tasks of cortical auditory processing include the representation of invari- ant object features and the association of these representations with meaning based on prior experience of the sensory world.

In the case of the most widely studied auditory signal, speech, it has been shown that acoustic properties of speech sounds as dis- crete auditory objects are encoded in more posterior areas in pos- terior and mid STG, whereas speech intelligibility—the meaning associated with the sounds—is extracted in more anterior areas in STG in the dominant cerebral hemisphere,21 ultimately link- ing spoken language with other modalities of semantic knowledge. Similar organizational principles are likely to govern the processing of non-verbal environmental sounds.

In contrast, preparation to produce speech and other vocal sounds via the dorsal auditory pathway is initiated by mechanisms in the vicin- ity of planum temporale and posterior STG: a putative ‘sensori-motor

42 SECTION 1 (a)

interface’ that lies within the compass of ‘Wernicke’s area’ in classical aphasiology.21,22 Speci c agnosias for pre- or non-linguistic auditory phenomena are uncommon but well-documented: examples include so-called pure word deafness and agnosias for di erent aspects of music. Speci c syndromes of this kind suggest underlying neural mechanisms that are functionally dissociable.23

Analogies between the visual and auditory cortical systems should not be overemphasized. e visual and auditory modali- ties present the brain with speci c computational problems (in the auditory modality, for example, the problem of resolving multiple ‘transparent’ sound sources overlaid in the auditory environment and the requirement to integrate information dynamically over time); these problems are likely to be solved by modality-speci c neural mechanisms. e peripheral visual and auditory processing pathways are organized along di erent lines: processing of infor- mation over subcortical relays is more extensive for auditory than for visual stimuli, and in addition, whereas visual information is relayed to the contralateral cerebral hemisphere, auditory informa- tion is distributed to both hemispheres.

e status of auditory spatial processing in the dorsal processing stream is less straightforward than the status of visuospatial process- ing in the dorsal visual stream:21,22 there is extensive interaction between the dorsal and ventral auditory streams when processing sound identity and location, and it has been suggested that the dor- sal auditory stream is not primarily a ‘where’ pathway but, rather, a ‘how’ pathway (processing dynamic changes in the auditory envi- ronment) or a ‘do’ pathway (programming motor responses based on relevant sound information).

Furthermore, the human cortical auditory system shows a unique specialization in the processing of speech sounds, and this may be partly based on distinctive neural mechanisms that are di erentiated between the cerebral hemispheres. In particular, it has been suggested that the le hemisphere may preferentially process auditory signals that (like speech) contain frequent, rapid spectro-temporal transitions whereas the right hemisphere may preferentially process slower spectro-temporal variations or infor- mation unfolding over longer timescales (e.g. in musical melodies). However, any such dichotomy is likely to be an oversimpli cation.24

Circuit 2. Superior temporal sulcus, middle temporal

gyrus, and a erent connections

A key principle of temporal lobe function is the integration of infor- mation from di erent sensory modalities and across processing stages to create uni ed representations of the world. Cortical areas in STS and MTG have extensive reciprocal anatomical communica- tions with modality-speci c (e.g. purely visual or purely auditory) superior, inferior, and posterior temporal cortices. Functionally, these regions have been implicated in the processing of visual, auditory, and somatic information and in the cross-modal integra- tion of sensory information when resolving inter-modal incon- gruities or building coherent multimodal perceptual and semantic representations.25–27

Cognitive processing stages such as ‘perceptual’ and ‘semantic’ have been distinguished neuroanatomically as well as neuropsy- chologically.27 However, the anatomical organization of temporal lobe circuitry suggests that modality-speci c and multimodal cor- tical areas cooperate with mutual information exchange during the perceptual and semantic analysis of sensory objects. e existence of such cooperation has been supported by functional imaging


Auditory Visual

as ce ip

CHAPTER 4 the temporal lobes 43












V3 V2

V1 ec







1.0 0 0 0.01

0.01 0.49 0.22 0.15

0 0.05 1.36 0.82

301/s 2s


Fig. 4.4 e ventral visual stream. (a) e ventral visual stream is a processing pathway critical for the perceptual analysis of objects. It originates in primary visual cortex (V1) and progresses along the ventral surface of the temporal lobe towards anterior temporal regions. Information processing in this stream is organized hierarchically, such that early regions process version simple information and more anterior regions process more complex information. (b) For example, here we illustrate a V1 neuron that is tuned to a bar of light oriented in a particular direction and res maximally (vertical lines correspond to action potentials) when a bar of light in its preferred orientation hits the cell’s receptive eld but not at all when the bar is dissimilar to its preferred orientation. (c) By contrast, anterior VVS regions are tuned to more complex features. Here we demonstrated a TE neuron that res maximally ( ring rates illustrated on the bar graph) to the shape circled in red. e preferences of these cells are remarkably selective and show weaker response rates as the image deviates from the preferred shape. Cells in TE are thought to respond to ‘moderately complex’ features.

(a) Adapted from Philos Trans R Soc Lond B Biol Sci., 298(1089), Mishkin M, A Memory System in the Monkey, pp. 83–95, Copyright (1982), with permission from e Royal Society, Figure courtesy of Mort Mishkin. (b) Reproduced from Dowling, John E, Neurons and Networks. An Introduction to Neuroscience, Copyright (1992), with permission from Harvard University Press. (c) Reproduced from Annu Rev Neurosci., 19, Tanaka K., Inferotemporal Cortex and Object Vision, pp. 109–39, Copyright (1996), with permission from Annual Reviews.

evidence in both healthy subjects and in de ned clinical popula- tions such as patients with semantic dementia.28,29

Indeed, one view is that the temporal poles—structures heavily damaged in semantic dementia—comprise an amodal semantic ‘hub’ that mediates communication across various sensory, motor, linguistic, and a ective domains.30 Damage to this temporal pole hub results in a dissolution of semantic knowledge across all conceptual domains and all modalities of testing.31 is hub is thought to become especially critical when the semantic system must extract conceptual similarity structure that is not directly re ected in any single modality (e.g. sensory, motor, linguistic, a ective).

For example, items that are very similar in kind may vary enor- mously in terms of their surface details: a penguin and a hum- mingbird are very di erent in terms of how they look and how they move, but they are classed as similar kinds of things.32 In contrast,

light bulbs and pears share many surface similarities but are classed as very di erent kinds of objects. us, critical to any semantic sys- tem is the capacity to represent conceptual similarity structure that is not re ected in any single surface modality (e.g. shape or move- ment), and this cross-modal associative conceptual knowledge may be subserved by the temporal pole.

ere are many instances where integration of cross-modal information is required to make sense of the environment. One key example is the representation of attributes of particular people, which generally entails conjoint processing of face and voice iden- tity.33 Functional imaging studies have shown that such process- ing engages multimodal cortical areas in STS and MTG as well as modality-speci c visual and auditory areas. In addition to involve- ment of higher-order multimodal areas, there are likely to be direct connections between modality-speci c auditory and visual areas,34 underlining the potential for cross-modal interactions at multiple




normal cognitive function

object representation

semantic processing



Fig. 4.5 Cortical auditory stream. A simpli ed schematic showing key processing stages in the putative ventral cortical stream for auditory object processing in the human brain. e auditory scene is initially parsed into constituent sound sources by non-primary cortex in the planum temporale and posterior superior temporal lobe, and adjacent cortical areas in and surrounding the superior temporal sulcus analyse the features of these sources and build auditory object representations. ese auditory object representations become associated with meaning as a result of higher order semantic processing in the anterior temporal lobe and beyond.

levels of the processing hierarchy. Such interactions might be par- ticularly relevant for resolving identity under ambiguous listening or viewing conditions. Analogous cross-modal interactions are likely to facilitate speech recognition from observation of lip move- ments and other non-auditory cues.35

Circuit 3. e medial temporal lobe and

its a erent connections

Case study 1 (Box 4.1) introduces the famous patient, HM, who su ered profound amnesia following damage to the temporal lobes. One of the most remarkable features of HM’s disorder (and that of other cases like him) was its seeming selectivity to the learning of new facts and events.36 Patients with MTL resections showed severe anterograde amnesia, together with some retrograde amne- sia for at least the immediate pre-operative period, but they mani- fested no other obvious changes in perceptual abilities, intellect, or personality.

Furthermore, all patients were able to remember relatively small amounts of information perfectly for seconds or minutes, so long as they were not interrupted. e instant their attention was diverted to a new topic, however, the material was lost. For example, one report37 describes an occasion on which HM was asked to remem- ber the number ‘584’ and was then allowed to sit quietly with no interruption for several minutes. At the end of this interval he was able to recall the number correctly without any hesitation, stat- ing, ‘It’s easy. You just remember 8. You see, 5, 8, 4, add to 17. You remember 8; subtract it from 17 and it leaves 9. Divide 9 in half and you get 5 and 4, and there you are: 584. Easy.’

Despite this elaborate mnemonic device, as soon as HM’s atten- tion was diverted to another topic, he was unable to remember, approximately one minute later, either the number ‘584’ or the fact that he had been given a number to remember in the rst place. is suggested that the structures in the MTL were critical to con- solidate new long-term memories, but were not important for the rehearsal and maintenance of information over short time periods (a cognitive ability termed working memory).

Working memory was not the only form of memory that appeared to be spared in amnesic subjects. Numerous studies dem- onstrated that amnesia spared knowledge that was based on rules or procedures, but dramatically a ected declarative memory— knowledge that was available as conscious recollections about facts (semantic memory) and events (episodic memory) (see, for example, references 3 and 38). For example, MTL amnesics could acquire selected motor skills (e.g. mirror drawing) over a period of days, despite having no recollection of having carried out the task. Subsequent studies expanded the collection of preserved abilities in amnesia to include memory for skills and habits, simple forms of conditioning, which eventually fell under the umbrella term of non-declarative memory and refer to a collection of abilities that are unconscious and expressed through performance rather than conscious recollection.

ese ndings led to the idea of an MTL declarative memory system containing several anatomically distinct structures, namely those damaged in HM: the hippocampus, together with the adja- cent, anatomically related entorhinal, perirhinal, and parahip- pocampal cortices (see references 36 and 39). According to this

parsing of auditory scene

feature analysis

Human brain

CHAPTER 4 the temporal lobes 45


Temporal lobe

Visual cortex

Declarative memory Conscious

Long-Term Memory


Non-declarative memory not conscious


Episodic Memory personal events

Semantic Memory facts knowledge

Perceptual Representation System priming

Procedural Memory motor skills conditioning

Fig. 4.6 Traditional taxonomy of memory systems. Declarative (implicit) memory refers to conscious memory for facts (semantic memory) and events (episodic memory), whereas non-declarative (implicit) memory refers to a collection of abilities that operate outside of conscious awareness.39 e prevailing view in cognitive neuroscience is that the brain can be best understood as consisting of modules specialized for distinct cognitive functions. In this example, two di erent expression
of long-term memory—conscious declarative memory and unconscious non-declarative memory—are presumed to have di erent neuroanatomical loci. Declarative memory is traditionally believed to be dependent on the medial temporal lobes, whereas priming (a form of non-declarative memory) is thought to be dependent on a perceptual representation system in more posterior neocortex.

view, the regions in the MTL work in concert, as a highly integrated system, to bind together the distributed elements of memory that are processed and represented by distinct cortical sites. is sys- tem is proposed to work in the service of declarative memory only, with no role in other cognitive functions, such as perception or working memory (Fig. 4.6). According to this account, injury to any component of the MTL memory system will result in a de cit on any type of declarative memory, and only declarative memory. According to this view, the process of consolidating the distributed elements of memory into a coherent and stable ensemble can take years, but eventually, memories are thought to become independ- ent of the MTL memory system (reference 40, although see too reference 41).

us with respect to the pathway currently under discussion— the MTL and its a erents—the view had emerged of a discontinu- ous pathway containing two qualitatively di erent ‘modules’: the declarative memory system in the MTL, and the perceptual rep- resentation system in the VVS, which mediates the putatively non-declarative functions of visual priming, categorization, and perceptual discrimination. is modular view has recently come into question, as will be discussed below.

More recent ideas regarding the functional organization of the VVS–MTL stream

Despite the popularity of the putative MTL memory system, there were several ndings that contradicted this view. ese ndings support two di erent but related ideas:

1. e heterogeneity of function within the putative MTL system, and

2. e VVS–MTL pathway as a continuous, rather than discontinu- ous, system.

Functional heterogeneity within the MTL

Beginning in the 1960s, researchers sought to understand the func- tions of the separate structures within the MTL. Many of these

studies focused on recognition memory, indicated by the ability to judge whether an item has been seen previously. Despite the fact that recognition memory is considered a canonical example of declarative memory, damage to the hippocampus appears to be neither necessary nor su cient to produce recognition mem- ory de cits.42–44 However, lesions that damaged one MTL cortical structure, the perirhinal cortex, consistently impaired recognition memory.45–49 In addition, with the advent of more detailed ana- tomical techniques, investigations into the mnemonic contribu- tion of the hippocampus alone—unconfounded by concomitant perirhinal damage—became possible. Using a precise excitotoxic lesion technique, it was shown that lesions to the hippocampus (without damage to underlying cortical regions) produced no rec- ognition memory impairment.50

A subsequent meta-analysis of three studies in monkeys with hippocampal lesions demonstrated that whereas greater rhinal cortex damage was associated with worse performance on a recog- nition memory task, greater hippocampal damage was associated with better performance on the same task.51 Further work indicated that the hippocampus and perirhinal cortex could be doubly dis- sociated.52 ese di erent structures, therefore, must contribute to memory in very di erent ways. Some of the most prominent ideas regarding division of labour between the hippocampus and other MTL structures are discussed below.

In a seminal review, Aggleton and Brown53 addressed the neu- ral substrates of two distinct memory processes, recollection (the ‘remembering’ of an event, associated with the retrieval of contex- tual details) and familiarity (the feeling of ‘knowing’ that an item has been experienced, in the absence of other associated details).54,55 ey proposed that the hippocampus, together with the fornix, mamillary bodies, and anterior thalamic nuclei, form a system that supports recollection, whereas familiarity re ects an independent process that depends on a distinct system involving the perirhinal cortex and the medial dorsal nucleus of the thalamus.

46 SECTION 1 normal cognitive function

A closely related model, the Convergence, Recollection, and Familiarity eory (CRAFT),56 also contrasts hippocampal and cortical function. Under this view, recollection is thought to be sup- ported by the hippocampus through pattern separation, a mecha- nism by which similar memories are di erentiated into distinct, non-overlapping representations,57 is computation is considered to be qualitatively di erent from the object/item familiarity and contextual familiarity computations supported by cortical MTL structures such as the perirhinal and parahippocampal cortices.

In a similar vein, the complementary learning system (CLS) is a network model that also makes important distinctions between hip- pocampal and MTL cortical contributions to memory.58 Under this framework, the MTL neocortex has a slow learning rate and uses overlapping distributed representations to extract the shared struc- ture of events (e.g. generalities based on accumulated experience, such as the best strategy for parking a car). us, because it does not su ciently di erentiate the representations of di erent information, this cortex is unable to support recall of information that has only been encountered on one or two occasions. In contrast, the hip- pocampus learns rapidly, using pattern separated representations to encode the details of speci c events while minimising interference (e.g. the memory for where the car is parked today is kept separate from the representation of where the car was parked yesterday).

Other prominent views of MTL function argue that the engage- ment of di erent MTL structures is best characterized by the type of information being processed (e.g. items, contexts, or the associa- tions between items and their contexts), rather than the processes themselves. One theory posits that the hippocampus has a criti- cal role in binding together arbitrarily-related associations (termed relational memory), whereas MTL cortical structures maintain rep- resentations for individual items.59,60

is theory has subsequently been developed into a three- component model, termed the ‘binding of item and context’ (BIC) model.61,62 Rather than proposing a simple mapping between dif- ferent MTL structures and familiarity and recollection, this view posits that MTL subregions di er in terms of the information they process and represent. More speci cally, the perirhinal cortex is thought to represent information about speci c items (e.g. who and what), the parahippocampal cortex is thought to represent infor- mation about the context of these items (e.g. where and when), and the hippocampus represents the associations between these items and contexts. us, each region has a functionally distinct role, but collectively, MTL regions support memory by binding item and context information.

In summary, the wealth of recent evidence suggests that, in con- trast to the idea of a unitary memory system, di erent MTL struc- tures make functionally dissociable contributions to memory and as such, di ering patterns of MTL damage will lead to distinct pro- les of memory impairment.

e VVS–MTL pathway as a continuous, rather than discontinuous, system

A second assumption of the historical view of the VVS–MTL pathway has also recently been questioned, namely the assump- tion that this system is best thought of as discontinuous, con- taining two qualitatively di erent modules, the MTL memory system and the VVS perceptual representation system. However, beginning in the mid-1990s, experimental data began to suggest

that structures within the MTL contribute not just to declara- tive memory but are also important for perceptual and other functions such as perceptual discrimination (e.g. being able to identify whether there are di erences between visually similar objects).48,63

To account for these data, it was proposed that structures within the MTL such as perirhinal cortex may be best understood as an extension of the representational hierarchy within the VVS (Fig. 4.7).64,65 In other words, rather than characterizing the func- tion of MTL structures in terms of psychological labels like ‘mem- ory’ and ‘perception’, it may be better to consider them in terms of the representations that they contain and the computations that they perform.66 Under this view, MTL structures are thought to contain the rich neural representations of objects and scenes that are neces- sary for both memory and perception. us, damage to these repre- sentations causes de cits on both mnemonic and perceptual tasks.

is notion was encapsulated in a computational/theoretical framework64,67 referred to as the ‘representational-hierarchical’ view.68 In accord with the prevailing view in the VVS literature,9,69 posterior regions in the VVS are assumed to represent simple fea- tures, whereas more anterior regions in the VVS and MTL are

Fig. 4.7 e representational-hierarchical view. e representational- hierarchical view suggests that a given brain region could be useful for multiple cognitive functions, rather than being specialized exclusively for functions such as memory or perception.64,65,84 Representations of visual stimulus features are organized hierarchically throughout the ventral visual stream, such that simple features are represented in more posterior regions and conjunctions of these features are represented in more anterior regions.9,69 e representational- hierarchical view proposes that highly complex conjunctions of these features— at approximately the level of an everyday object—are represented in the perirhinal cortex. ese object-level representations are important for both memory and perception, and thus, damage to the perirhinal cortex will impair both these cognitive functions.
Adapted from Neuron, 75(1), Barense MD, Groen II, Lee AC, Yeung LK, Brady SM, Gregori M,
et al. Intact memory for irrelevant information impairs perception in amnesia, pp. 157–67, Copyright (2012), with permission from Elsevier, reproduced under the Creative Commons CC BY 3.0 License; Trends in Cognitive Sciences, 3(4), Murray EA and Bussey TJ, Perceptual-mnemonic functions of the perirhinal cortex, pp. 142–51, Copyright (1999), with permission from Elsevier.




conjunctions Objects




Simple feature conjunctions (AB, CD)

Feature (A,B,C,D)

Objects (ABCD)

anterior posterior

assumed to represent more complex conjunctions of these features. According to the representational-hierarchical view (Fig. 4.7), because damage to the perirhinal cortex destroys or compromises highly complex visual representations, one must rely on the repre- sentations of simple features housed in more posterior regions of VVS to solve cognitive tasks. us, impairments in perception (as well as memory) are caused by perirhinal cortex damage because such damage leads to impoverished representations of complex stimuli, and the remaining representations of simple features are inadequate for making certain types of discrimination between visual objects.

To test the model, a ‘lesion’ was made by removing the layer of the computational network corresponding to perirhinal cor- tex, and the effects of this lesion were compared with previously reported effects of lesions in perirhinal cortex in monkeys.64 The model was able to simulate the effects of lesions of per- irhinal cortex on visual discrimination behaviour in a range of different experimental contexts (see, for example, references 70 and 71). Central to the model is the notion of ‘feature ambigu- ity’. An ambiguous feature—for example, one that is rewarded as part of one stimulus but not as part of another stimulus—will not contribute towards the solution of a task such as a visual discrimination. In order to solve a problem that contains ambig- uous features, more complex conjunctions of features (such as those represented in perirhinal cortex), which are much less likely to be ambiguous, are required.

Subsequent work therefore manipulated feature ambiguity explicitly to test this prediction of the model. A number of stud- ies provided support for the prediction that perirhinal cortex is required for any visual discrimination task that necessitates reso- lution of feature ambiguity at the object level in monkeys63,70–72 and humans,73–78 although there have been some con icting reports.79–82 More recently, this work has been extended to show that impoverished visual representations following MTL damage cause de cits not only in complex discrimination tasks.


What all these tasks had in common was the requirement to form a representation of the relationships between complex stimuli— either in terms of comparisons across complex objects,93,94 or in terms of the relationships of the objects that comprise a scene.75,76 ese ndings challenge the longstanding assumption that the hippocampus is uniquely involved in long-term memory, and suggest instead that this structure—along with the rest of the MTL—should best be understood in terms of the information it represents, rather than in terms of cognitive modules or circum- scribed processes.


1. Milner B, Corkin S, and Teuber HL. Further analysis of the hippocam- pal amnesic syndrome: 14-year follow-up of HM. Neuropsychologia. 1968;6:215–34.

2. Milner B. Amnesia following operation on the tempo-
ral lobes. In: CWM Whitty and OL Zangwill (eds). Amnesia. London: Butterworths, 1966, pp. 109–33.

3. Corkin S. What’s new with the amnesic patient H.M.? Nat Rev Neurosci. 2002 Feb;3(2):153–60.

4. Wernicke C. Der aphasische Symptomenkomplex: Eine psycholo- gische Studie auf anatomischer Basis. In: Breslau, Cohn, Weigert (eds). Wernicke’s Works on Aphasia: A Sourcebook and Review. e Hague: Mouton, 1874.

5. Kiernan JA. Anatomy of the temporal lobe. Epilepsy Res Treat. 2012. <;.

6. Kennedy DN, Lange N, Makris N, et al. Gyri of the human neocor-
tex: An MRI-based analysis of volume and variance. Cereb Cortex. 1998 Jun;8(4):372–84.

7. Goodale MA. Transforming vision into action. Vision Res. 2011 Jul 1;51(13):1567–87.

8. Ungerleider L and Mishkin M. Two cortical visual streams. In: D Ingle, M Goodale, and R Mans eld (eds). Analysis of Behavior. Cambridge, MA: MIT Press, 1983, pp. 549–86.

9. Desimone R and Ungerleider LG. Neural mechanisms of visual pro- cessing in monkeys. In: F Boller and J Grafman (eds). Handbook of Neuropsychology. New York, NY: Elsevier Science, 1989, pp. 267–99.

10. Gross CG. Single neuron studies of inferior temporal cortex. Neuropsychologia. 2008 Feb 12;46(3):841–52.

11. Tanaka K. Inferotemporal cortex and object vision. Annu Rev Neurosci. 1996;19:109–39.

12. Kanwisher N, McDermott J, and Chun MM. e fusiform face
area: A module in human extrastriate cortex specialized for face percep- tion. J Neurosci. 1997 Jun 1;17(11):4302–11.

13. Epstein R and Kanwisher N. A cortical representation of the local visual environment. Nature. 1998 Apr 9;392(6676):598–601.

14. Kourtzi Z and Kanwisher N. Cortical regions involved in perceiving object shape. J Neurosci. 2000 May 1;20(9):3310–18.

15. Downing PE, Jiang Y, Shuman M, et al. A cortical area selec- tive for visual processing of the human body. Science. 2001 Sep 28;293(5539):2470–3.

16. McCandliss BD, Cohen L, and Dehaene S. e visual word form
area: expertise for reading in the fusiform gyrus. Trends Cogn Sci. 2003 Jul;7(7):293–9.

17. Kanwisher N. Functional speci city in the human brain: a window into the functional architecture of the mind. Proc Natl Acad Sci USA. 2010 Jun 22;107(25):11163–70.

18. McGugin RW, Gatenby JC, Gore JC, et al. High-resolution imaging of expertise reveals reliable object selectivity in the fusiform face area related to perceptual performance. Proc Natl Acad Sci USA. 2012 Oct 16;109(42):17063–8.

19. Gauthier I, Tarr M, and Bub D (eds). Perceptual Expertise: Bridging Brain and Behavior. Oxford: Oxford University Press, 1990.

For example, McTighe and colleagues
cal de cit in object recognition memory seen in animals with perirhinal cortex damage may be accounted for by interference due to feature ambiguity, and removing such interference can completely rescue memory. Similar ndings have recently been reported in humans: individuals with memory disorders (from either focal damage to the MTL that included perirhinal cor- tex, and individuals with mild cognitive impairment) were also vulnerable to object-based interference, and when this interfer- ence was controlled, their performance was recovered to normal levels.84–86

A similar argument would apply to other regions in the MTL such as the hippocampus, albeit in the context of more complex stimulus representations such as spatial scenes.66,68,87 Initial evi- dence supports this view: individuals with hippocampal dam- age were impaired on tasks requiring the rich representation of information, irrespective of timescales. For example, hippocam- pal amnesics were impaired on working memory tasks requiring maintenance of scenes,88,89 topographical maps,90 and objects in spatial arrays.91,92 Even more strikingly, damage to the hip- pocampus also impaired performance on tasks that simulta-

neously presented all information necessary to make a correct response.75,76,93,94

showed that the classi-

CHAPTER 4 the temporal lobes 47

48 SECTION 1 normal cognitive function

20. Tulving E and Schacter DL. Priming and human memory systems. Science. 1990 Jan 19;247(4940):301–6.

21. Rauschecker JP and Scott SK. Maps and streams in the auditory cortex: nonhuman primates illuminate human speech processing. Nat Neurosci. 2009 Jun;12(6):718–24.

22. Warren JE, Wise RJ, and Warren JD. Sounds do-able: auditory-motor transformations and the posterior temporal plane. Trends Neurosci. 2005 Dec;28(12):636–43.

23. Goll JC, Crutch SJ, and Warren JD. Central auditory disorders: toward a neuropsychology of auditory objects. Curr Opin Neurol. 2010 Dec;23(6):617–27.

24. McGettigan C and Scott SK. Cortical asymmetries in speech percep- tion: what’s wrong, what’s right and what’s le ? Trends Cogn Sci. 2012 May;16(5):269–76.

25. Noppeney U, Josephs O, Hocking J, et al. e e ect of prior visual information on recognition of speech and sounds. Cereb Cortex. 2008 Mar;18(3):598–609.

26. Naumer MJ, Doehrmann O, Muller NG, et al. Cortical plastic- ity of audio-visual object representations. Cereb Cortex. 2009 Jul;19(7):1641–53.

27. Binder JR, Desai RH, Graves WW, et al. Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb Cortex. 2009 Dec;19(12):2767–96.

28. Martin A and Chao LL. Semantic memory and the brain: Structure and processes. Curr Opin Neurobiol. 2001 Apr;11(2):194–201.

29. Goll JC, Ridgway GR, Crutch SJ, et al. Nonverbal sound processing in semantic dementia: a functional MRI study. Neuroimage. 2012 May 15;61(1):170–80.

30. Patterson K, Nestor PJ, and Rogers TT. Where do you know what you know? e representation of semantic knowledge in the human brain. Nat Rev Neurosci. 2007 Dec;8(12):976–87.

31. Hodges JR, Patterson K, Ward R, et al. e di erentiation of semantic dementia and frontal lobe dementia (temporal and frontal variants of frontotemporal dementia) from early Alzheimer’s disease: a compara- tive neuropsychological study. Neuropsychology. 1999 Jan;13(1):31–40.

32. Rogers TT and Cox CR. e neural bases of conceptual knowl-
edge: Revisiting a Golden Age hypothesis in the era of cognitive neuro- science. In: A Duarte, MD Barense, and DR Addis (eds). e Cognitive Neuroscience of Memory. Oxford: Wiley, 2015.

33. Campanella S and Belin P. Integrating face and voice in person percep- tion. Trends Cogn Sci. 2007 Dec;11(12):535–43.

34. Blank H, Anwander A, and von Kriegstein K. Direct structural connec- tions between voice- and face-recognition areas. J Neurosci. 2011 Sep 7;31(36):12906–15.

35. McGettigan C, Faulkner A, Altarelli I, et al. Speech comprehension aided by multiple modalities: Behavioural and neural interactions. Neuropsychologia. 2012 Apr;50(5):762–76.

36. Squire LR and Wixted JT. e cognitive neuroscience of human memory since H.M. Annu Rev Neurosci. 2011 Jul 21;34:259–88.

37. Milner B. e memory defect in bilateral hippocampal lesions. Psychiatr Res Rep Am Psychiatr Assoc. 1959 Dec;11:43–58.

38. Cohen NJ and Squire LR. Preserved learning and retention of pattern- analyzing skill in amnesia: dissociation of knowing how and knowing that. Science. 1980 Oct 10;210(4466):207–10.

39. Squire LR and Zola-Morgan S. e medial temporal lobe memory system. Science. 1991 Sep 20;253(5026):1380–6.

40. Squire LR and Bayley PJ. e neuroscience of remote memory. Curr Opin Neurobiol. 2007 Apr;17(2):185–96.

41. Moscovitch M, Rosenbaum RS, Gilboa A, et al. Functional neuro- anatomy of remote episodic, semantic and spatial memory: a uni ed account based on multiple trace theory. J Anat. 2005 Jul;207(1):35–66.

42. Mishkin M. Memory in monkeys severely impaired by combined but not by separate removal of amygdala and hippocampus. Nature. 1978;273(5660):297–8.

43. Murray EA and Mishkin M. Severe tactual as well as visual memory de cits follow combined removal of the amygdala and hippocampus in monkeys. J Neurosci. 1984 Oct;4(10):2565–80.

44. Mayes AR, Holdstock JS, Isaac CL, et al. Relative sparing of item rec- ognition memory in a patient with adult-onset damage limited to the hippocampus. Hippocampus. 2002;12(3):325–40.

45. Meunier M, Bachevalier J, Mishkin M, et al. E ects on visual recogni- tion of combined and separate ablations of the entorhinal and perirhinal cortex in rhesus monkeys. J Neurosci. 1993 December;13(12):5418–32.

46. Suzuki WA, Zola-Morgan S, Squire LR, et al. Lesions of the perirhinal and parahippocampal cortices in the monkey produce long-lasting memory impairment in the visual and tactual modalities. J Neurosci. 1993 June;13(6):2430–51.

47. Zola-Morgan S, Squire LR, Clower RP, et al. Damage to the perirhinal cortex exacerbates memory impairment following lesions to the hip- pocampal formation. J Neurosci. 1993 January;13(1):251–65.

48. Eacott MJ, Ga an D, and Murray EA. Preserved recognition memory for small sets, and impaired stimulus identi cation for large sets, fol- lowing rhinal cortex ablations in monkeys. Eur J Neurosci. 1994 Sep 1;6(9):1466–78.

49. Bowles B, Crupi C, Mirsattari SM, et al. Impaired familiarity with preserved recollection a er anterior temporal-lobe resection
that spares the hippocampus. Proc Natl Acad Sci USA. 2007 Oct 9;104(41):16382–7.

50. Murray EA and Mishkin M. Object recognition and location memory in monkeys with excitotoxic lesions of the amygdala and hippocampus. J Neurosci. 1998;18(16):6568–82.

51. Baxter MG and Murray EA. Opposite relationship of hippocampal and rhinal cortex damage to delayed nonmatching-to-sample de cits in monkeys. Hippocampus. 2001;11(1):61–71.

52. Winters BD, Forwood SE, Cowell RA, et al. Double dissociation between the e ects of peri-postrhinal cortex and hippocampal lesions on tests of object recognition and spatial memory: heterogeneity of function within the temporal lobe. J Neurosci. 2004 Jun 30;24(26):5901–8.

53. Aggleton JP and Brown MW. Episodic memory, amnesia, and the hippocampal-anterior thalamic axis. Behav Brain Sci. 1999 Jun;22(3):425–44; discussion 44–89.

54. Mandler G. Recognizing: e judgement of previous occurrence. Psychol Rev. 1980;87:252–71.

55. Jacoby LL. A process dissociation framework: separating automatic from intentional uses of memory. J Memory Lang. 1991;30:513–41.

56. Montaldi D and Mayes AR. e role of recollection and familiar- ity in the functional di erentiation of the medial temporal lobes. Hippocampus. 2010 Nov;20(11):1291–314.

57. Norman KA and O’Reilly RC. Modeling hippocampal and neocortical contributions to recognition memory: A complementary-learning- systems approach. Psychol Rev. 2003 Oct;110(4):611–46.

58. Norman KA. How hippocampus and cortex contribute to recogni- tion memory: Revisiting the complementary learning systems model. Hippocampus. 2010 Nov;20(11):1217–27.

59. Eichenbaum H and Cohen NJ. From Conditioning to Conscious Recollection: Memory Systems of the Brain. New York, NY: Oxford University Press, 2001.

60. Eichenbaum H, Otto T, and Cohen NJ. Two functional components of the hippocampal memory system. Behav Brain Sci. 1994;17:449–518. 61. Diana RA, Yonelinas AP, and Ranganath C. Imaging recollection and

familiarity in the medial temporal lobe: a three-component model.

Trends Cogn Sci. 2007 Sep;11(9):379–86.
62. Eichenbaum H, Yonelinas AP, and Ranganath C. e medial temporal

lobe and recognition memory. Annu Rev Neurosci. 2007;30:123–52. 63. Buckley MJ and Ga an D. Perirhinal cortex ablation impairs visual

object identi cation. J Neurosci. 1998 Mar 15;18(6):2268–75.
64. Bussey TJ and Saksida LM. e organization of visual object representa-

tions: A connectionist model of e ects of lesions in perirhinal cortex.

Eur J Neurosci. 2002 Jan;15(2):355–64.
65. Murray EA and Bussey TJ. Perceptual-mnemonic functions of the

perirhinal cortex. Trends Cogn Sci. 1999 April;3(4):142–51.
66. Bussey TJ and Saksida LM. Object memory and perception in the

medial temporal lobe: an alternative approach. Curr Opin Neurobiol. 2005 Dec;15(6):730–7. Review.

67. Cowell RA, Bussey TJ, and Saksida LM. Why does brain damage impair memory? A connectionist model of object recognition memory in perirhinal cortex. J Neurosci. 2006 Nov 22;26(47):12186–97.

68. Saksida LM and Bussey TJ. e representational-hierarchical view of amnesia: Translation from animal to human. Neuropsychologia. 2010 Jul;48(8):2370–84.

69. Riesenhuber M and Poggio T. Hierarchical models of object recognition in cortex. Nat Neurosci. 1999 Nov;2(11):1019–25.

70. Bussey TJ, Saksida LM, and Murray EA. Perirhinal cortex resolves fea- ture ambiguity in complex visual discriminations. Eur J Neurosci. 2002 Jan;15(2):365–74.

71. Bussey TJ, Saksida LM, and Murray EA. Impairments in visual discrimination a er perirhinal cortex lesions: Testing ‘declarative’ vs. ‘perceptual-mnemonic’ views of perirhinal cortex function. Eur J Neurosci. 2003 Feb;17(3):649–60.

72. Buckley MJ, Booth MC, Rolls ET, et al. Selective perceptual impair- ments a er perirhinal cortex ablation. J Neurosci. 2001 Dec 15;21(24):9824–36.

73. Barense MD, Bussey TJ, Lee AC, et al. Functional specializa- tion in the human medial temporal lobe. J Neurosci. 2005 Nov 2;25(44):10239–46.

74. Barense MD, Ga an D, and Graham KS. e human medial tem- poral lobe processes online representations of complex objects. Neuropsychologia. 2007 Jul 2;45(13):2963–74.

75. Lee AC, Buckley MJ, Pegman SJ, et al. Specialization in the medial temporal lobe for processing of objects and scenes. Hippocampus. 2005 July;15(6):782–97.

76. Lee AC, Bussey TJ, Murray EA, et al. Perceptual de cits in amne- sia: challenging the medial temporal lobe ‘mnemonic’ view. Neuropsychologia. 2005;43(1):1–11.

77. Barense MD, Ngo JK, Hung LH, et al. Interactions of memory and per- ception in amnesia: the gure-ground perspective. Cereb Cortex. 2012 Nov;22(11):2680–91.

78. Barense MD, Rogers TT, Bussey TJ, Saksida LM, and Graham KS. In uence of conceptual knowledge on visual object discrimina-
tion: insights from semantic dementia and MTL amnesia. Cereb Cortex. 2010 Nov;20(11):2568–82.

79. Shrager Y, Gold JJ, Hopkins RO, et al. Intact visual perception in memory-impaired patients with medial temporal lobe lesions.
J Neurosci. 2006 Feb 22;26(8):2235–40.

80. Kim S, Jeneson A, van der Horst AS, et al. Memory, visual discrimina- tion performance, and the human hippocampus. J Neurosci. 2011 Feb 16;31(7):2624–9.

81. Knutson AR, Hopkins RO, and Squire LR. Visual discrimination per- formance, memory, and medial temporal lobe function. Proc Natl Acad Sci USA. 2012 Aug 7;109(32):13106–11.

82. Levy DA, Shrager Y, and Squire LR. Intact visual discrimination of complex and feature-ambiguous stimuli in the absence of perirhinal cortex. Learn Mem. 2005 Jan-Feb;12(1):61–6.

83. McTighe SM, Cowell RA, Winters BD, et al. Paradoxical false memory for objects a er brain damage. Science. 2010 Dec 3;330(6009):1408–10.

84. Barense MD, Groen, II, Lee AC, et al. Intact memory for irrel- evant information impairs perception in amnesia. Neuron. 2012 Jul 12;75(1):157–67.

85. Newsome RN, Duarte A, and Barense MD. Reducing percep-
tual interference improves visual discrimination in mild cognitive impairment: Implications for a model of perirhinal cortex function. Hippocampus. 2012 Oct;22(10):1990–9.

86. Yeung LK, Ryan JD, Cowell RA, and Barense MD. Recognition Memory Impairments Caused by False Recognition of Novel Objects. J Exp Psychol Gen. 2013 Nov;142(4):1384–97.

87. Lee AC, Yeung LK, and Barense MD. e hippocampus and visual perception. Front Hum Neurosci. 2012;6:91.

88. Ryan JD and Cohen NJ. e nature of change detection and online representations of scenes. J Exp Psychol Hum Percept Perform. 2004 Oct;30(5):988–1015.

89. Hannula DE, Tranel D, and Cohen NJ. e long and the short of it: Relational memory impairments in amnesia, even at short lags. J Neurosci. 2006 Aug 9;26(32):8352–9.

90. Hartley T, Bird CM, Chan D, et al. e hippocampus is required for short-term topographical memory in humans. Hippocampus. 2007;17(1):34–48.

91. Pertzov Y, Miller TD, Gorgoraptis N, et al. Binding de cits in memory following medial temporal lobe damage in patients with voltage-gated potassium channel complex antibody-associated limbic encephalitis. Brain. 2013 Aug;136(Pt 8):2474–85.

92. Olson IR, Page K, Moore KS, et al. Working memory for conjunc- tions relies on the medial temporal lobe. J Neurosci. 2006 Apr 26;26(17):4596–601.

93. Warren DE, Du MC, Jensen U, et al. Hiding in plain view: lesions of the medial temporal lobe impair online representation. Hippocampus. 2012 Jul;22(7):1577–88.

94. Warren DE, Du MC, Tranel D, et al. Observing degradation of visual representations over short intervals when medial temporal lobe is dam- aged. J Cogn Neurosci. 2011 Dec;23(12):3862–73.

CHAPTER 4 the temporal lobes 49

Gross anatomy


e parietal lobes

Masud Husain

On its medial surface (Fig. 5.2) the parietal lobe consists of a large cortical area, the precuneus,7 which lies adjacent to the poste- rior cingulate cortex8 and retrosplenial cortex.9 In recent years, these medial regions have become the focus of much interest in Alzheimer’s disease. Indeed, several investigators have reported that atrophy and hypometabolism in these areas is closely associated with mild cognitive impairment and early Alzheimer’s disease.10–13

Functional network connectivity

Although we have known about the connections of parietal cor- tex at a gross anatomical level for over a century, our understand- ing of its detailed connectivity has, until relatively recently, been based largely on studies in non-human primates.14 However, there is considerable debate about whether the parietal lobes in human and monkey are homologous structures.15,16 e IPL in humans is proportionately much larger, and it has been argued that it may have both a di erent structure and function to the IPL in monkey. Conversely, there is much evidence to suggest that there might be some homologous sub-regions across the two species (see refer- ences 5 and 16 for discussion).


Fig. 5.1 Lateral view of parietal cortex of human and macaque monkey. e human parietal cortex consists of an anterior portion (uncoloured) situated in front of the postcentral sulcus, and a posterior portion behind this. e posterior parietal cortex is divided by the intraparietal sulcus (IPS) into two parts: the superior parietal lobule (SPL) and the inferior parietal lobule (IPL). e IPL consists of the angular gyrus (Ang) and supramarignal gyrus (Smg), and borders the superior temporal gyrus (purple) at a region that is often referred to as the temporo-parietal junction (TPJ). In macaque monkeys, the posterior parietal cortex consists of an SPL (Brodmann’s area 5) and an IPL (Brodmann’s areas 7a and 7b) but, according to Brodmann, the homologues of these macaque regions are all con ned to the human SPL (shaded in yellow), so he considered that the IPL in humans consists of novel cortical areas. Subsequent anatomists disagreed with this scheme, considering the IPL to be similar across both species. It remains to be established whether there are new functional sub-regions within the human IPL.

Adapted from Trends Cogn Sci. 11(1), Husain M and Nachev P. Space and the parietal cortex, pp. 30–6, Copyright (2007), with permission from Elsevier, reproduced under the Creative Commons CC BY License.

On its lateral surface, the human parietal lobe consists of an ante- rior and a posterior portion. e anterior part, bounded by the cen- tral sulcus in front and postcentral sulcus behind, has largely been implicated in basic sensorimotor functions. e posterior parietal lobe, which lies between the postcentral sulcus and the occipital and temporal lobes, has a far greater role in cognitive function. It is divided by the intraparietal sulcus (IPS) into the superior parietal lobule (SPL) and the inferior parietal lobule (IPL) (Fig. 5.1).

e IPL consists of the angular and supramarginal gyrus (Brodmann’s areas 39 and 40 respectively). e nearby border zone between the temporal and parietal lobes is referred to as the tem- poroparietal junction (TPJ). In humans, parts of the IPL and TPJ appear to have distinctly di erent functions in the le and right hemisphere, with limb apraxia, language, and number process- ing disorders more o en associated with le -sided lesions and visuospatial, attentional, and social (e.g., theory of mind) de cits associated with right-sided ones.1–6 e portion of the lateral pari- etal cortex that lies deep to the temporal lobe within the insula is referred to as the parietal operculum and posterior insula.


7a 7b



52 SECTION 1 normal cognitive function

Recent human neuroimaging studies which have examined structural and functional connectivity suggest that both these views might be correct: there appear to be novel regions within the human IPL as well as conserved ones that are homologous to those in the rhesus monkey.17,18 In addition, as noted previously, there is abundant evidence to suggest that the IPL in humans is strongly lateralized between the hemispheres, while the case for such hemi- spheric specialization in monkeys is weak.

e main projections to parietal cortex in non-human primates come from areas involved in sensory processing (e.g. visual, soma- tosensory, and vestibular), while the major outputs are to premotor regions (frontal eye elds and superior colliculus, which control saccadic eye movements, and premotor cortex, which controls reaching and grasping). In turn, these premotor areas project back to parietal cortex, which also sends projections back to brain regions involved in sensory processing. us, the parietal cortex is an important location for the convergence of information from di erent sensory modalities, as well as for the association of sen- sory and motor signals.19 ese ndings also appear to hold for human parietal regions.20,21 e parietal cortex appears to be a major hub in cortical organization, operating on ‘bottom-up’ inputs from sensory regions as well as ‘top-down’ control signals from the frontal lobe.

In the monkey, the anterior parietal lobe is the site of pri- mary somatosensory processing. This region projects heavily to the SPL, whereas visual signals project from occipital cortex predominantly to the IPL. The occipital visual projection to the IPL in the monkey is considered to be part of a ‘dorsal visual stream’ of pathways involved in spatial perception, or visual control of eye and limb movement,22–24 The IPS appears to be an extremely important site for the convergence of information from the SPL and IPL, as well as from premotor centres. Regions

within the IPS encode sensory, motor, attention and short-term memory information in both monkeys and humans.20,21 The medial parietal cortex appears to receive both visual and soma- tosensory inputs and also has reciprocal connections to premo- tor cortex.

In humans, the dorsal visual stream emanating from occipi- tal regions appears to project more heavily to the SPL, IPS, and precuneus rather than to the IPL.5,25,26. Parts of the more ventral parietal regions in humans—the IPL and TPJ—may instead have evolved to subserve higher cognitive functions, including language, number processing, and praxis in the left hemisphere, and spatial, attentional, and ‘social’ cognitive func- tions in the right hemisphere.1–6 Human neuroimaging studies that have assessed resting state function connectivity and func- tional activation now implicate both IPL/TPJ and medial pari- etal regions as key network hubs—cortical areas where there is massive convergence of information from many different brain regions.12,27,28

Medial parietal areas and more posterior parts of the IPL have been implicated as part of the so-called default mode network. is set of brain regions is strongly deactivated during goal- directed tasks, but is active when an individual is at wakeful rest, thinking but not focusing on a problem in the outside world.13 In contrast, more anterior parts of the IPL and adjacent TPJ in the right hemisphere have been identi ed as part of a ventral attention network4,29 which is active during attentive states, while in the le hemisphere, homologues of these regions appear to form part of a language network (Fig. 5.3).29 Both IPL and TPJ have high degrees of functional and structural connectivity with ventrolateral frontal regions, including Broca’s area in the le hemisphere and its homologue in the right hemisphere (see also chapter 8).29,30


31 23

31 23

Brodmann 1909


31 23


Fig. 5.2 Medial view of the parietal cortex of human. e human medial parietal cortex includes the precuneus, the posterior cingulate cortex (Brodmann’s area 23), the retrosplenial cortex embedded in the posterior callosal sulcus (Brodmann’s areas 29 and 30), and the transitional zone (area 31) which separates precuneus from cingulate cortex. e precuneus is located between the marginal ramus of the cingulate sulcus anteriorly and the parieto-occipital ssure posteriorly. e two insets on the right show two di erent parcellations of these regions according to Brodmann and von Economo subsequently.

Adapted from Proc Natl Acad Sci USA. 106(47), Margulies DS, Vincent JL, Kelly C, Lohmann G, Uddin LQ, Biswal BB, et al. Precuneus shares intrinsic functional architecture in humans and monkeys, pp. 20069–74, Copyright (2009), with permission from Proc Natl Acad Sci USA.

31 23



Economo 1925






























u e








c c










g a




l c




































parieto-occipital fissure


































spatial locations.19,20,33,34,35–38 Some of the most prominent disor- ders that follow damage to the posterior parietal lobe are charac- terized by a spatial component,39 although non-spatial functions also contribute.40 At one end of the spectrum are sensory defects; for example, in the visual domain, inferior quadrantanopias which arise because of damage to part of the optic radiations as they pass through the parietal white matter from the lateral geniculate nucleus to the calcarine sulcus. At the other end of the spectrum are complex disorders of attention that can have devastating con- sequences for a patient, presenting an enormous challenge for rehabilitation.

It is important to appreciate that many perceptual disorders that follow parietal damage are di cult to explain simply in terms of de cits in sensory processes alone. us, for example, visual diso- rientation, mislocalization, and constructional apraxia (discussed below) have all been attributed to de cits of ‘spatial remapping’.41,42 is may be due to di culties in updating representations that combine visual information and motor commands sent to the eye muscles to produce a dynamic, spatial ‘map’ of the body and the external world.19,43 Not knowing which way the eyes were pointing in the orbit when the retinal ‘snapshot’ was taken can lead to poor integration of the relative locations of items around us, a factor that probably contributes to several parietal disorders of perception and attention.

It is also the case that many perceptual de cits (e.g. unilateral neglect syndrome) are not con ned to one sensory modality but are multimodal, involving vision, audition, and touch. Indeed, some have considered the parietal lobe to be essential in forming a mul- timodal representation of the body schema,44,45 consistent with the known convergence of di erent types of sensory input to parietal regions. Many of the studies that have been performed in patients, however, have focused on disturbances of vision and touch because these are o en the most clinically conspicuous ndings.

Visual disorientation and mislocalization

Holmes rst described in detail a syndrome of ‘visual disorienta- tion’ in cases of bilateral posterior parietal damage following gun-

shot wounds. Typically, when asked to touch an object in front

of him, a patient would reach in the wrong direction and grope hopelessly until his hand came into contact with it, almost as if he was searching for a small object in the dark, and experience great di culty in walking through a room without bumping into objects. Less dramatic impairments have been demonstrated in unilateral lesions. Patients with parietal lesions misreach when pointing to visual targets presented on a perimeter.48 However, a potential confound is that parietal damage may lead to a disorder of visu- ally guided reaching (see optic ataxia below) in addition to visual mislocalization.

To circumvent this issue, Warrington developed a perceptual test, rst brie y presenting a dot and then a card on which appeared numbers at di erent locations. She asked patients to report the number which best approximated the dot’s location.49 Visual mis- localization on such tasks is more prominent following posterior lesions of the right hemisphere.49,50 A version of this dot locali- zation test, without brief visual presentation, continues to be used in neuropsychological batteries today (e.g. visual object and space perception or VOSP battery). Depth perception and judgment of line orientation may also be impaired a er unilateral (right?) pari- etal lesions.39

CHAPTER 5 the parietal lobes 53






Fig. 5.3 Dorsal and ventral attention networks. e ventral frontoparietal attention network extends from the IPL (inferior parietal lobule) and TPJ (temporoparietal junction) to the VFC (ventral frontal cortex) and is considered to be lateralized to the right hemisphere. Homologous regions in the left hemisphere are considered to form part of a language network. e dorsal attention network, by contrast, is considered to be bilateral. It extends from the SPL (superior parietal lobe) and IPS (intraparietal sulcus) to the FEF (frontal eye elds).

Adapted from Trends Cogn Sci. 11(1), Husain M and Nachev P. Space and the parietal cortex, pp. 30–6, Copyright (2007), with permission from Elsevier, reproduced under the Creative Commons CC BY License.

By contrast, the SPL and IPS appear to be heavily connected to dorsolateral frontal regions. ese parietal and frontal areas are considered to be part of a dorsal attention network which, unlike the ventral attention network, appears to be symmetric across both hemispheres (Fig. 5.3).4 e dorsal frontoparietal attention net- work (not to be confused with the ‘dorsal visual stream’ which con- nects occipital regions to dorsal parietal areas—see chapter 6) may play a role in directing attention to locations or objects of interest in the environment.

e IPL and medial parietal regions, particularly posterior cin- gulate and retrosplenial cortex, also have strong connections to the medial temporal lobe (MTL),24,25,31 accessing the hippocampus via the parahippocampal region.32 e functional role of parieto- hippocampal interactions is yet to be established but these may play an important role in episodic memory. Intriguingly, atrophy and hypometabolism in medial parietal regions that connect to the MTL and are part of the default mode network is closely associated with mild cognitive impairment and early Alzheimer’s disease.10–13 Some have argued that it is the strong network connectivity of these parietal regions to MTL areas a ected in Alzheimer’s pathol- ogy that makes them particularly vulnerable relatively early in the course of the illness.12

Next, the functional anatomy of the parietal cortex in the context of disorders of perception, action, language, and number process- ing that follow damage to the human parietal lobe is considered. Where possible, the anatomy of lesion localization is related to the de cits observed.

Perception and attention

Parietal regions play a crucial role in perception, integrating infor- mation from di erent sensory modalities and directing atten- tion, particularly for localizing or attending to objects at di erent

54 SECTION 1 normal cognitive function Disorders of touch and proprioception

Classically, parietal lesions lead to ‘discriminative’ sensory loss.44 Two-point discrimination, position sense, texture discrimin- ation, stereognosis (ability to identify by touch objects placed in the hand), and graphesthaesia (recognition of numbers scratched on the hand) may all be impaired. Usually, this ‘cortical sensory loss’ is limited to one or two body parts, is more prominent in the arm than the leg, and follows damage to the contralateral anterior parietal lobe or its connections. However, there are also reports of astereognosis following damage to the SPL or IPL. One patient with a large SPL cyst complained that she kept ‘losing’ her arm if she did not look at it: she could not maintain a representation of the limb in the absence of vision.51 In contrast to astereognosis, tactile agno- sia refers to selective impairment of tactile object recognition in the absence of a clinically demonstrable basic sensory impairment. With their eyes closed, patients with tactile agnosia are unable to recognize familiar objects placed in the hand contralateral to the lesion which o en involves the IPL and or posterior insula.52

Constructional apraxia

A common way to demonstrate visuospatial impairments following parietal damage is to ask patients to copy a drawing (e.g. a complex gure such as the Rey–Ostrrieth gure, or equivalent) or a three- dimensional block design. Typically, they encounter di culty in understanding the spatial relationships of the drawing or block design and produce poor reproductions. Such an inability to use visual information to guide acts which require an understanding of the spatial relationship of objects is referred to as constructional apraxia, a syndrome most o en associated with right IPL dam- age.53,54 Paterson and Zangwill gave a particularly clear account of a young man with a focal lesion of the right IPL.55 ey observed that the patient drew complex objects or scenes detail by detail, and appeared to lack any real grasp of the object as a whole. ey char- acterized this problem as a ‘piecemeal approach’—a fragmentation of the visual contents with de cient synthesis.55 It is as if snapshots of the visual scene fail to be integrated correctly, so the relative loca- tions of di erent parts of the scene or an object are not correctly perceived.

Disorders of attention

Parietal regions appear to play a crucial role in deploying select- ive attention to spatial locations or objects as well as sustaining attention over time.5,33,34,38 For example, neurons that are select- ive for a region of space increase their ring when monkeys attend more closely to that location.33,38 ree disorders of attention follow damage to the posterior parietal lobes: extinction, neglect, and simultagnosia. e rst two o en occur a er unilateral dam- age, whereas the last is less common and is observed in its full- blown form a er bilateral parietal lesions or atrophy o en as part of Bálint’s syndrome.56 None of them can be adequately explained as simple sensory impairments.

Extinction is the failure to report a contralesional stimulus (one presented to the side opposite the brain lesion) in the presence of a competing ipsilesional stimulus (on the same side of space as the brain lesion). It can occur in visual, tactile, or auditory domains. For example, patients acknowledge the presence of a single visual stimulus (e.g. the examiner’s nger) when it is presented brie y in either le or right visual hemi elds. However, when both stimuli

are simultaneously presented transiently, one in each hemi eld, they report seeing only the ipsilesional one. Extinction can occur with either le or right parietal lesions, and has been associated with damage to the IPS or TPJ,21 but might also occur with lesions to other brain regions.

Neglect (also referred to as unilateral neglect or hemispatial neglect) is a failure to acknowledge a contralesional stimulus— regardless of the presence or absence of a competing stimulus in ipsilesional space—which cannot be explained simply by sensory loss or motor de cit,4,57 It is o en multimodal, involving visual, tactile, and auditory domains. If neglect is very dense it can be di cult to distinguish from sensory de cits, and some patients with large lesions su er from both (e.g. a visual eld de cit and neglect). However, the clinician is o en alerted to the presence of neglect by the patient’s persistent turning of eyes and head towards the ipsilesional side (without an associated gaze palsy), by nd- ing that unawareness of contralesional stimuli can vary and is not absolute, by observing in the visual domain that the apparent eld loss does not obey the vertical meridian (unlike homonym- ous hemianopia), and by the patient’s failure to orient fully into contralesional space on simple pen-and-paper tasks such as line bisection and cancellation. Some patients also fail to draw the contralesional side of objects. A patient with hemianopia (without neglect) may be slow in performing these tasks but will usually explore contralesional space.

Finally, an important clinical clue comes from the patient’s his- tory. Most patients with neglect are not aware they have a prob- lem (see anosognosia below), whereas those with a hemianopia (without neglect) complain bitterly that they have di culty seeing on one side of space. Neglect is most severe and most long-lasting following right parietal/TPJ lesions, particularly stroke, although it can also occur a er right inferior frontal, basal ganglia, and tha- lamic damage.

Simultagnosia (or simultanagnosia) refers to a disorder of vision in which individuals have di culty apprehending the entire scene, in visualizing its separate elements simultaneously. Although they may describe some of the details meticulously, individuals with simultagnosia may still not appreciate what is happening overall in a picture (e.g. the Boston cookie the scene). eir perception appears piecemeal, as if they have snapshots of di erent items in a scene but cannot integrate these into a coherent whole.58 Simultagnosia is one component of Bálint’s syndrome.56 Previously, simultagnosia was most commonly associated with massive bilat- eral lesions of temporoparieto-occipital cortex (e.g. from watershed infarctions). Nowadays, it is most commonly observed as a feature of posterior cortical atrophy59 (see chapter 15) which is usually a posterior variant of Alzheimer’s disease.


Unawareness of illness is referred to as anosognosia. Patients may steadfastly deny they have su ered a stroke or hemiparesis, even if the examiner demonstrates that one limb is weak. e condition is o en, but not invariably, associated with unilateral neglect, with many such patients denying they have a visual disorder. Anosognosia appears most commonly a er right-hemisphere lesions. Although it is traditionally associated with right IPL damage,60 recent studies of anosognosia for hemiparesis suggest involvement of right poste- rior insula or premotor frontal regions.61,62

Visuomotor and motor control

Neurons in the parietal cortex integrate sensory information (e.g. location of a visual object) with motor commands (e.g. to the eyes or limbs) and, together with premotor regions in frontal cortex, appear to play a crucial role in directing gaze and the hand to objects—including tools—around us.20,63,64 Imaging studies have identi ed several regions within dorsal and dorsomedial parietal cortex involved in directing the eyes and the hands to reach, as well as action observation (e.g. when people view others using tools) (Fig. 5.4). Some of the disorders that follow parietal damage re ect such functions.16,65

Optic ataxia

Bálint rst used the term ‘optic ataxia’ to refer to an impairment of visually guided reaching that he observed following bilateral posterior cortical damage. Since then, many reports have followed of patients with unilateral or bilateral parietal lesions. e term Bálint’s syndrome is used to refer to a combination of optic ataxia, simultagnosia, and ocular apraxia,56 most commonly observed nowadays in cases of posterior cortical atrophy.59 However, many patients have been reported with optic ataxia alone. e most com- monly described defect appears to be a ‘ eld e ect’: inaccurate reaching with either hand to visual targets located in the visual hemi eld contralateral to the lesion. However, an ‘arm e ect’ has also been reported: misreaching with the contralesional arm to tar- gets in either visual eld. is may also occur in combination with a ‘ eld e ect’.66

At the bedside, the disorder is best demonstrated by asking the patient to xate centrally (e.g. on the examiner’s nose) and point to a target presented peripherally (e.g. the examiner’s nger). If the patient is allowed to move his eyes and look at the target, the

disorder may not be evident. As well as misdirecting their reaches, optic ataxic patients may also encounter di culty in planning the appropriate grasp required to pick up an object.66 Lesions in either hemisphere appear to cause the syndrome, with the critical lesion site being the SPL and adjacent IPS, consistent with functional imaging studies in healthy people which demonstrate these regions play a crucial role in reaching and grasping (Fig. 5.4).20,64

Impairments of gaze control or ocular apraxia

In addition to simultagnosia and optic ataxia, patient’s with Bálint’s syndrome experience di culty in shi ing gaze to objects in periph- eral vision.56 ey seem to lock their gaze on the item they are xat- ing and have di culty initiating saccades to other objects—ocular apraxia. Holmes described a similar problem in his cases with vis- ual disorientation, but in addition reported other disorders of ocu- lomotor control.46,47 Typically, when one of his patients was asked to look at something or was spoken to, he would stare in the wrong direction and then move his eyes awkwardly until he found, o en as if by chance, the object he was looking for. Some of Holmes’ cases also failed to accommodate and converge their eyes correctly, and smooth pursuit could also be impaired. Holmes considered these problems to be secondary to visual perceptual de cits. However, these disorders may be accounted for by loss of neurons associated with maintaining xation, directing saccades, or pursuit eye move- ments, all of which have been demonstrated in monkey posterior parietal cortical neurons.19 Functional imaging studies in humans suggest that there are several parietal eye elds located within the dorsal IPS (Fig. 5.4).35,67

Limb apraxia

Limb apraxia refers to an impairment in the ability to perform skilled movements which cannot be attributed to weakness,








Tool execution

Tool planning


Action observation

Central Postcentral Intraparietal

Transverse occipital Parieto-occipital

Fig. 5.4 Parietal regions activate in imaging studies of action control. (a) Schematic of parietal regions implicated in functional imaging studies of directing saccades, pointing or grasping. e parietal eye elds (PEF) are now known to consist of several di erent regions that are activated by eye movements. Area AIP (anterior intraparietal sulcus) has been considered to play a role in grasping while areas mIPS (medial intraparietal sulcus) and mOPJ (medial occipitoparietal junction) have been implicated in reaching. Area vIPS (ventral intraparietal sulcus) responds to multimodal moving stimuli. (b) Lateral inferior parietal regions in the left hemisphere active during tool use or thinking about tool use. (c) Left parietal regions active during action observation.

Adapted from Curr Opin Neurobiol. 16(2), Culham JC and Valyear KF. Human parietal cortex in action, pp. 205–12, Copyright (2006), with permission from Elsevier.

CHAPTER 5 the parietal lobes 55

56 SECTION 1 normal cognitive function

sensory disturbance, or involuntary movements such as tremor,1 It may occur in up to 50 per cent of unselected patients with le – hemisphere damage, but frequently goes unrecognized either because patients may not be aware of a problem in daily life, or because praxis is commonly not tested, or because many le – hemisphere patients are dysphasic.

Liepmann, at the turn of the last century (see reference 68), originally proposed that there are three types of apraxia: ideational, ideomotor, and limb-kinetic (or melokinetic). He considered that inadequate formulation of a motor programme would result in ide- ational apraxia. Traditionally, this is considered to be best observed when a patient is asked to produce a sequence of gestures on com- mand, rather than when the examiner performs a gesture for him to imitate. By contrast, in ideomotor apraxia, a patient may know what to do but cannot produce the correct actions either on verbal request or when asked to imitate gestures. He is aware of his poor performance and may try to correct it, so the problem is one of defective execution rather than ideation. is is the most common type of limb apraxia for which clinicians usually test. Finally, limb- kinetic apraxia consists of loss of control of ne nger movements and o en follows damage to the corticospinal pathways, and will not be considered further in this discussion.

In ideomotor apraxia, the representation of the gesture to be performed is considered to be intact but its execution is defective. Traditionally, an important piece of evidence in favour of this dis- tinction is the failure of patients to produce correct gestures even when asked to imitate the examiner’s movements. us, these patients perform poorly regardless of whether they have to pro- duce a gesture on verbal command (by recalling a movement rep- resentation) or imitate it. Typically, however, their performance is better when imitating movements or using objects than when they are asked to pantomime transitive acts (i.e. mime the use of a tool or instrument). Intransitive movements (communicative gestures such as waving goodbye) may be relatively well preserved. us, ideomotor apraxia appears to spare movements that are automatic or habitual such as waving, or repetitive as in nger-tapping.

Some patients with ideomotor apraxia may use a body part as a tool, such as using their ngers to act like scissor blades, when asked to pantomime using scissors. is type of error may have been overemphasized, since even neurologically normal individu- als will sometimes do this. Other patients produce inappropriate movements about multiple joints. For example, when asked to pan- tomime the use of a screwdriver, they may rotate their arm at the shoulder rather than at the elbow.

e localization of apraxia appears in many ways to be the mirror image of the neglect syndrome, involving inferior parietal and fron- tal regions in the le hemisphere.69 Liepmann considered ideomo- tor apraxia to be a disconnection syndrome, in which sensory visual and audioverbal representations (in the posterior le hemisphere) were disconnected from kinesthetic-motor ‘engrams’ (around the central sulcus). e critical anatomical site of the disconnection, he suggested, was the white matter underlying the le IPL. Liepmann was quite clear that his model did not envisage a centre for ‘gesture control’ within the IPL, but subsequent investigators have chal- lenged this scheme, arguing that movement representations encod- ing the spatial and temporal patterns of skilled movements, are stored within the le IPL (see reference 68 and Fig. 5.4).

e use of the term ideational apraxia has been extremely con- fusing. It is o en used to refer to an impairment in the ability to

perform a series of motor acts. For example, when asked to make a cup of tea, a patient may perform each element of the sequence but in an incorrect order. However, De Renzi has argued that ideational apraxia refers to an inability to recall previously well- established actions, for example, object use, an ‘amnesia of usage’.70 ere are certainly examples of patients who have di culty using a single object without having to perform a sequence of acts using multiple objects. For example, Pick originally reported a case who used a razor as a comb! Some favour a di erent term—conceptual apraxia—to specify a defect in the knowledge required to select and use tools and objects.71 is appears most frequently to follow lesions of the le posterior parietal lobe. Functional imaging stud- ies in healthy people have delineated le parietal regions involved in tool use and observing the actions of others.64

Language and number processing

In functional imaging studies, part of the le IPL (angular gyrus) is activated by tasks that require semantic processing including comprehension during reading,72 while a region around the le TPJ (known as area Spt: Sylvian parietotemporal, within the pla- num temporale) has been implicated in auditory sensorimotor processing and phonological short-term or working memory.73 By contrast, neuroimaging has implicated the le IPS in number processing.74

Conduction aphasia

Lesions of the le parietal lobe have been associated with the syndrome of conduction aphasia which is characterized by uent speech but with phonemic errors, intact comprehension but poor repetition. Classically this has been considered to be a ‘disconnec- tion syndrome’ in which the arcuate fasciculus is a ected, thereby disconnecting superior temporal lobe language zones from Broca’s area. More recent lesion analysis suggests that damage to cortical area Spt might be su cient without having to invoke white matter disconnection,73 although this is contested.

Dyscalculia and Gerstmann’s syndrome

ere is now considerable evidence that lesions of the le parietal lobe can lead to de cits in number processing and dyscalculia (see chapter 17). e existence of Gerstmann’s syndrome (dyscalculia, dysgraphia, nger agnosia, or the inability to distinguish between ngers and le -right disorientation) —has, however, been disputed. When reported, it has been associated with le parietal lesions near the TPJ.


It is generally agreed that the parietal lobes play a role in short- term or working memory. Imaging studies have repeatedly demon- strated this with verbal material more likely to activate le parietal regions more than right, and vice versa for spatial material. Most o en the IPS has been implicated.75 Lesion studies too have impli- cated posterior parietal areas in the le hemisphere in phonological working memory and right hemisphere regions in spatial working memory.76,77 Some recent studies suggest that parietal areas, which project heavily to the medial temporal lobe, might also play a role in aspects of episodic memory largely on the basis of imaging data,78 but this proposal remains controversial.


1. Goldenberg G. Apraxia and the parietal lobes. Neuropsychologia. 2009 May;47(6):1449–59.

2. Henseler I, Regenbrecht F, and Obrig H. Lesion correlates of patholinguistic pro les in chronic aphasia: comparisons of syndrome-, modality- and symptom-level assessment. Brain. 2014 Mar;137(Pt 3):918–30.

3. Grafman J, Passa ume D, Faglioni P, et al. Calculation disturbances in adults with focal hemispheric damage. Cortex. 1982 Apr;18(1):37–49.

4. Corbetta M and Shulman GL. Spatial neglect and attention networks.
Annu Rev Neurosci. 2011;34:569–99.

5. Singh-Curry V and Husain M. e functional role of the inferior pari-
etal lobe in the dorsal and ventral stream dichotomy. Neuropsychologia.
2009 May;47(6):1434–48.

6. Decety J and Lamm C. e role of the right temporoparietal junction in
social interaction: how low-level computational processes contribute to
meta-cognition. Neuroscientist. 2007 Dec;13(6):580–93.

7. Cavanna AE and Trimble MR. e precuneus: a review of its functional
anatomy and behavioural correlates. Brain. 2006 Jan 3;129(3):564–83.

8. Leech R and Sharp DJ. e role of the posterior cingulate cortex in
cognition and disease. Brain. 2014 Jan;137(Pt 1):12–32.

9. Vann SD, Aggleton JP, and Maguire EA. What does the retrosplenial
cortex do? Nat Rev Neurosci. 2009 Nov;10(11):792–802.

10. Pengas G, Hodges JR, Watson P, et al. Focal posterior cingulate atrophy in incipient Alzheimer’s disease. Neurobiol Aging. 2010 Jan;31(1):25–33.

11. Karas G, Scheltens P, Rombouts S, et al. Precuneus atrophy in early- onset Alzheimer’s disease: a morphometric structural MRI study. Neuroradiology. 2007 Dec;49(12):967–76.

12. Buckner RL, Sepulcre J, Talukdar T, et al. Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer’s disease. J Neurosci. 2009 Feb 11;29(6):1860–73.

13. Buckner RL, Andrews-Hanna JR, and Schacter DL. e brain’s default network: anatomy, function, and relevance to disease. Ann NY Acad Sci. 2008 Mar;1124:1–38.

14. Schmahmann JD and Pandya D. Fiber Pathways of the Brain. Oxford University Press, 2009.

15. Husain M and Nachev P. Space and the parietal cortex. Trends Cogn Sci. 2007;11:30–6.

16. Caminiti R, Chafee MV, Battaglia-Mayer A, et al. Understanding the parietal lobe syndrome from a neurophysiological and evolutionary perspective. Eur J Neurosci. 2010 Jun;31(12):2320–40.

17. Mars RB, Jbabdi S, Sallet J, et al. Di usion-weighted imaging tractography-based parcellation of the human parietal cortex and com- parison with human and macaque resting-state functional connectivity. J Neurosci. 2011 Mar 16;31(11):4087–100.

18. Mantini D, Corbetta M, Romani GL, et al. Evolutionarily novel functional networks in the human brain? J Neurosci. 2013 Feb 20;33(8):3259–75.

19. Andersen RA. Multimodal integration for the representation of space in the posterior parietal cortex. Philos Trans R Soc Lond B. 1997;1997(352):1421–8.

20. Culham JC and Valyear KF. Human parietal cortex in action. Curr Opin Neurobiol. 2006 Apr;16(2):205–12.

21. Vandenberghe R and Gillebert CR. Parcellation of parietal cortex: con- vergence between lesion-symptom mapping and mapping of the intact functioning brain. Behav Brain Res. 2009 May 16;199(2):171–82.

22. Ungerleider LG and Mishkin M. Two Cortical Visual Systems. Analysis of Visual Behaviour. Cambridge, MA: MIT Press, 1982.

23. Milner AD and Goodale MA. e Visual Brain in Action. Oxford: Oxford University Press, 1995.

24. Kravitz DJ, Saleem KS, Baker CI, et al. A new neural framework for visuospatial processing. Nat Rev Neurosci. 2011 Apr;12(4):217–30.

25. Margulies DS, Vincent JL, Kelly C, et al. Precuneus shares intrinsic
functional architecture in humans and monkeys. Proc Natl Acad Sci USA. 2009 Nov 24;106(47):20069–74.

26. Katzner S and Weigelt S. Visual cortical networks: of mice and men. Curr Opin Neurobiol. 2013 Apr;23(2):202–6.

27. Cabeza R, Ciaramelli E, and Moscovitch M. Cognitive contributions of the ventral parietal cortex: an integrative theoretical account. Trends Cogn Sci. 2012 Jun;16(6):338–52.

28. Carter RM and Huettel SA. A nexus model of the temporal-parietal junction. Trends Cogn Sci. 2013 Jul;17(7):328–36.

29. Laird AR, Fox PM, Eickho SB, et al. Behavioral interpreta- tions of intrinsic connectivity networks. J Cogn Neurosci. 2011 Dec;23(12):4022–37.

30. iebaut de Schotten M, Dell’Acqua F, et al. A lateralized brain network for visuospatial attention. Nat Neurosci. 2011 Oct;14(10):1245–6.

31. Kahn I, Andrews-Hanna JR, Vincent JL, et al. Distinct cortical anatomy linked to subregions of the medial temporal lobe revealed by intrinsic functional connectivity. J Neurophysiol. 2008 Jul;100(1):129–39.

32. Ranganath C and Ritchey M. Two cortical systems for memory-guided behaviour. Nat Rev Neurosci. 2012 Oct;13(10):713–26.

33. Colby C and Goldberg ME. Space and attention in parietal cortex. Annu Rev Neurosci. 1999;22:319–49.

34. Culham JC and Kanwisher N. Neuroimaging of cognitive functions in human parietal cortex. Curr Opin Neurobiol. 2001;11:157–63.

35. Sereno MI and Huang R-S. Multisensory maps in parietal cortex. Curr Opin Neurobiol. 2014 Feb;24(1):39–46.

36. Driver J and Spence C. Multisensory perception: beyond modularity and convergence. Curr Biol. 2000 Oct 19;10(20):R731–5.

37. Macaluso E. Orienting of spatial attention and the interplay between the senses. Cortex. 2010 Mar;46(3):282–97.

38. Bisley JW and Goldberg ME. Attention, intention, and priority in the parietal lobe. Annu Rev Neurosci. 2010;33:1–21.

39. De Renzi E. Disorders of Space Exploration and Cognition. New York, NY: Wiley, 1982.

40. Husain M and Rorden C. Non-spatially lateralized mechanisms in hemispatial neglect. Nat Rev Neurosci. 2003;4(1):26–36.

41. Pisella L, Alahyane N, Blangero A, et al. Right-hemispheric dominance for visual remapping in humans. Philos Trans R Soc Lond B Biol Sci. 2011 Feb 27;366(1564):572–85.

42. Russell C, Deidda C, Malhotra P, et al. A de cit of spatial remapping in constructional apraxia a er right-hemisphere stroke. Brain. 2010 Apr;133(Pt 4):1239–51.

43. Duhamel JR, Colby C, and Goldberg ME. e updating of the repre- sentation of visual space in parietal cortex by intended eye movements. Science. 1992;1992:90–2.

44. Head H and Holmes G. Sensory Disturbances from Cerebral Lesions. Brain. 1911 Jan 11;34(2–3):102–254.

45. Haggard P and Wolpert DM. Disorders of Body Scheme. In: HJ Freund, M Jeannerod, M Hallett, and R Leiguarda (eds). Higher-Order Motor Disorders. Oxford University Press: Oxford, 2005.

46. Holmes G. Disturbances of visual orientation. Br J Ophthalmol. 1918 Sep;2(9):449–68.

47. Holmes G. Disturbances of visual orientation. Br J Ophthalmol. 1918 Oct;2(10):506–16.

48. Ratcli G and Davies-Jones GA. Defective visual localization in focal brain wounds. Brain. 1972;95(1):49–60.

49. Warrington EK and Rabin P. Perceptual matching in patients with cerebral lesions. Neuropsychologia. 1970 Nov;8(4):475–87.

50. Hannay HJ, Varney NR, and Benton AL. Visual localization in patients with unilateral brain disease. J Neurol Neurosur Ps. 1976 Apr;39(4):307–13.

51. Wolpert DM, Goodbody SJ, and Husain M. Maintaining internal repre- sentations: the role of the human superior parietal lobe. Nat Neurosci. 1998 Oct;1(6):529–33.

52. Caselli RJ. Ventrolateral and dorsomedial somatosensory association cortex damage produces distinct somesthetic syndromes in humans. Neurology. 1993 Apr;43(4):762–71.

53. Hier DB, Mondlock J, and Caplan LR. Behavioral abnormalities a er right hemisphere stroke. Neurology. 1983 Apr;33(3):337–44.

CHAPTER 5 the parietal lobes 57

58 SECTION 1 normal cognitive function

54. Ruessmann K, Sondag HD, and Beneicke U. On the cer-
ebral localization of constructional apraxia. Int J Neurosci. 1988 Sep;42(1–2):59–62.

55. Patterson A and Zangwill OL. Disorders of visual space percep- tion associated with lesions of the right cerebral hemisphere. Brain. 1944;67:331–58.

56. Rizzo M and Vecera SP. Psychoanatomical substrates of Bálint’s syn- drome. J Neurol Neurosur Ps. 2002 Feb;72(2):162–78.

57. Parton A, Malhotra P, and Husain M. Hemispatial neglect. J Neurol Neurosur Ps. 2004 Jan;75(1):13–21.

58. Dalrymple KA, Barton JJS, and Kingstone A. A world unglued: simul- tanagnosia as a spatial restriction of attention. Front Hum Neurosci. 2013;7:145.

59. Crutch SJ, Lehmann M, Schott JM, et al. Posterior cortical atrophy. Lancet Neurol. 2012 Feb;11(2):170–8.

60. Vossel S, Weiss PH, Eschenbeck P, et al. e neural basis of ano- sognosia for spatial neglect a er stroke. Stroke J Cereb Circ. 2012 Jul;43(7):1954–6.

61. Karnath H-O, Baier B, and Nägele T. Awareness of the functioning of one’s own limbs mediated by the insular cortex? J Neurosci. 2005 Aug 3;25(31):7134–8.

62. Berti A, Bottini G, Gandola M, et al. Shared cortical anatomy for motor awareness and motor control. Science. 2005 Jul 15;309(5733):488–91.

63. Andersen RA and Cui H. Intention, action planning, and decision making in parietal-frontal circuits. Neuron. 2009 Sep 10;63(5):568–83.

64. Vingerhoets G. Contribution of the posterior parietal cortex in reaching, grasping, and using objects and tools. Front Psychol. 2014;5:151.

65. Andersen RA, Andersen KN, Hwang EJ, et al. Optic ataxia: from Balint’s syndrome to the parietal reach region. Neuron. 2014 Mar 5;81(5):967–83.

66. Perenin M-T and Vighetto A. Optic ataxia: a speci c disruption in visuomotor mechanisms. I. Di erent aspects of the de cit in reaching for objects. Brain. 1988;111:643–74.

67. Konen CS and Kastner S. Representation of eye movements and stimulus motion in topographically organized areas of human posterior parietal cortex. J Neurosci. 2008 Aug 13;28(33):8361–75.

68. Goldenberg G. Apraxia: e Cognitive Side of Motor Control. Oxford: Oxford University Press, 2013.

69. Haaland KY, Harrington DL, and Knight RT. Neural representations of skilled movement. Brain. 2000 Nov;123 (Pt 11):2306–13.

70. De Renzi E and Lucchelli F. Ideational apraxia. Brain. 1988 Oct;111 (Pt 5):1173–85.

71. Heilman KM, Maher LM, Greenwald ML, et al. Conceptual apraxia from lateralized lesions. Neurology. 1997 Aug;49(2):457–64.

72. Binder JR, Desai RH, Graves WW, et al. Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb Cortex. 1991. 2009 Dec;19(12):2767–96.

73. Hickok G and Poeppel D. e cortical organization of speech process- ing. Nat Rev Neurosci. 2007 May;8(5):393–402.

74. Nieder A and Dehaene S. Representation of number in the brain. Annu Rev Neurosci. 2009;32:185–208.

75. Baddeley A. Working memory: looking back and looking forward. Nat Rev Neurosci. 2003 Oct;4(10):829–39.

76. Shallice T and Warrington EK. Independent functioning of verbal memory stores: a neuropsychological study. Q J Exp Psychol. 1970 May;22(2):261–73.

77. Hanley JR, Young AW, and Pearson NA. Impairment of the visuo- spatial sketch pad. Q J Exp Psychol A. 1991 Feb;43(1):101–25.

78. Cabeza R, Ciaramelli E, Olson IR, et al. e parietal cortex and episodic memory: an attentional account. Nat Rev Neurosci. 2008 Aug;9(8):613–25.


e occipital lobes

Geraint Rees

In the human brain, the occipital lobe is a pyramidal shaped struc- ture located at the most posterior point of each cerebral hemisphere. Traditionally it is de ned as extending from the occipital pole to the parieto-occipital ssure, and in primate brains it is a structure involved in processing visual information. e discovery and func- tional characterization of di erent visual areas of the occipital lobe is one of the major achievements of twentieth-century neurology and visual neuroscience and has helped clarify and understand the clinical presentation of many sensory disorders caused by occipital lobe damage or dysfunction.

At the end of the nineteenth century, it was noted that unilat- eral lesions of the striate cortex of the occipital lobe in monkeys lead to hemianopia.1 is identi cation of the occipital lobe with visual function was extended to humans in clinical observations2 that suggested that the calcarine sulcus, which extends anteriorly from the occipital pole on the medial aspect of the occipital lobe, was the crucial location which when damaged produced contralat- eral hemianopia. ese clinical observations established that the occipital lobe received input from the contralateral hemiretina, but the precise correspondence between how the visual eld was rep- resented on the retina and how it was represented in the calcarine sulcus remained obscure because of the relatively large size of the lesions in the patients who were studied, which limited the ability to localize function.

e invention and subsequent utilization of the high-velocity ri e in the armed con icts that swept the world at the beginning of the twentieth century produced new opportunities to discover the functional anatomy of visual cortex. In soldiers with head inju- ries that were associated with visual eld defects, it proved possible to determine the intracerebral trajectory of the bullet that caused such a defect because its velocity meant that it took a straight course between entry and exit wounds. Inouye3 studied such brain- injured patients from the Russo–Japanese war, and deduced that the visual elds were represented in striate cortex in the form of a map. Speci cally, he proposed that the central visual eld was represented more posteriorly in the contralateral occipital lobe. Moreover, he suggested from careful consideration of the di erent patients that the cortical maps were distorted, with the central vis- ual eld occupying a larger area of occipital cortex than the periph- eral visual elds.

e British neurologist Gordon Holmes subsequently studied over 2000 brain-injured British soldiers in the First World War,4 con rming and extending these observations to propose an antero- posterior organization with central vision located more posteri- orly and peripheral vision more anteriorly in the calcarine sulcus.

Holmes also concluded that cortical lesions resulted in homony- mous (congruous) defects and produced a more detailed descrip- tion of the representation in the visual cortex of the horizontal and vertical axes of the retina.

ese clinical observations thus rmly established the corre- spondence between the gross anatomy of the human occipital lobe and the de cits in vision that resulted from brain injury. In particular, they proposed a retinotopic organization of the visual cortex whereby there is a topographic correspondence between locations in the retina and corresponding locations in the early visual cortex that represent a particular part of the visual eld. Speci cally, nearby regions on the retina project to nearby cor- tical regions and in the cortex, neighbouring positions in the visual eld are represented by groups of neurons that are adja- cent in the grey matter. is primary visual cortex (subsequently known as V1) was located in the calcarine sulcus in the posterior occipital lobe.

Using non-invasive brain imaging

to measure retinotopic maps

In the 1980s and early 1990s, investigators realized that the top- ographic organization of visual areas in humans that had been revealed almost a century earlier could now be studied using non- invasive methods. e use of positron emission tomography (PET) and then the advent of functional magnetic resonance imaging (MRI) allowed signals to be recorded from healthy volunteers that re ected local neuronal activity in the human brain. Some of the rst studies to demonstrate this new technique employed activa- tion of the occipital lobe in response to visual eld stimulation with a ashing checkerboard.5 By asking participants to xate and pre- senting visual stimuli at particular locations rather than through- out the visual eld, investigators devised e cient approaches that could map topographic cortical representations of the visual eld in the occipital lobe.6–8 is technique became known as retinotopic mapping and is now a standard procedure (Fig. 6.1).

ese early studies showed, as suspected from earlier clinico- pathological investigation, that the mapping from the retina to the visual cortex was not only topographic but could be best described by a log-polar transformation. Such a transformation results in the standard x/y (Cartesian) axes in the retina being modi ed into a polar coordinate system in the cortex, where position on the retina (corresponding to position in the visual eld) is represented on the cortical surface in terms of eccentricity (the di erence from the centre of vision) and polar angle (relative to a horizontal or verti- cal axis). e logarithmic nature of the transformation is such that


60 SECTION 1 normal cognitive function

Fig. 6.1 Retinotopic maps in the early visual cortex. Two di erent stimuli used to delineate retinotopic maps in the human occipital lobe are expanding rings (left) and rotating wedges (right). Each stimulus traverses the visual eld repeatedly while brain activity is measured using fMRI. Analysis allows each point on the cortical surface that responds to the visual stimuli to be labelled according to the location in the visual eld that when stimulated produces the maximal activation. When the colour labels correspond to visual eld eccentricity (left panels) or phase/angle (right panels), two di erent types of macroscopic organization are visible. On the left, regions responding to more central portions of the visual eld are located more posteriorly; while on the right, a pattern of stripes orthogonal to the organization shown in the right panels illustrates a series of visual eld representations that when analysed more closely correspond to the organization shown in Fig. 6.2.

Reproduced from J Vis. 3(10), Dougherty RF et al. Visual eld representations and locations of visual areas V1/2/3 in human visual cortex, pp. 586–98, Copyright (2003), with permission from the Association for Research in Vision and Ophthalmology.

representations of the central retina (visual eld) are expanded rel- ative to those of the more peripheral retina (visual eld).

e elegance of this log-polar transformation in accounting for the topographic cortical representations in human visual cor- tex is evident when inspecting such retinotopic maps (Fig. 6.1). A variety of visualization methods have been developed in the last 25 years that computationally separate the grey and white matter, and o en make responses from sulcal regions visible by compu- tationally ‘in ating’ or ‘ attening’ representations of the cortical surface (see Fig. 6.4). By examining the activations produced by retinotopic mapping using functional MRI on such surface rep- resentations, the topographic relationship between visual eld stimulation and the locations that respond on the cortical surface becomes apparent. In particular, examining the angle (phase) com- ponent of retinotopic maps reveals a stripey pattern on the med- ial occipital cortex whereby representations of the horizontal and vertical meridians are arranged in parallel stripes on the cortical surface (Fig. 6.1 right-hand panel). ese alternating bands corres- pond to the borders between what are now known to be multiple retinotopic maps whose representations lie alongside each other in the occipital lobe.

A complementary organizational principle is revealed when examining the eccentricity map, where stripes at right angles to the angle (phase) map show that there is a gradient of representations of eccentricity (Fig. 6.1 le -hand panel), with more central regions of the visual eld being represented more posteriorly in the retino- topic map and more peripheral regions anteriorly.

Organization of retinotopic maps

in human early visual cortex

is organization of the early visual cortex has now been repeat- edly con rmed and is summarized in Fig. 6.2 (also see Fig. 6.6). A complete representation of the visual eld is contained within the primary visual cortex or V1, which is consistently located in the depths of the calcarine sulcus extending superiorly and anteriorly onto the medial surface of the occipital lobe, and posteriorly to the occipital pole. Its boundaries superiorly and inferiorly are repre- sentations of the vertical meridian; the lower vertical meridian lies superiorly and represents the boundary between V1 and dorsal V2. Inferiorly the upper vertical meridian lies between V1 and ventral V2. V2 therefore contains a complete representation of the contra- lateral visual eld, but split between an anatomically dorsal portion (representing the contralateral lower visual quadrant) and a ven- tral portion (representing the contralateral upper visual quadrant). Similarly V3 is also split into dorsal and ventral portions, so V1–V3 form a concentric arrangement in occipital cortex.

is organization elegantly complements and accounts for previ- ous clinical observations and deductions of cortical anatomy from those observations. For example, the split representation of V2 and V3 can account for the clinical observation that homonymous quadrantic eld defects arising from cortical lesions can have sharp horizontal edges. Although it was thought initially that such eld defects might arise from lesions to primary visual cortex in the cal- carine sulcus, this appeared inconsistent with the o en irregular

(c) (d)

Fig. 6.2 Topography of human primary visual cortex and surrounding areas. e functional anatomy of early visual areas is overlaid on an anatomical MRI image from a single participant for right and left hemispheres respectively. Panels (a) and (b) show occipital cortex from right and left hemispheres; panels (c) and (d) present the same data in a cortically ‘in ated’ view and from a posterior vantage point. Human brain areas revealed by retinotopic mapping are displayed in false (blue/yellow) colour and labelled. A concentric arrangement of V1, V2, and V3 is apparent.

Reproduced from Proc Natl Acad Sci USA. 95(3), Tootell RBH, Hadjikhani NK, Vandu ell W, et al. Functional analysis of primary visual cortex (V1) in humans, pp. 811–17, Copyright (1998), with permission from PNAS.

borders of cortical lesions because the representation of the hori- zontal meridian runs along the depths of the calcarine sulcus, and in order to produce a sharp edge to the eld defect the lesion would need to run exactly along such a boundary. But the split representa- tion of V2/V3 provides an elegant answer to this conundrum, as proposed by Horton and Hoyt.9 Speci cally, even if a lesion has irregular boundaries, if it is located in V2/3 and crosses the bound- ary of the horizontal meridian between V3 and V2 or V2 and V1, then it will produce a quadrantic eld defect because of the split representation of the upper and lower visual elds in V2 and V3. us the retinotopic organization of early human visual cortices has localizing power for clinical practice.

Damage to the early visual cortex generally results in a visual eld defect. Profound bilateral cortical damage such as that caused by bilateral cerebral infarction in the territory of the posterior cerebral arteries can also cause Anton’s syndrome, albeit rarely.10 Patients with Anton’s syndrome have no functional vision and sometimes cannot even distinguish light and dark; they have normal pupil- lary responses to light. However, despite being profoundly corti- cally blind, strikingly they deny having any visual di culty. Anton’s syndrome is therefore an anosognosia. A variety of explanations have been advanced but without a clear consensus on the underly- ing mechanisms.11 Typically the cortical damage associated with Anton’s syndrome involves early (retinotopic) visual cortices bilat- erally. However, the syndrome has also been described following bilateral optic nerve damage and frontal contusions,12 so can also be caused by peripheral lesions to the early visual system.

Retinotopic mapping has further revealed a multiplicity of visual maps in humans, extending throughout occipital cortex. In con- trast to the V1—V3 retinotopic maps, the precise number, extent, and organization of such maps remains a topic of debate (see ref- erence13 for a review). ese may include areas known as hV4, VO-1, and VO-2 on the ventral occipital surface next to the ven- tral portion of V3; maps that have been labelled LO-1, LO-2, TO-1, and TO-2 on the lateral occipital surface that are coextensive with object-selective cortices discussed below; and V3A/V3B on the dorsal surface plus further maps running into parietal cortex (see reference 14 for a review).

Technically these maps are o en much smaller and their responses harder to measure, so their precise functional properties and exact characterization remain o en controversial. Nevertheless, the sheer multiplicity of maps in the human occipital lobe suggests that they must be important for visual processing, but a demonstration that such a topographic organization is critical for normal visual func- tion remains elusive. Clinically, neurodevelopmental disorders that massively disrupt topographic visual eld maps such as albinism15 or failure of development of the optic chasm (see e.g. reference 16) have relatively little e ect on spatial vision. Finally, position in the visual eld is not the only feature that is mapped on the cortical surface. Consistent with observations in monkeys, it appears that ocular dominance and orientation17 can be mapped on the occipi- tal cortical surface though the spatial scale of such mapping is suf- ciently ne that measurement with contemporary neuroimaging remains challenging.

CHAPTER 6 the occipital lobes 61

(a) (b)

62 SECTION 1 normal cognitive function

Functional segregation in the human

occipital lobe

Alongside the use of non-invasive brain imaging to delineate spatial maps in the occipital lobe has come parallel investigation of whether di erent areas of the occipital lobe respond di er- entially to the many features that make up a visual scene. Early clinical investigators such as Holmes’ suggested that selective disturbances of motion perception could not be distinguished from more general disorders of the perception of objects and that purely cortical lesions did not cause loss of colour vision.18 Subsequent clinical observations showed that selective distur- bances of colour19 and motion20 could result from focal damage to the occipital lobe.

In humans, these observations following brain damage were complemented by pioneering work using positron emission tomog- raphy to visualize changes in blood ow associated with neural activity during perception of di erent visual features (Fig. 6.3). is demonstrated an area of extrastriate cortex on the lateral surface of the occipital lobe close to the boundary with the temporal lobe that responded more strongly to moving than stationary stimuli.21 is area is now known as V5/MT, re ecting its apparent homol- ogy with similar motion-responsive regions in monkey. A second region on the ventral surface of the occipital lobe responded more to coloured patterns than to matched grayscale patterns, consid- ered to be consistent with a colour-responsive region in monkey cortex known as area V4.22

ese early observations demonstrated the principle of func- tional specialization in the extrastriate visual cortex; di erent cortical regions process di erent aspects of the visual scene. Such functionally specialized areas, when damaged, give rise to corre- sponding clinical de cits in, for example, colour or motion per- ception. Further investigation has revealed that some of these functionally specialized regions also contain spatial maps. For example, the colour-responsive region in the ventral visual cortex has retinotopic organization23 although the precise nature of that organization has remained a topic of vigorous debate. Similarly the

motion-responsive region V5/MT, although smaller, also appears to contain visual eld maps (e.g. see reference 24).

Functional specialization is not restricted to simple features of visual scenes such as colour and motion, and subsequent investiga- tion has revealed specialization for the categories of visual objects (see reference 25 for a review and Fig. 6.4 for a summary). Anterior and lateral to early retinotopic cortices lie areas that respond more strongly when healthy humans view pictures of objects compared to scrambled objects or textures.26 Such object-selective areas are particularly centred in lateral occipital cortex (LOC) where a large area demonstrates relatively non-speci c responses to all types of objects. Damage focused on this region, such as that seen in patient DF,27 can be associated with visual agnosia. Also, close to area V5/ MT is a cortical region whose responses show selectivity for visu- ally presented body parts.28 is ‘extrastriate body area’ appears to play a causal role in perceiving people in real-world scenes, as transient inactivation of the area with transcranial magnetic stim- ulation causes impairments in tasks that require identi cation of people (compared to cars) in visually presented scenes.29

In contrast, more ventrally in occipital (and occipito-temporal) cortex lie regions that appear to be selective for particularly types of object such as faces30 or houses and scenes of particular places. Similarly, damage to this region is associated with di culties in discriminating the spatial con guration of di erent elements of a face,32 as well as the association of prosopagnosia with more medial temporo-occipital lesions close to regions also showing face-selective responses. ere are also more dorsal object-selective regions along the transverse occipital sulcus thought to be involved in the context of grasping and object manipulation whose func- tional role is less well understood (e.g. see reference 33). Selectivity of this kind for visual responses appears to be remarkably robust. Even following bilateral destruction of primary visual cortices (and accompanying cortical blindness), some measure of selec- tive responses to faces and body parts remains in di erent cortical regions.34 is indicates that the inputs from which such selectivity derive come not just from early retinotopic visual cortices but also from subcortical pathways.





Sagittal Coronal


Fig. 6.3 Functional specialization. Responses to moving and coloured stimuli, relative to control stimuli that lack motion or colour, produce distinct spatial patterns of activation in occipital cortex. (a) Activity in the brain measured using PET when participants view a coloured Mondrian (inset) compared to a grey Mondrian is seen on the left ventral occipital surface. Activated regions are projected onto a ‘glass brain’ in sagittal, coronal, and tranverse sections. (b) Similar plotting conventions are used to display regions in lateral occipital cortex that respond more strongly when participants view moving random dots compared to static dots. Note that earlier visual cortical areas (see Fig. 6.2) are not activated in these comparisons because they respond roughly equally to both moving and static dots, thus indicating the selectivity of visual areas later in the anatomical hierarchy.

Adapted from J Neurosci. 11(3), Zeki S, Watson JD, Lueck CJ, et al. A direct demonstration of functional specialization in human visual cortex, pp. 641–9, Copyright (1991), with permission from the Society for Neuroscience.





Fig. 6.4 Object-selective areas in the human occipital lobe. is gure summarizes a number of di erent studies that have used functional MRI to describe di erent areas in human occipital cortex and adjoining areas that respond selectively to di erent types of objects. e colour code indicates the type of object that an area responds to and the colours are overlaid on either computationally ‘in ated’ lateral or ventral views of the left hemisphere, or a left hemisphere that has been computationally ‘cut’ and ‘ attened’. e early visual areas V1–V3 (see Fig. 6.2 and text) are not selective for particular objects or object classes, but the lateral occipital (LO) area is selective for objects, the fusiform face area (FFA) for faces, and the parahippocampal place area (PPA) for places. Reproduced from Annu Rev Neurosci. 27, Grill-Spector K and Malach R, e human visual cortex, pp. 649–77, Copyright (2004), with permission from Annual Reviews.

Organizational principles of occipital cortex

We have already seen that there are two dominant features of the functional organization of the occipital cortex in humans that correspond to clinical observations following occipital damage. e rst is functional specialization; di erent areas process di er- ent aspects of the visual scene, and so focal cortical damage can produce remarkably speci c de cits in visual perception as well as more general disorders of object vision such as agnosia. e sec- ond is that most occipital regions contain a multiplicity of topo- graphic maps of the visual eld, and even functionally specialized regions are o en also topographically mapped. us focal damage, particular to early cortical regions V1–V3, produces visual de cits that are mapped to the corresponding region of the visual eld, but are there any more general organizing principles that govern the relationship between all these visual eld maps and functionally specialized areas?

e patterns of anatomical connectivity between di erent regions have been proposed as one way to uncover organizational principles, in particular distinguishing between feed-forward and feed-back connections established through anatomical bre trac- ing in monkeys. is suggested a hierarchical organization of visual cortex based on anatomy (see reference 35; Fig. 6.5). One


in uential framework proposes that visual cortical areas within this anatomical hierarchy are segregated into dorsal and ventral process- ing streams.36

Ungerleider and Mishkin observed that lesions to inferotempo- ral cortex in monkey led to de cits in their ability to distinguish between di erent visual objects on the basis of their appearance, but did not a ect their performance on a task that required knowl- edge only of the spatial locations of di erent objects. Conversely, posterior parietal cortex lesions produced de cits in tasks requir- ing knowledge of spatial relations but not on visual discrimination tasks. ey thus proposed that the anatomical distinction between dorsal and ventral streams is mirrored in a simple distinction between spatial and object vision—‘where’ and ‘what’ respectively (Fig. 6.6).

e simple distinction that Ungerleider and Mishkin made between ‘what’ and ‘where’ has become progressively more com- plicated as clinical syndromes have been more fully considered. For example, damage to the human parietal cortex can lead to optic ataxia where patients have di culty reaching and grasping objects placed in the contralateral visual eld. However, such patients also have di culties with aspects of vision less obviously spatial, such as the size and shape of objects they are able to grasp correctly.37 is, and other observations, has led to proposals38 that the functional distinction between dorsal and ventral streams may re ect a sub- tler distinction between a system that uses visual information for skilled action (‘vision for action’—the dorsal stream) and ‘vision- for-perception’ (ventral stream). More broadly, it is recognized that even with such functional distinctions, coordinated and goal- directed action requires the integrated operation of both streams.

Such schemes have proven very useful heuristically in terms of understanding and integrating a large amount of neuroscien- ti c data on the occipital lobe, but in isolation they cannot always tell the whole story. For example, while an anatomical hierarchy is apparent,35 it is equally clear that signals from the retina reach di erent points in the anatomical hierarchy and at di erent times, which do not always correspond.39 us some areas ‘higher’ in the proposed anatomical hierarchy might receive signals earlier than other areas apparently ‘lower’ in the hierarchy. In the context of a highly dynamic system where signals associated with visual per- ception pass backwards and forwards,40 the idea of a simple linear progression of stages of the analysis of a visual scene is likely to be an oversimpli cation.

Comparisons between humans

and other species

e existence of visually responsive areas in the occipital lobe of non-human primates has been known for over a century,1 and pio- neering work using single unit electrophysiology (see e.g. reference 41) delineated many of the principles of functional specialization at the level of single neurons that have subsequently been elaborated and elucidated using functional imaging techniques in humans. Combining electrophysiology with other tools including cytoarchi- tectural and anatomical connectivity analyses has led to the parcel- lation of extra striate cortex in non-human primate into a number of di erent visual areas. More recently it has been possible to use functional MRI (fMRI) methods in both humans and non-human primates to compare the organization of visual maps (see e.g. ref- erence 42) and functionally specialized regions (e.g. reference 43).

CHAPTER 6 the occipital lobes 63


Objects, place, & faces Faces & objects Places & objects Objects Faces Places


normal cognitive function

7b VIP











36 46 TF TH






M V1 P-B P-I



Fig. 6.5 Possible organizational principles. is proposed ‘circuit diagram’ from Felleman and Van Essen illustrates how 32 di erent cortical areas responding to visual stimulation in the macaque are connected anatomically, and sets out a proposed hierarchy of areas.
Reproduced from Cereb Cortex. 1(1), Felleman DJ and Van Essen DC, Distributed hierarchical processing in the primate cerebral cortex, pp. 1–47, Copyright (1991), with permission from Oxford University Press.

While there are strong similarities across species, it has also become increasingly apparent that there are important di erences. For example, topographic maps in humans are substantially larger than in macaque; and homology of areas beyond V1–V3 and V5/MT is signi cantly more di cult to establish with clarity.

Cytoarchitecture of human occipital cortex

is chapter has focused on relatively macroscopic measurements of occipital lobe structure and function, and how they correspond to clinicopathological syndromes following brain damage. However, it has also been known for over a century that the detailed histo- logical structure—the cytoarchitecture and myeloarchitecture—of the human brain di ers across the cortical surface. is led to the publication of classic cytoarchitectonic maps of the human cerebral cortex (e.g. reference 44), and in particular the distinction between striate and extra striate cortex touched upon above. More recently there has been substantial progress in the computerized image

analysis of histological specimens and the introduction of markers that re ect di erent architectonic aspects of cortical organization (such as receptor autoradiography). Together with developments in image analysis techniques that allow for inter-subject variabil- ity in macroscopic anatomy, this has enabled new insights into the detailed structure of human visual cortex.45 For example, probabil- istic cytoarchitectonic maps are now available of occipital cortex.46 Signals obtained from structural MRI sequences, including high- resolution MRI, re ect the myeloarchitecture and cytoarchitecture found in histological sections (e.g. reference 47) which has led to renewed interest in using structural MRI to identify speci c regions of human visual cortex such as V5/MT (e.g. reference 48).

Individual variability in human occipital

cortex anatomy

Most investigations of the occipital lobe focus on the common- alities in structure and function across individuals and how these



CHAPTER 6 the occipital lobes 65


Posterior Parietal Cortex








Primary Visual Cortex




Fig. 6.6 Schematic illustration of how visual signals from the retina reach dorsal and ventral processing streams. e dorsal and ventral pathways are schematically illustrated on an outline of a macaque monkey brain, but the organizational principles are broadly consistent in humans. e broad functional distinction between dorsal and ventral streams may re ect the use of visual information for action (dorsal stream) or perception (ventral stream) but goal-directed action usually requires the coordinated action of both streams.

Reproduced from Goodale M and Milner D, e Visual Brain in Action, Copyright (1995), with permission from Oxford University Press.

di er following brain damage, but it has long been noted informally that the precise sulcal and gyral anatomy can vary somewhat across individuals [e.g. Fig. 6.7]. For example, while there are regularities, such as the position of the calcarine sulcus running anteriorly from the occipital pole, the precise direction and shape of the sulcus var- ies across individuals (e.g. reference 49). Similarly, at a histologi- cal level, the architectonic features that delineate striate (primary) visual cortex extend for a variable distance above and below the calcarine sulcus, presumably accounting for the variability that can be observed macroscopically in non-invasive estimates of the spa- tial extent of primary visual cortex [Fig. 6.7].

Indeed, in normal human subjects the range of interindividual variation in V1 area is approximately threefold.50 Importantly, this variability in V1 area in humans is correlated with the cross- sectional area of the optic tract and the volumes of the magno- cellular and parvoceullar layers of the lateral geniculate nucleus (reference 51; Fig. 6.7). is coordinated variation indicates that development of the di erent parts of the human visual system are interdependent. Notably, the range of variability in the size of these visual system components is substantially greater than the variabil- ity of the overall size of the human brain, which is about 30 per cent.52 It has been suggested that such coordinated variation in size might be associated with di erences in visual ability across indi- viduals, and this has recently become the focus of renewed investi- gation (see reference 53 for a review).

One recent investigation studied how variability in cortical mag- ni cation and overall size of V1 was related to ne visual acuity. Individuals with a larger overall cortical area in V1 had lower over- all Vernier acuity thresholds; they were able to make ner percep- tual judgements.54 is relationship between objective measures of visual perception and individual di erences in visual cortex size extends also to the subjective qualities of visual perception. Although it is di cult to compare the subjective visual experi- ences of di erent people directly, inter-individual di erences in the perceived strength of a perceptual illusion—whereby physically

160 150

140 130

120 110 100


(b) RFD




11 10

9 8

7 6

Infero- temporal Cortex





Fig. 6.7 Individual variability. (a) Each point represents data from a single post- mortem human. ere is correlated variability in the surface area of the primary visual cortex (V1), the volume of the lateral geniculate nucleus and the surface area of the optic tract. Note the variation of almost twofold in the surface area of primary visual cortex across individuals. (b) ree example right hemispheres in which the central 2–12 degrees of the visual eld representation in V1–V3 have been mapped. While in each individual the macroscopic concentric organization of V1–V3 demonstrated in Fig. 6.2 is apparent, there is also substantial individual variability in the surface area of V1 (magenta), V2 (cyan), and V3 (red).

(a) Reproduced from J Neurosci. 17(8), Andrews TJ et al. Correlated size variations in human visual cortex, lateral geniculate nucleus, and optic tract, pp. 2859–68, Copyright (1997), with permission from the Society for Neuroscience. (b) Reproduced from J Vision. 3(10), Dougherty et al. Visual eld representations and locations of visual areas V1/2/3 in human visual cortex, pp. 586–98, Copyright (2003), with permission from the Association for Research in Vision and Ophthalmology.

identical stimuli produce perceptually different appearances depending on their local context—can be quantitatively compared. In a study that compared individuals’ susceptibility to geometri- cal visual illusions (the Ponzo and Ebbinghaus illusions), just such variability in illusion strength was found.55 Moreover, the strength of the illusion correlated negatively with the size of early retinotopic visual area V1, but not visual area V2 and visual area V3.


e fundamental organization and the macroscopic anatomy that gives rise to clinicopathological correlations between brain damage and visual behaviour have been known in outline for over a cen- tury. However, recent advances in brain imaging technology and the ability to integrate information from many di erent sources has led to dramatic advances in our understanding of the relationship




Dorsal Stream

LGN volume (mm3)

Ventral Stream

Optic Tract (mm2)

VI area (mm2)

66 SECTION 1 normal cognitive function

between structure and function in the human visual system. is in turn clari es the anatomical basis for many clinical syndromes but also lays the foundation for a mechanistic understanding of the relationship between structure, function, and the e ects of damage to the human visual system.


1. Munk H. Über die Functionen der Grosshirnrinde. Hirschwald, Berlin, 1881.

2. Henschen S. Klinische und Anatomische Beiträge zur Pathologie des Gehirns (Pt 1). Almquist & Wiksell, Upsala, 1890.

3. Inouye T. (1909) Die Sehstörungen bei Schssverletzungen der Kortikalen Sehsphäre nach Beobachtungen an Verwundeten der Letzten Japanischen Kriege, W. Engelmann (English trans.); visual disturbances following gunshot wounds of the cortical visual area. Brain (Suppl). 2000;123.

4. Holmes G and Lister WT (1916) Disturbances of vision from cerebral lesions, with special reference to the cortical representation of the macula. Brain. 1916;39:34–73.

5. Belliveau JW, Kennedy DN Jr, McKinstry RC, et al. Functional mapping of the human visual cortex by magnetic resonance imaging. Science. 1991;254(5032):716–9.

6. DeYoe EA, Carman GJ, Bandettini P, et al. Mapping striate and extras- triate visual areas in human cerebral cortex. Proc Natl Acad Sci USA. 1996;93:2382–6.

7. Engel SA, Rumelhart DE, Wandell BA, et al. fMRI of human visual cortex. Nature. 1994;369:525.

8. Sereno MI, Dale AM, Reppas JB, et al. Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science. 1995;268:889–93.

9. Horton JC and Hoyt WF. Quadrantic visual eld defects. A hallmark of lesions in extrastriate (V2/V3) cortex. Brain. 1991;114 (Pt 4):1703–18.

10. Anton G. Herderkrankungen des Gehirnes, welche vom Patienten selbst nicht wahrgenommen werden. Wiener klinische Wochenschri . 1898;11;227–9.

11. Prigatano G and Schacter DL (eds). Awareness of De cit a er Brain Injury. Oxford: Oxford University Press, 1991.

12. McDaniel KDK and McDaniel LD. Anton’s Syndrome in a Patient With Posttraumatic Optic Neuropathy and Bifrontal Contusions Arch Neurol. 1991;48(1):101–05. doi:10.1001/ archneur.1991.00530130113028.

13. Wandell BA and Winawer J. Imaging retinotopic maps in the human brain. Vision Res. 2011;51(7):718–37. doi:10.1016/j.visres.2010.08.004. Epub 6 August 2010.

14. Sereno MI and Huang RS. Multisensory maps in parietal cortex. Curr Opin Neurobiol. 2014;24(1):39–46. doi:10.1016/j.conb.2013.08.014.

15. Ho mann MB, Tolhurst DJ, Moore AT, et al. Organization of the visual cortex in human albinism. J Neurosci. 2003;23(26):8921–30.

16. Victor JD, Apkarian P, Hirsch J, et al. Visual function and brain organi- zation in non-decussating retinal-fugal bre syndrome. Cereb Cortex. 2000;10(1):2–22.

17. Yacoub E, Harel N, and Ugurbil K. High- eld fMRI unveils orientation columns in humans. Proc Natl Acad Sci USA. 2008;105(30):10607–12. doi:10.1073/pnas.0804110105. Epub 18 July 2008.

18. McDonald I. Gordon Holmes and the neurological heritage. Brain. 2006;130(1), 288–98.

19. Meadows JC. Disturbed perception of colours associated with localised cerebral lesions. Brain. 1974;97:615–32.

20. Zihl J, von Cramon D, and Mai N. Selective disturbance of movement vision a er bilateral brain damage. Brain. 1983;106:313–40.

21. Lueck CJ, Zeki S, Friston KJ, et al. e colour centre in the cerebral cortex of man. Nature. 1989;340(6232):386:3863.

22. Zeki SM, Watson JD, Lueck CJ, et al. A direct demonstration of functional specialization in human visual cortex. J Neurosci. 1991;11(3):641–9.

23. McKeefry DJ and Zeki S. e position and topography of the human colour centre as revealed by functional magnetic resonance imaging. Brain. 1997;120(12): 2229–42.

24. Amano K, Wandell BA, and Dumoulin SO. Visual eld maps, popula- tion receptive eld sizes, and visual eld coverage in the human MT+ complex. J Neurophysiol. 2009;102(5):2704–18.

25. Grill-Spector K and Malach R. e human visual cortex. Annu Rev Neurosci. 2004;27:649–77.

26. Malach R, Reppas JB, Benson RR, et al. Object-related activity revealed by functional magnetic resonance imaging in human occipital cortex. Proc Natl Acad Sci USA. 1995 Aug 29;92(18):8135–9.

27. Bridge H, omas OM, Minini L, et al. Structural and Functional Changes across the Visual Cortex of a Patient with Visual Form Agnosia. J Neurosci. 2013;33(31):12779–91.

28. Downing PE, Jiang Y, Shuman M, et al. A cortical area selective for visual processing of the human body. Science 2001;293:2470–3.

29. van Koningsbruggen MG, Peelen MV, and Downing PE. A causal role for the extrastriate body area in detecting people in real-world scenes. J Neurosci. 2013;17;33(16):7003–10.

30. Kanwisher N, McDermott J, and Chun MM. e fusiform face
area: A module in human extrastriate cortex specialized for face percep- tion. J Neurosci. 1997 Jun 1;17(11):4302–11.

31. Epstein R, Harris A, Stanley D, et al. e parahippocampal place area: Recognition, navigation, or encoding? Neuron. 1999 May;23(1):115–25.

32. Barton JJ, Press DZ, Keenan JP, et al. Lesions of the fusiform face area impair perception of facial con guration in prosopagnosia. Neurology. 2002 Jan 8;58(1):71–8.

33. Culham JC and Valyear KF. Human parietal cortex in action. Curr Opin Neurobiol. 2006 16(2):205–12.

34. Van den Stock J, Tamietto M, Zhan M, et al. Neural correlates of body and face perception following bilateral destruction of the primary visual cortices. Front Behav Neurosci. 2014 Feb 13;8:30. doi:10.3389/ fnbeh.2014.00030. eCollection 2014.

35. Felleman DJ and Van Essen DC. Distributed hierarchical processing in the primate cerebral cortex. Cereb Cortex. 1991;1(1):1–47.

36. Ungerleider LG and Mishkin M. Two Cortical Visual Systems. In: MA Goodale and AD Milner (eds). e Analysis of Visual Behavior. Cambridge: Cambridge University Pess, 1982, pp. 549–86.

37. Perenin M -T and Vighetto A. Optic ataxia: A speci c disruption in visuomotor mechanisms. 1. Di erent aspects of the de cit in reaching for objects. Brain. 1988;111:643–74.

38. Goodale MA and Milner AD. Separate visual pathways for perception and action. Trends Neurosci. 1992;15(1):20–5.

39. Schmolesky MT, Wang Y, Hanes DP, et al. Signal timing Across the Macaque Visual System. J Neurophysiol. 1988;79:3272–8.

40. Lamme VAF and Roelfsema PR. e distinct modes of vision o ered by feed-forward and recurrent progressing. Trends Neurosci. 2000;23(11):571–9.

41. Hubel DH and Wiesel TN. Functional architecture of macaque visual cortex. Proc. Roy Soc Ser B. 1977;198:1–59.

42. Brewer AA, Press WA, Logothetis NK, et al. Visual areas in macaque cortex measured using functional magnetic resonance imaging.
J Neurosci. 2002;22(23):10416–26.

43. Tsao DY, Freiwald WA, Tootell RB, et al. A cortical region consisting entirely of face-selective cells. Science. 2006;311(5761):670–4.

44. Brodmann K. Vegleichende Lokalisationslehre der Grosshirnde. Leipzig: Barth, 1909.

45. Amunts K, Schleicher A, and Zilles K. Cytoarchitecture of the cerebral cortex—More than localisation. Neuroimage. 2007;37:1061–5.

46. Amunts K, Malikovic A, Mohlberg H, et al. Brodmann’s areas 17 and 18 brought into stereotaxic space Where and how variable? Neuroimage. 2000;11:66–84.

47. Eickho S, Walters NB, Schleicher A, et al. High-resolution MRI re ects myeloarchitecture and cytoarchitecture of human cerebral cortex. Hum Brain Mapp. 2005;24(3):206–15.

48. Walters NB, Egan GF, Kril JJ, et al. In vivo identi cation of human corti- cal areas using high-resolution MRI: an approach to cerebral structure- function correlation. Proc Natl Acad Sci USA. 2003;100(5):2981–6. Epub 24 February 2003.

49. Iaria G and Petrides M. Occipital sulci of the human brain: variability and probability maps. Journ Comp Neurol. 2007;501:243–59.

50. Stensaas SS, Eddington DK, and Dobelle WH. e topography and variability of the primary visual cortex in man. J Neurosurg. 1974;40:747–55.

51. Andrews TJ, Halpern SD, and Purves D. Correlated Size Variations in Human Visual Cortex, Lateral Geniculate Nucleus and Optic Tract.
J Neurosci. 1997;17(8), 2859–68.

52. Boyd R. Tables of the weights of the human body and internal organs in the sane and insane of both sexes at various ages arranged from 2614 post-mortem examinations. Philos Trans. 1861;1:249–53.

53. Kanai R and Rees G. e structural basis of inter-individual dif- ferences in human behaviour and cognition. Nature Neurosci. 2011;12:231–42.

54. Duncan RO and Boynton GM. Cortical Magni cation within Human Primary Visual Cortex Correlates with Acuity resholds. Neuron. 2003;38:659–71.

55. Schwarzkopf DS, Song C, and Rees G. e surface area of human V1 predicts the subjective experience of object size. Nature Neurosci. 2011;14:28–30.

CHAPTER 6 the occipital lobes 67


e basal ganglia
in cognitive disorders
James Rowe and Timothy Rittman


e basal ganglia are a vital set of forebrain nuclei, richly connected with the cortex, thalamus, and brainstem. As one of the oldest parts of the brain in evolutionary terms, it is not surprising that neuro- logical disease a ecting the basal ganglia has severe consequences for behaviour and cognition. In this chapter, we review the princi- ples underlying the anatomy and connectivity of the basal ganglia because they illuminate the myriad clinical features of basal ganglia dysfunction across a broad range of disorders.

omas Willis is credited with the rst description of the ‘cor- pora striata’ in 1664, correctly identifying their role in movement but also suggesting they receive sensory information. A century ago, Kinnier Wilson suggested that the basal ganglia were mainly concerned with inhibiting signals from the motor cortex.1 Further work suggested the basal ganglia act as a ‘funnel’ for messages from motor association cortex, integrating information for delivery via the ventrolateral thalamus to motor cortex.2 e idea that the basal ganglia were primarily concerned with motor function remained largely unchallenged until the 1980s. is motor chauvinism was reinforced by the false impression that signi cant cognitive impair- ment was uncommon in Parkinson’s disease, whereas it is now rec- ognized as a common and early feature of the disease.3

e basal ganglia are central to the understanding and treat- ment of many cognitive disorders, some of which are associated with movement disorders (e.g. akinetic rigidity, tremor, dystonia, and chorea). e separation of cognitive and movement disorders is arti cial but still common in didactic teaching of neurology and neuroscience, contrary to the clinical evidence and functional anatomy of the basal ganglia. For example, dementias such as frontotemporal dementia (FTD) and dementia with Lewy bodies (DLB) are o en associated with extrapyramidal motor dysfunc- tion, and many diseases cause a syndrome in which cognitive and motor de cits have similar weighting, such as Huntington’s disease (HD), progressive supranuclear palsy (PSP), corticobasal degen- eration (CBD), neurodegeneration with brain iron accumulation, paediatric autoimmune neurological disorders associated with streptococci and encephalitis lethargica. Psychiatric disorders of addiction, obsessive–compulsive disorders and impulsivity are also associated with basal ganglia dysfunction and cognitive abnormali- ties, but lie outside the scope of this chapter.

e diversity of clinical disorders and cognitive functions associ- ated with the basal ganglia re ects their unique functional anatomy and neurochemistry. We will rst review the normal gross anatomy

of the basal ganglia, and examine how this supports both integra- tion and segregation of cognitive processes. We then consider the neurochemical organization and connectivity of the basal ganglia. Finally, we show how the basal ganglia contribute to cognitive dis- orders, revealed by neuropsychology, and structural and functional brain imaging.

Macroscopic anatomy

e macroscopic organization of the basal ganglia is intimately con- nected with that of the cortex and thalamus. e principal input nucleus is the striatum, comprising the caudate and putamen (see Fig. 7.1), but the subthalamic nucleus also receives direct cortical inputs. e striatum projects to the globus palludus (also called the pallidum) which has two parts: internal and external. e substan- tia nigra and the subthalamic nuclei are smaller but critical nuclei in the basal ganglia complex. e inputs, connections, and outputs of these basal ganglia nuclei are arranged in a series of cortico- striato-thalamo-cortical loops, with gross structural homologies (Fig. 7.2). Studies injecting tracers, for example in premotor regions, rst suggested a cognitive role for the basal ganglia by revealing connections from the pallidum via the thalamus to premotor cor- tex.4,5 ese connections were reciprocal, in a closed-loop system that could facilitate feedback from the basal ganglia to association cortex.6 Further closed-loop systems were identi ed, suggestive of distinct motor, oculomotor, cognitive, and limbic functions.

At rst glance, these loops suggest separate parallel processing of information by subdomains of the basal ganglia (Fig. 7.2). For example, the ventral striatum receives input from the orbital and medial prefrontal cortex and anterior cingulate. is loop is closely associated with reward, motivation, and reinforcement in a lim- bic system, with the clinical counterparts of apathy, learning de – cits, addiction, and cognitive in exibility. In contrast, the central regions of the striatum receive their main input from dorsolateral prefrontal cortex, forming a loop that has been linked to associative and executive functions underlying adaptive behaviours (e.g. plan- ning, set-shi ing, and working memory). Topographical mapping in the caudate preserves the di erences between projections from, for example, dorsolateral cortical prefrontal areas 9, 46, and sup- plementary eye elds. e dorsal components form a further loop with inputs from premotor and motor cortex, and are most closely associated with motor control and action selection. e early dys- executive syndrome in Parkinson’s disease3,7 is likely to re ect dys- function of this associative (cognitive) loop.

70 SECTION 1 normal cognitive function

Fig. 7.1 e top left panel illustrates the relative size and position of the principal basal ganglia in the rat, connecting cortex via the striatum to the globus pallidus (with external part, Gpe, and internal part, GPi), subthalamic nucleus (STN), and substantia nigra pars reticulata (SNpr) and thalamus (T). Dopaminergic innervation of the striatum is from the ventral tegmental area (VTA) and substantia nigra pars compacta (SNpc). e other three panels illustrate the equivalent structures in an adult human brain on a structural magnetic resonance image in axial, saggital, and coronal sections and distinguishing the caudate (C) and putamen (P) that make up the striatum.

Human structural and functional neuroimaging con rms this functional anatomy. For example, di usion-weighted magnetic resonance imaging (MRI) with tractography identi es the major corticostriatal pathways,8 with limbic, associative, and motor pathways between cortex, striatum, and substantia nigra (and the adjacent ventral tegmental area of dopaminergic neurons). In addi- tion, meta-analysis of PET imaging identi es analogous functional loops.9 More recently, detailed analysis for the functional connec- tivity patterns of individual basal ganglia structures has been pos- sible using seed-based connectivity in functional MRI scans.10

Despite the apparent parallel organization of these loops, they are not wholly segregated. Indeed, it is a priori necessary for limbic, associative, and motor systems to interact to enable goal-directed behaviours that develop or adapt appropriate responses, essential for tasks such as rule learning.

A revised model of basal ganglia function has been developed that proposes multiple mechanisms of interaction (Fig. 7.3). First, the axonal projections from cortex to the striatum can cross between limbic and associative areas, or between associative and motor areas, facilitating cross-talk between systems. us, the general topogra- phy outlined above has so boundaries. In addition, adjacent corti- cal areas project on to smaller and partially overlapping basal ganglia regions so that there is approximately a ten-to-one reduction in the

number of neurons receiving input in the basal ganglia. e onward projections back to the cortex terminate in wide terminal elds sug- gesting important processing and integration of information as it ows through the basal ganglia. Finally, the reciprocal connections between basal ganglia structures are not symmetric.11 is asymme- try promotes a directional ow from limbic to associative to motor regions. Together, these mechanisms enable both segregation and integration of cognitive, motor, sensory, and a ective information as it passes through the basal ganglia.

Connectivity within the basal

ganglia: Direct and indirect pathways

Medium spiny neurons predominate in the striatum, making up 95 per cent of rat striatal neurons.12 ey receive the bulk of gluta- matergic cortical inputs, and are the main striatal output cell, with GABAergic projections. Medium spiny neurons are densely den- dritic, synapsing with other medium spiny neurons and interneu- rons within the striatum to create a complex internal structure. ere is considerable plasticity within this densely connected network, arising from spike-timing-dependent processes that are dependent on glutamatergic NMDA receptors and the presence of dopamine receptor activation.13

Generic pattern



Pallidum/ nigra

alamic nuclei




Vl-Gpi cl-SNr





cdm-Gpi vl-SNr


Cognitive (associative)


Dorsal Caudate

Idm-Gpi rlSNr


Limbic (o)


Ventromedial Caudate

mdm-Gpi rm-SNr

VAmc MDmc

Limbic (a)


Ventral Striatum

rl-Gpi rd-SNr


CHAPTER 7 the basal ganglia in cognitive disorders 71

Fig. 7.2 e cortico-striato-thalamo-cortical loops follow a generic pattern (left), which is mirrored in parallel motor, oculomotor, cognitive, and limbic circuits.4 Functional di erences are related to the speci c subregions of cortex, striatum, pallidum, nigra, and thalamus. Note that this model of basal ganglia connectivity emphasizes segregated information processing within each of the parallel loops. SMA, supplementary motor area; FEF, frontal eye elds; DLPFC, dorsolateral prefrontal cortex; OFC, orbitofrontal cortex; ACC, anterior cingulate cortex; Gpi, globus pallidus internal; SNr, substantia nigra pars reticulata; and thalamic nuclei including ventrolateral, VL, ventral anterior, VA, mediodorsal, MD.

Reproduced from Prog Brain Res., 85, Alexander GE, Crutcher MD, DeLong MR, Basal ganglia-thalamocortical circuits: parallel substrates for motor, oculomotor, ‘prefrontal’ and ‘limbic’ functions, pp. 119–46, Copyright (1991), with permission from Elsevier.

e striatum is the main receiving centre of the basal ganglia, but it has complex projections to other parts of the basal ganglia, and on to thalamus and cortex. e ‘dual circuit’ model (also called the ‘rate’ model, or ‘Albin DeLong’ model: see Fig. 7.4) has been highly in uential in clinical and pre-clinical analyses of basal ganglia function since the early 1990s. In this model, GABAergic outputs from the striatum form two main pathways which are associated with two types of dopaminergic neurones.

e direct pathway contains medium spiny neurons with pre- dominant dopamine D1 receptors, which in response to gluta- matergic cortical inputs and dopaminergic inputs from substantia nigra pars compacta (or ventral tegmental area, VTA) send inhibi- tory GABAergic projections directly to the globus pallidus interna and substantia nigra pars reticulata, which in turn send inhibitory connections to the thalamus.

e indirect pathway’s medium spiny neurons have dopamine D2 receptors and send inhibitory projections to the globus pallidum externa, with onward inhibitory projections to the subthalamic nucleus. e subthalamic nucleus’ projections to the globus palli- dus interna and substantia nigra are excitatory. e result is antago- nism between the direct and indirect pathways. In the motor loop, the direct pathway promotes movement and the indirect pathway inhibits movement, with analogous regulation of cognitive tasks in the cognitive (associative) loop and reward or punishment tasks in the limbic (a ective) loop.

is dual-circuit model explains many experimental ndings and clinical phenomena. For example, stimulation of D2 receptors preferentially expressed in the indirect pathway enhances activ- ity in the external segment of the globus pallidus, inducing a net decrease in basal ganglia output. Conversely, loss of dopamine increases inhibitory output of the basal ganglia, and inhibition of thalamocortical activity. However, new anatomical, transgenic,

and optogenetic investigations suggest a much more complex set of interactions within and even between the direct and indirect pathways (Fig. 7.4). It becomes once again much more di cult to predict the input–output function of the system. Moreover, recent evidence suggests coordination through transient co-activation of the direct and indirect pathways, rather than simple antagonism,14 with heteromeric D1–D2 receptors and at best partial separation of D1 and D2 striatal projections to internal and external segments of the globus pallidus.15 Nonetheless, the dual-circuit model remains a useful starting point for understanding the functional anatomy of the basal ganglia and the cognitive consequences of basal ganglia disorders.

Dopaminergic neurons of the substantia nigra and VTA project to the striatum and pallidum. e ring rate of these dopaminergic cells is not uniform: their background ‘tonic’ ring rate is supple- mented by brief ‘phasic’ bursts of ring. e phasic dopaminergic signal is critical for cognitive function as it signals a prediction error in the brain. For example, animal studies show that an unex- pected reward leads to phasic activity in dopaminergic projections to the striatum which gradually diminishes if the animal can learn to predict the reward.16 Phasic reductions of ring can also occur if, for example, an expected reward is omitted or delayed. is dopa- minergic signal is fundamental to learning, memory, the control of attention, and switching between behavioural strategies in response to environmental or internal feedback. Tonic ring rates a ect the signal-to-noise for phasic ring: pharmacological enhancement of tonic dopaminergic ring might therefore paradoxically attenuate the behavioural bene ts of dopamine dependent phasic rewards (reduced signal-to-noise) or phasic punishments.17

An interesting corollary of phasic dopaminergic responses is that they may contribute to the sense of agency (the sense that we control our own actions) which is a ected by many neurological diseases.18

72 SECTION 1 normal cognitive function

Fig. 7.3 Cortico-striatal and striato-nigral projections are not entirely parallel or fully segregated, but instead introduce cross-talk between a ective, cognitive, and motor pathways. Striato-nigral projections illustrated here broadly follow a rostrocaudal gradient according to function (red = limbic, green = associative, blue = motor). As part of an a ective loop, the accumbens shell (S) receives input from the amygdala, hippocampus, and orbitofrontal cortex; the accumbens core receives input from orbitomedial prefrontal cortex (OMPFC); as part of the cognitive loop, the dorsolateral prefrontal cortex (DLPFC) projects to the central striatum while as part of the motor loop premotor and motor cortex project to the dorsolateral striatum. Midbrain projections from the shell target both the ventral tegmental area (VTA) and ventromedial SNc (inset, red arrows). Midbrain projections from the VTA to the shell form a ‘closed’, loop (red arrow). Projections from the medial substantia nigra project to the core to form the rst part of a spiral (orange arrow). e spiral of connectivity continues through the adjacent loops, illustrated by the yellow, green,

and blue arrows. e magni ed inset oval region shows the synaptic interactions in reciprocal loops: the reciprocal component terminates directly on a dopamine cell, resulting in inhibition, while the feedforward component terminates indirectly on a dopamine cell via a GABAergic interneuron (brown). is leads to disinhibition and facilitation of dopaminergic cell burst ring. IC, internal capsule; SNc, substantia nigra, pars compacta; SNr, substantia nigra, pars reticulata.
Reproduced from J Neurosci., 20(6), Haber SN, Fudge JL, McFarland NR, Striatonigrostriatal pathways in primates form an ascending spiral from the shell to the dorsolateral striatum, pp. 2369–82, Copyright (2000), with permission from the Society for Neuroscience.

Whether a sensory event is perceived as being casued by one’s own action as the ‘agent’ or perceived as externally caused depends on the harmony or discrepancy between sensory information and the sensory predictions made from precise internal models of the consequences of one’s own actions.19,20 Dopaminergic drugs and basal ganglia disorders such as Parkinson’s disease and corticobasal degeneration a ect the sense of agency, for example with alien limb phenomena.21,22 Before reviewing the e ects of such neurodegen- erative disorders in detail, we turn next to the neuropsychological consequences of focal lesions to the basal ganglia.

Lesions of the basal ganglia

Ischaemic strokes, haemorrhage, tumours, and focal necrotic, met- abolic, or immunological responses can lead to selective damage of basal ganglia nuclei, unilaterally or bilaterally. Motor syndromes

have been widely described, such as hemiballismus a er subtha- lamic nucleus stroke, and hemidystonia or hemi-parkinsonism a er striatal lesions. However, cognitive syndromes and personal- ity change are under-recognized in clinical practice. Many patients with basal ganglia lesions have signi cant and long-lasting cogni- tive change.23

e cognitive and behavioural e ects of basal ganglia lesions should not be seen as mere disconnection of the cortical regions from which they receive a erents. Although there are o en marked similarities between the e ect of a cortical lesion and lesion of the part of the basal ganglia to which it projects, the basal ganglia are not passive conduits: the integration and compression of informa- tion through cortico-striato-thalamo-cortical loops, and the dis- tinct pharmacology of the basal ganglia mean that basal ganglia lesions o en have very widespread e ects. Given the close proxim- ity of functionally distinct circuits, and the heterogeneity of lesions,


D1 D2



SNc VTA Inhibitory (GABA)

CHAPTER 7 the basal ganglia in cognitive disorders 73 Cortex





Fig. 7.4 e left panel illustrates the in uential ‘dual circuit model’, in which the output of the basal ganglia is determined by the balance between the direct pathway, with striatonigral inhibitory connections that promote behaviour, and the indirect pathway, via the external globus pallidus (GPe) and subthalamic nucleus (STN), that suppress behaviour. e balance between these two pathways is modulated by dopaminergic inputs from the substantia nigra pars compacta (SNc) and the ventral tegmental area (VTA), which act on D1 and D2 dopamine receptors that are di erentially expressed in the direct and indirect pathways. e right-hand panel brings together the evidence for a more complex connectivity, including dopaminergic modulation at multiple sites, and reciprocal connections among the globus pallidus pars externa, subthalamic nucleus, and globus pallidus pars interna (Gpi). SNr, substantia nigra pars reticulata.

Modi ed from Nat Rev Neurosci. 11(11), Redgrave P, Rodriguez M, Smith Y, Rodriguez-Oroz MC, Lehericy S, Bergman H, et al. Goal-directed and habitual control in the basal ganglia: implications for Parkinson’s disease, pp. 760–72, Copyright (2010), with permission from Nature Publishing Group.

the neuropsychological approach to basal ganglia function has arguably not been as informative for functional mapping as it has been for cortical functions.

Bellebaum and colleagues studied the ability to learn new rules in ten patients with unilateral lesions, using probabilistic stimu- lus association task with di erential rewards. Patients were able to learn the associations, but were impaired at learning the reversal of associations, especially with dorsal lesions, a de cit also observed in Parkinson’s disease. Carry-over e ects impaired learning of sec- ondary tasks. Intriguingly, a patient with bilateral lesions showed superior performance compared to controls, due to an e ective compensatory declarative memory strategy.24

e complex cognitive consequences of basal ganglia lesions are demonstrated in Benke and colleagues’ description of two cases with haematomas a ecting distinct regions of the le striatum and pallidum. Despite only having unilateral lesions, both patients were acutely abulic, with minimal spontaneous activity of speech, long response latencies, motivational de cits, and relative indi erence to their illness.25 A disabling lack of concern, motivation, and ini- tiative persisted long term, without depression. On untimed tests, both patients had preserved arithmetic, reading, writing, naming, and comprehension but both manifested a dynamic aphasia with sparse delayed and reduced verbal output and reduced uency. Cognitive exibility, set-shi ing, design uency, and attention were severely a ected, with di culty initiating responses and respond- ing to error feedback. ese features overlap with the dysexecutive syndrome of frontal cortical lesions, as well as Huntington’s and Parkinson’s disease.

e syndrome manifested by these two patients did not, however, correspond to the separate predictions of a ective, associative and motor functions in segregated parallel loops via ventral and dorsal striatum. is may be because the lesions were larger than were

seen by non-invasive brain imaging: more extensive overlapping changes in white matter connections might have been revealed by techniques such as di usion-weighted imaging. However, there was a surprising similarity between the two patients’ neuropsychologi- cal de cits, despite their lesions being in quite di erent places. is suggests extensive cross-talk between the basal ganglia circuits for a ective, associative, and motor functions, con rming the extent to which the basal ganglia create an integrated system for complex goal-directed behaviours.26

Lesions to the ventral striatum and caudate nucleus may also a ect social and emotional cognition,27,28 while pallidal lesions may also lead to profound apathy.29 is re ects the rich intercon- nections of this basal ganglia region with the orbitofrontal cortex and ventromedial prefrontal cortex, which are associated with social and emotional cognition in health,30 and social cognitive impairments in degenerative neurological disease.31 For example, Kemp and colleagues reported the e ects of a haemorrhagic arte- riovenous malformation in the le caudate nucleus of a 44-year-old man.32 He gradually lost empathy and changed character, becom- ing ‘mean’, ‘sel sh’, and paranoid. His abstract reasoning remained excellent, together with language, memory, visual attention, and most executive functions (except for some slowing). He could rec- ognize basic emotions (e.g. anger, sadness) and accurately answer questions about scenarios pertaining to other people’s knowledge or beliefs. However, he was greatly impaired in recognizing other people’s complex mental states (e.g. desire) and could not under- stand the occurrence of social faux pas.33 Although the only lesion was in the caudate nucleus, brain perfusion imaging suggested hypometabolism in the upstream and downstream connections of the caudate, speci cally in the le thalamus, prefrontal and orbito- frontal cortex, highlighting the need to recognize cortico-striato- thalamo-cortical loops as a coherent system.






SNc Dopaminergic




74 SECTION 1 normal cognitive function

Some authors present Parkinson’s disease as a model of basal gan- glia dysfunction but this approach can be misleading. Parkinson’s disease is associated with widespread pathology, in basal ganglia, brainstem nuclei, and cortex, and a ects multiple neurotransmitter systems. Few studies have directly compared Parkinson’s disease with focal basal ganglia lesions.34 Both impair rule-based categorization tasks, but focal lesions selectively impair the learning of a complex discrimination task based on a conjunction of stimuli, not a simple categorization task. In contrast, Parkinson’s disease a ects the sus- tained performance of a simple one-dimensional task as well as caus- ing suboptimal strategies on the more complex conjunction task.

In summary, even unilateral lesions of the basal ganglia can cause long-lasting and severe cognitive de cits, a ecting executive functions, learning, and social cognition. However, human lesion data currently lack the anatomical speci city for precise functional mapping of the basal ganglia.

Neurodegenerative disorders

of the basal ganglia

Much of the information available about the role of basal ganglia in cognition has come from the study of neurodegenerative disorders, especially Parkinson’s disease and Huntington’s disease, but also progressive supranuclear palsy and frontotemporal dementia. One must bear in mind that these disorders are not neuropathologically restricted to the basal ganglia, or to a single neurotransmitter such as dopamine. For example, serotonergic,35 noradrenergic,36 and extras- triatal dopamine37 systems all contribute to cognitive de cits in Parkinson’s disease. Nonetheless, striatal dysfunction is a major con- tributor the neuropsychological pro le of these neurodegenerative disorders (see Fig. 7.5). Whilst the cognitive manifestations of these disorders are discussed in more detail in Section 3, a brief overview of each with particular focus on the basal ganglia, is provided below.

Parkinson’s disease

Half of all people with Parkinson’s disease have mild cognitive impairment soon a er diagnosis,3 and cognitive de cits may be present before diagnosis or the onset of motor symptoms. However, the cognitive impact of Parkinson’s disease is multifaceted. e dual syndrome hypothesis38,39 sets out the distinction between common early frontostriatal de cits and a later dementia. Early frontostriatal de cits are associated with loss of striatal dopamine (and loss of ser- otonin and noradrenaline) and are seen in about a third of patients at presentation, doubling a er four years.7,40 ey are characterized by impairments in executive functions: cognitive exibility includ- ing reversal learning, response inhibition, planning, attentional set- shi ing, action selection, and decision-making according to risk or reward. Indeed, the impact of early Parkinson’s disease on learning and memory is in part due to these executive function de cits.41

e dementia associated with Parkinson’s disease is not merely a wors- ening of these frontostriatal de cits but rather a set of temporoparietal cortical de cits, most associated with cholinergic loss. ese encompass poor episodic memory, visuospatial de cits, poor uency, and risk of hallucination. Approximately one in ten people with Parkinson’s disease develops dementia by three years and half by ten years.97

e ability to adapt behaviour to a novel or changing environ- ment is central to the concept of executive functions. is has been widely studied in the context of visual discrimination learning, from the Wisconsin Card Sort Test and Montreal Card Sort Test through to translational models such as the Cambridge Automatic Neuropsychological Test Battery’s (CANTAB) intra- and extra- dimensional shi task (IDED). During the IDED task, partici- pants learn a series of visual discriminations based on compound stimuli. When a given discrimination is learned to criterion, the rules change and, in response to feedback, subjects must change their cognitive strategy and learn a new discrimination. Mild to

Fig. 7.5 In contrast to healthy adults (top left, HC), a carrier of CAG expansions in the Huntingtin gene (top middle, HD) shows marked atrophy of the caudate nucleus (yellow arrows) while still asymptomatic several years before Huntington’s disease onset. Below, a voxel-based morphometry (VBM) analysis of 21 presymptomatic carriers con rms the signi cant degree of caudate atrophy (yellow cluster) in the absence of signi cant cortical atrophy. In contrast, the caudate is grossly preserved in early Parkinson’s disease but dopamine transporter (DAT) imaging shows signi cant dopaminergic denervation of the striatum, especially the putamen (DAT-PD, red arrows), in contrast to a healthy adult (DAT-HC).

Courtesy of Prof. Roger Barker.

moderate Parkinson’s disease does not a ect the acquisition of simple discrimination, but it severely impairs the ability to make an attentional shi between two alternate perceptual dimensions in the stimuli, such as ‘colour’ and ‘shape’ (the ‘extra-dimensional shi ’).42–44

is de cit in Parkinson’s disease is ambiguous: it could be due to perseveration (the inability to disengage attention from a previ- ously relevant dimension) or to learned irrelevance (the inability to attend and learn about information which has previously been shown to be irrelevant). People with Parkinson’s disease are espe- cially impaired when an extra-dimensional shi is accompanied by learned irrelevance.45 However, the de cit in Parkinson’s dis- ease does not in itself indicate that it is due to striatal dopamin- ergic abnormalities. Indeed, dopaminergic medication makes little di erence to extra-dimensional shi impairments.46 In addition, severe dopamine depletion from the caudate in marmosets does not impair discrimination learning or extradimensional shi s. However, caudate dopamine depletion does impair shi ing back to a previously reinforced dimension, suggesting that it is learned irrelevance which is a ected by striatal dopamine depletion in Parkinson’s disease.47,48

Parkinson’s disease impairs reversal learning, in which reward contingencies are reversed across a set of stimuli. e striatum is implicated in reversal learning, from animal models and human neuroimaging.49 People with Parkinson’s disease are impaired on reversal learning, but dopaminergic medication may actually worsen this impairment. is paradoxical e ect may result from the precision of normal dopaminergic ring, with phasic bursts against background tonic activity, such that dopaminergic medica- tion reduces signal-to-noise of the ventral striatal phasic dopamine release that signals reversal.17 Interestingly, the adverse e ect of dopamine treatment is restricted to conditions in which the rever- sal is signalled by unexpected punishment, not reward.50 e pres- ence of cognitive impairment, including reversal learning de cits, depends on the stage of disease and the type of stimulus used, with a di erence in the importance of cortex versus striatum according the use of abstract versus concrete rules.50,51 e shi and reversal tasks described above relied on trial and error learning, accord- ing to feedback. However, Parkinson’s disease also impairs cogni- tive exibility when the required task shi is explicitly cued52 or implied by a sequence of stimuli.53,54

To optimize behaviour, it is o en necessary to weight di erent cognitive strategies according to recent experience and anticipated events, rather than make ‘black and white switches’ between cogni- tive strategies as in the IDED task and reversal paradigms. Rowe and colleagues studied such weighting between cognitive strate- gies, using a continuous performance task with two concurrent stimulus dimensions and a partial reward schedule.55 People with Parkinson’s disease were able to modulate the balance between alternate cognitive sets, according to the reward relevance of antici- pated stimuli. However, the associated activations of the caudate nucleus and the ventrolateral prefrontal cortex were dependent on the severity of disease and dopaminergic treatment: there was a non-linear (inverted U-shaped) relationship between the activa- tion and the disease severity. e deviation from normality of this inverted U-shape curve increased progressively across the cortex (from motor to premotor to dorsal then ventral prefrontal cortex) and striatum (from caudal putamen to ventral striatum). A simi- lar U-shape function in caudate and ventral prefrontal cortical

activations in Parkinson’s disease was observed for cognitive deci- sions regarding alternate manual responses,56 and represents a gen- eralized non-linear function of dopamine in human cognition.55

e non-linear U-shaped relationship between performance (or activation) and disease severity, or between performance (or activation) and dopaminergic drug dose, has major implications for treating cognitive function in Parkinson’s disease. First, clin- ical decisions for dose escalation are typically made according to motor features (e.g. tremor, rigidity) and the levodopa dose is rarely chosen so as to optimize cognitive function even though cognitive impairments are a major determinant of patient and carer quality of life. Second, it may not be possible to optimize both cognitive and motor functions with a given dose using systemic medication. Instead, a combined approach with local basal ganglia therapies (such as deep brain stimulation or gene therapy) and systemic drugs may be required to approximate optimal treatment in di er- ent basal ganglia circuits for a ective, cognitive, and motor func- tions. ird, since dopaminergic dysfunction in early Parkinson’s disease mainly a ects the dorsal striatum disease,57 dopaminergic medication may e ectively ‘overdose’ the ventral striatum and pre- frontal cortex. Indeed, compensatory changes in the substantia nigra and VTA may lead to mild hyperdopaminergic states in the ventral striatum and mesocortex in early Parkinson’s58 in addition to pharmacotherapeutic overdose of the ventral striatum.

A striking consequence of ventral striatal dopamine ‘overdose’ is the induction of impulse control disorders (ICDs) in about one in seven patients on dopamine agonists. ese include hypersexual- ity, paraphilias, pathological gambling, binge eating, and impulsive shopping which can be devastating in their long-term conse- quences even a er medication is reduced and the behaviour abated. As explained above, dopaminergic neurons projecting from the ventral tegmental area signal unexpected rewards, or cues that have been associated with reward.59 is dopamine reward signal in the striatum is exaggerated in relatively impulsive normal adults60 and appears to be magni ed in Parkinson’s disease. For example, positron emission tomography (PET) studies reveal abnormally enhanced dopamine release in the ventral striatum of patients with pathological gambling.61 However, extrastriatal dopamine may also contribute to the pathogenesis of ICDs in Parkinson’s disease62 including the cingulate and medial prefrontal cortical mecha- nisms by which actions are associated with reward. Functional MRI (fMRI) studies suggest that Parkinson’s disease (even without ICDs) reduces the cingulate cortical response to reward anticipa- tion, but increases the regional response to actual reward.54

is devaluation of anticipated future rewards in Parkinson’s dis- ease contributes to the preference for smaller immediate rewards over larger delayed rewards,63 especially in those patients with ICDs and those taking dopamine agonists. For reversal learning, there is again a di erential e ect of Parkinson’s disease on posi- tive (rewarding) versus negative (punishment) feedback: patients at risk of ICDs become less responsive to negative feedback,64 as well as more responsive to rewards. is distortion of the evaluation of outcomes, worsened by dopamine agonists, increases risk taking despite lower ventral striatal, orbitofrontal, and anterior cingulate activity.65,66

Huntington’s disease

Huntington’s disease (HD) is a complex, multifocal neurologi- cal disorder, caused by an inherited expansion of a trinucleatide

CHAPTER 7 the basal ganglia in cognitive disorders 75

76 SECTION 1 normal cognitive function

cytosine–adenine–guanine (CAG) repeat in the Huntingtin gene. e disease causes progressive motor dysfunction, cognitive decline, and psychiatric disturbances starting usually between 30 and 50 years old. Cognitive symptoms or signs o en develop prior to motor signs. Although the normal functions of this gene are not fully elucidated, striatal involvement is characteristic,67 with severe loss of the caudate nuclei as one of the hallmarks of the disease (Fig. 7.5).

Huntington’s disease impairs executive functions, emotion and social cognition, and memory. e autosomal dominant genetic aetiology of Huntington’s disease allows one to study presymp- tomatic stages of disease, in the absence of medication or gross performance de cits. In addition, there are correlations between caudate volume and cognitive function and functional brain imag- ing by fMRI, pointing to the relevance of the striatum to cognitive function and cognitive decline in Huntington’s disease.68–70

Caudate loss is evident in presymptomatic carriers (Fig. 7.5),71,72 which progresses in severity and spatial extent during the symp- tomatic phase from the dorsal head of caudate to ventral striatum and putamen.72–75 In contrast, cortical atrophy is more commonly associated with later stages of disease.74 Within the body and head of the caudate, medium spiny neurons of the indirect pathway are especially a ected. In keeping with the dual pathway model, this leads to disinhibition of the external globus pallidus, and down- stream disinhibition of the thalamus. e direct pathway becomes overactive, exaggerating the thalamic disinhibition.

e imbalance between direct and indirect pathways can a ect associative, a ective, and motor loops through the basal ganglia. However, because of the topographical organization of neuropath- ology, there are trends towards di erential times of onset of cog- nitive and behavioural impairments according to the functional anatomy of the cortico-striato-thalamo-cortical loops. For example, Holl and colleagues reported de cits in verbal uency and Stroop interference,76 but in contrast to Parkinson’s disease, patients with Huntington’s disease were unimpaired on a gambling task that required risk decision-making. e dissociation is likely because of the di erential distribution of pathology across the ventromedial versus dorsolateral caudate nucleus and the respective connections of these regions. However, these clinicopathological correlations are only partial. Among patients ten or more years before estimated disease onset, there is evidence of caudate volume reduction in the absence of cognitive decline.77–79 is suggests early compensation for the striatal changes, either within the striatum or the regions with which it is interconnected.

Cognitive changes in such presymptomatic cases or early stage disease are likely to be due to striatal involvement, and Huntington’s disease has o en been used as a model to study the role of the stria- tum in cognition, especially when supported by speci c structure– function correlations. For example, early ‘striatal’-stage disease impairs rule based language learning, in contrast to later cortical stages which a ect other forms of learning.80 Importantly, learning capacity correlates with the severity of caudate atrophy. Other early de cits include executive functions such as uency, interference control, and Trail Making Test B,78,81,82 emotion recognition,83,84 and visuomotor integration.85

In symptomatic disease, the severity and range of cognitive de – cits broadens, due to emerging cortical as well as extended striatal involvement. Planning, attention, and rule learning, psychomo- tor speed, episodic memory, and emotional or social cognition

progressively decline. However, some major cognitive domains remain relatively una ected until late stages of disease, including semantic memory, language (not including uency), visuospatial functions, and orientation.82

Further evidence for the striatal contribution to cognitive change comes from functional brain imaging with fMRI. For example, ven- tral striatal activity related to anticipated reward is blunted in gene carriers approaching disease onset.86 However, changes in activa- tion are not necessarily localized to the striatum, even in early dis- ease. For example, the executive function of set-shi ing activates extensive prefrontal, parietal and cingulate cortex, and basal gan- glia in healthy adults. e putamenal and pallidal activations were increased in patients even in premanifest cases, but there were also extensive increases in cortical activations.87

Similarly, during working memory performance the activa- tion di erences observed in manifest and presymptomatic carri- ers include, but are not con ned to, the caudate and putamen.88 is should not be surprising, in view of the connectivity through cortico-striato-thalamo-cortical loops, as the e ects of a lesion or perturbation in one node of the circuit are propagated throughout the circuit, including recurrent connections to the cortical regions that project to the striatum. e importance of this circuit-based understanding of cognitive dysfunction is underscored by the cor- relations between cognitive decline and (i) atrophy of cortex;89 (ii) atrophy of caudate;90 (iii) changes in the white matter structural connections between frontal cortex and the striatum;91,92 and (iv) changes in frontostriatal functional connectivity.70,86

Progressive supranuclear palsy

Progressive supranuclear palsy (PSP) is sometimes still described as a ‘Parkinson’s plus’ syndrome and movement disorder. However, this overlooks the marked clinical and pathological distinctions from Parkinson’s disease,93 and the extensive cognitive problems which are a major determinant of patient and carer quality of life.94 ‘Mental features’ were noted in the original description 50 years ago,95 and cognitive change remains part of the supportive diag- nostic criteria. Indeed, one in ten patients present with cognitive symptoms,96 and two-thirds will develop a dementia.97,98

PSP is caused by hyperphosphorylation and aggregation of the microtubule-associated protein tau, leading to cell dysfunction and death. It a ects many parts of the basal ganglia, including the striatum, pallidum, substantia nigra, subthalamic nucleus (other a ected regions include the red nucleus, pontine tegmentum, ocu- lomotor nuclei, medulla, dentate nucleus and cortex99). Atrophy of the dorsal midbrain is severe with marked reductions in dopa- minergic innervation of striatum and cortex. Caudate atrophy is evident on MRI,100 together with severe striatal hypometabolism from FDG-PET101 and abnormal striato-frontal connections.102,103

e cognitive e ects of PSP include behavioural change (apathy, irritability, childishness, impulsivity), executive dysfunction, mem- ory, visuospatial, language and social cognitive de cits. Cognitive slowing typically develops early in the disease. Executive de cits occur in about three quarters of patients. For example, Robbins and colleagues105 identi ed de cits in short-term memory and spatial working memory with poor memory strategies, but also poor plan- ning on the Tower of London task, and severe de cits in attentional set-shi ing. However, simple rule acquisition remains relatively intact.104,105 Others have reported de cits in tests of frontal lobe function such as the Trail Making B task106 and a range of executive

and non-verbal reasoning tasks.98,107,108 Even verbal uency, which requires executive as well as lexical functions, is profoundly impaired in PSP.97 Recent work has also shown that emotional and social cognitive systems are abnormal in PSP.31,109 Both emotion recognition and higher-order social inferences (known as eory of Mind) are a ected across visual and auditory domains. One-third of patients manifest poor episodic memory and poor visuospatial functions.110–112 However, such de cits may be in part related to executive impairments, a ecting retrieval or task strategies.

Despite the wide-ranging cognitive de cits in PSP and the sever- ity of pathology in the basal ganglia, it is less clear to what extent the basal ganglia changes are the cause of the cognitive decline. Albert and colleagues used PSP to illustrate the concept of ‘subcortical dementia’, attributing the majority of cognitive change to subcor- tical pathology. is was distinguished from ‘cortical dementias’ such as Alzheimer’s disease with amnesia, aphasia, apraxia, and agnosia. However, the extent of cortical pathology and of cortical neurotransmitter loss has become more widely recognized, and functional cognitive impairments shown to correlate with corti- cal atrophy100,113 or cortical hypopmetabolism,114 including global cognitive function and social cognitive de cits.31 Nonetheless, dor- sal striatal atrophy occurs in PSP,113,115 and caudate atrophy can be severe, correlating with global cognitive decline in PSP,104 hypome- tabolism,101 and the presence of neuropathology in the majority of cases.116 Further, albeit indirect, evidence comes from the observa- tion that greater pathology in the caudate and substantia nigra is associated with a classical phenotype (also called PSP–Richardson’s syndrome) with prominent cognitive and behavioural changes, as opposed to a syndrome more closely resembling Parkinson’s disease.117

Frontotemporal dementia

Frontotemporal dementia (FTD) has long been associated with severe atrophy of the frontal, temporal, and insula cortex. However, the basal ganglia are also a ected, especially in the behavioural var- iant of frontotemporal dementia, with hypometabolism and atro- phy.118,119 e non- uent variant of primary progressive aphasia (progressive non- uent aphasia) is also associated with atrophy in caudate, nucleus accumbens, and, to a lesser extent, the putamen. In the semantic variance of primary progressive aphasia (semantic dementia) the caudate is grossly preserved. In addition to atrophy, functional connectivity of the striatum is abnormal in FTD.120 It has been suggested that cognitive de cits related to striatal dys- function in FTD are lateralized, with right-sided changes associ- ated with behavioural change, apathy, empathy, and stereotypies, whereas le -sided changes are associated with executive, language, and psychomotor features.121

However, the contribution of the striatal atrophy to cognitive impairment in FTD is not fully characterized. It may be that some of the observations re ect changes that are secondary to atrophy of the cortical areas with which striatal regions interconnect. It is necessary to try to uncouple the cortical from striatal contributions to cognitive impairment, for example by closer analysis of individ- ual di erences or longitudinal designs. For example, Dalton and colleagues used voxel-based morphometry to study the anatom- ical basis of the impairment of probabilities-associative learning in FTD. Performance variability within the patient group correlated with grey matter volume in the striatum, including ventral stri- atum, head of caudate, and rostral putamen.122

CHAPTER 7 the basal ganglia in cognitive disorders 77 Conclusion

e basal ganglia are a ected by diverse neurological disorders, with common cognitive and behavioural consequences includ- ing the impairment of executive functions (e.g. attentional shi s, reversal), apathy and impulse control disorders, disrupted learning, social and emotional cognition. e cognitive de cits are similar to the e ects of lesions of the frontal cortical regions with which the striatum is densely connected. A set of ‘frontostriatal’ circuits has been proposed, in which the functional consequences of dis- ease re ect the anatomy, pharmacology, and connectivity of the normal basal ganglia. ese circuits are organized by two broad principles that facilitate integration and segregation of informa- tion processing: rst, that there is homology between cortico- striato-thalamo-cortical loops for motor, cognitive, and limbic functions; second, that there is an anatomical and pharmacologi- cal distinction between direct and indirect pathways connecting the striatum, pallidum, subthalamic nucleus, and substantia nigra. Neurodegenerative disorders show partial selectivity within these networks, by region and by pharmacologically de ned neuronal subtypes, leading to characteristic neuropsychological pro les in premanifest, early, and late stages of disease.


James Rowe is supported by the Wellcome Trust (103838) and Timothy Rittman is supported by the Medical Research Council.


1. Wilson S. An experimental research into the anatomy and physiology of the corpus striatum. Brain. 1914;36:427–92.

2. Heimer L, Switzer R, and Hoesen G. Ventral striatal and ventral pal- lidum: Additional copmonents of the motor system? Trends Neurosci. 1982;5:83–7.

3. Yarnall AJ, Breen DP, Duncan GW, et al. Characterizing mild cogni- tive impairment in incident Parkinson disease: e ICICLE–PD Study. Neurology. 2014;82(4):308–16. Epub 2013/12/24.

4. Alexander GE, Crutcher MD, and DeLong MR. Basal ganglia- thalamocortical circuits: Parallel substrates for motor, oculomotor, ‘prefrontal’ and ‘limbic’ functions. Prog Brain Res. 1990;85:119–46.

5. Alexander GE, DeLong MR, and Strick PL. Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu Rev Neurosci. 1986;9(1–2):357–81.

6. Middleton FA and Strick PL. Basal ganglia and cerebellar loops: Motor and cognitive circuits. Brain Res Rev. 2000;31(2–3):236–50.

7. Williams-Gray CH, Foltynie T, Brayne CE, et al. Evolution of cogni- tive dysfunction in an incident Parkinson’s disease cohort. Brain. 2007;130(Pt 7):1787–98.

8. Draganski B, Kherif F, Kloppel S, et al. Evidence for segregated and integrative connectivity patterns inthe human basal ganglia. J Neurosci. 2008;28:7143–52.

9. Postuma RB and Dagher A. Basal ganglia functional connectivity based on a metanalysis of 126 positron emission tomography and functional magnetic resonance imaging publications. Cereb Cortex. 2006;10:1508–21.

10. Choi EY, Yeo BTT, and Buckner RL. e organization of the human striatum estimated by intrinsic functional connectivity. J Neurophysiol. 2012;108(8):2242–63.

11. Haber SN, Fudge JL, and McFarland NR. Striatonigrostriatal pathways in primates form an ascending spiral from the shell to the dorsolateral striatum. J Neurosci. 2000;20(6):2369–82. Epub 2000/03/08.

12. Oorschot DE. Total number of neurons in the neostriatal, pal- lidal, subthalamic, and substantia nigral nuclei of the rat basal

78 SECTION 1 normal cognitive function

ganglia: A stereological study using the cavalieri and optical disector

methods. Journ Comp Neurol. 1996;366(4):580–99.

13. Pawlak V and Kerr JND. Dopamine receptor activation is required for
corticostriatal spike-timing-dependent plasticity. Journal of Neurosci.

14. Cui G, Jun S, Jin X, Pham M, et al. Concurrent activation of stri-
atal direct and indirect pathways during action initiation. Nature.

15. Calabrese P, Picconni B, Tozzi A, et al. Direct and Indirect pathways of
basal ganglia: A critical reappraisal. Nat Neurosci. 2014;17(8):1022–30.

16. Schultz W and Dickinson A. Neuronal coding of prediction errors.
Annu Rev Neurosci. 2000;23:473–500.

17. Cools R, Lewis SJ, Clark L, et al. L-DOPA disrupts activity in the
nucleus accumbens during reversal learning in Parkinson’s disease.
Neuropsychopharmacol. 2007;32(1):180–9.

18. Wolpe N and Rowe J. Disorders of Volition from Neurological Disease.
In: P Haggard (ed.). Agency: Functions and Mechanisms. Oxford:
Oxford University Press, 2014, pp. 389–414.

19. Redgrave P, Vautrelle N, and Reynolds JNJ. Functional properties of
the basal ganglia’s re-entrant loop architecture: Selection and reinforce-
ment. Neuroscience. 2011;198:138–51.

20. Redgrave P and Gurney K. e short-latency dopamine signal: a role in
discovering novel actions? Nature Rev Neuro. 2006;7(12):967–75.

21. Wolpe N, Moore JW, Rae CL, Rittman T, Altena E, Haggard P, et al. e
medial frontal-prefrontal network for altered awareness and control of action in corticobasal syndrome. Brain. 2013;137(1):208–20. Epub 2013/12/03.

22. Moore J, Schneider S, Schwingenshuhc P, Morettoa G, Bhatia KP, and Haggard P. Dopaminergic medication boosts action–e ect binding in Parkinson’s disease. Neuropsychologia. 2010;48:1125–32.

23. Bhatia K and Marsden C. e behavioural and motor consequences of focal lesions of the basal ganglia in man. Brain. 1994;117(4):859–76.

24. Bellebaum C, Koch B, Schwarz M, and Daum I. Focal Basal Ganglia
lesions are associated with impairments in reward-based reversal learn-
ing. Brain. 2008;131(3):829–41.

25. Benke T, Delazer M, Bartha L, and Auer A. Basal Ganglia Lesions
and the eory of Fronto-Subcortical Loops: Neuropsychological Findings in Two Patients with Le Caudate Lesions. Neurocase. 2003;9(1):70–85.

26. Haber SN. e primate basal ganglia: parallel and integrative networks. J Chem Neuroanat. 2003;26(4):317–30.

27. Calder A, Keane J, Lawrence A, and Manes F. Impaired recogni- tion of anger following damage to the ventral striatum. Brain 2004;127:1958–69.

28. Paulman S, Pell M, and Kotz S. Functional contributions of the basal ganglia to emotional prosody: Evidence from ERPs. Brain Res. 2008;1217:171–8.

29. Adam R, Le A, Sinha N, Turner C, et al. Dopamine reverses reward insensitivity in apathy following globus pallidus lesions. Cortex. 2013 May;49(5):1292–303.

30. Amodio D and Frith C. Meeting of minds: e medial frontal cortex and social cognition. Nat Rev Neurosci. 2006;7(4):268–77.

31. Ghosh BC, Calder AJ, Peers PV, Lawet al. Social cognitive de cits and their neural correlates in progressive supranuclear palsy. Brain. 2012;135(Pt 7):2089–102.

32. Kemp J, Berthel MC, Dufour A, et al. Caudate nucleus and social cogni- tion: Neuropsychological and SPECT evidence from a patient with focal caudate lesion. Cortex. 2013;49(2):559–71. Epub 2012/02/14.

33. Baron-Cohen S, O’Riordan M, Stone V,. Recognition of faux pas by normally developing children and children with Asperger syndrome or high-functioning autism. J AutismDev Disord. 1999;29(5):407–18.

34. Ell S, Weinstein A, and Ivry R. Rule-Based Categorization De cits in Focal Basal Ganglia Lesion and Parkinson’s Disease Patients. Neuropsychologia. 2010;48(10):2974–86.

35. Ye Z, Altena E, Nombela C, et al. Selective serotonin reuptake inhibi- tion modulates response inhibition in Parkinson’s disease. Brain. 2014 Apr;137(Pt 4):1145–55.

36. Ye z, Altena E, Nombela C, Houseden C, et al. Improving impulsivity in Parkinson’s disease with atomoxetine. Biol Psychiat. 2014. doi:10.1016/ j.biopsych.2014.01.024.

37. Christopher L, Marras C, Du -Canning S, , et al. Combined insu-
lar and striatal dopamine dysfunction are associated with executive de cits in Parkinson’s disease with mild cognitive impairment. Brain. 2014;137:565–75.

38. Kehagia A, Barker R, and Robbins T. Neuropsychological and clinical heterogeneity of cognitive impairment and dementia in patients with Parkinson’s disease. Lancet Neurol. 2010;9:1200–13.

39. Kehagia A, Barker R, and Robbins T. Cognitive impairment in Parkinson’s disease: e dual syndrome hypothesis. Neurodegener Dis. 2013;11:79–92.

40. Foltynie T, Brayne CE, Robbins TW, et al. e cognitive ability of an incident cohort of Parkinson’s patients in the UK. e CamPaIGN study. Brain. 2004;127(Pt 3):550–60.

41. Grahn JA, Parkinson JA, and Owen AM. e role of the basal ganglia in learning and memory: Neuropsychological studies. Behav Brain Res. 2009;199:53–60.

42. Owen AM, James M, Leigh PN, et al. Fronto-striatal cognitive de cits at di erent stages of Parkinson’s disease. Brain. 1992;115(Pt 6):1727–51. 43. Owen AM, Roberts AC, Hodges JR, et al. Contrasting mechanisms of

impaired attentional set-shi ing in patients with frontal lobe damage or

Parkinson’s disease. Brain. 1993;116(Pt 5):1159–75.
44. Downes JJ, Roberts AC, Sahakian BJ, et al. Impaired extra-dimensional

shi performance in medicated and unmedicated Parkinson’s disease: Evidence for a speci c attentional dysfunction. Neuropsychologia. 1989;27(11–12):1329–43.

45. Slabosz A, Lewis SJ, Smigasiewicz K, et al. e role of learned irrel- evance in attentional set-shi ing impairments in Parkinson’s disease. Neuropsychol. 2006;20(5):578–88.

46. Cools R, Barker RA, Sahakian BJ, et al. Enhanced or impaired cognitive function in Parkinson’s disease as a function of dopaminergic medica- tion and task demands. Cereb Cortex. 2001;11(12):1136–43.

47. Cro s HS, Dalley JW, Collins P, et al. Di erential e ects of 6-OHDA lesions of the frontal cortex and caudate nucleus on the ability to acquire an attentional set. Cereb Cortex. 2001;11(11):1015–26.

48. Collins P, Roberts AC, Dias R, et al. Perseveration and strategy in a novel spatial self-ordered sequencing task for nonhuman primates. E ects Of excitotoxic lesions and dopamine depletions of the prefrontal cortex. J Cogn Neurosci. 1998;10(4):332–54.

49. Cools R, Clark L, Owen AM, et al. De ning the neural mechanisms of probabilistic reversal learning using event-related functional magnetic resonance imaging. J Neurosci. 2002;22(11):4563–7.

50. Cools R, Altamirano L, and D’Esposito M. Reversal learning in Parkinson’s disease depends on medication status and outcome valence. Neuropsychologia. 2006;44(10):1663–73.

51. Cools R, Clark L, and Robbins TW. Di erential responses in human striatum and prefrontal cortex to changes in object and rule relevance. J Neurosci. 2004;24(5):1129–35.

52. Cools R, Barker RA, Sahakian BJ, et al. L-Dopa medication remedi- ates cognitive in exibility, but increases impulsivity in patients with Parkinson’s disease. Neuropsychologia. 2003;41(11):1431–41.

53. Rowe JB, Eckstein D, Braver T, et al. How does reward expecta- tion in uence cognition in the human brain? J Cogn Neurosci. 2008;20(11):1980–92.

54. Rowe JB, Hughes L, Ghosh BC, et al. Parkinson’s disease and dopamin- ergic therapy—di erential e ects on movement, reward and cognition. Brain. 2008;131:2094–105.

55. Cools R and D’Esposito M. Inverted U-shaped dopamine aactions on human working memory and cognitive control. Biol Psychiatry. 2011;69(2):113–25.

56. Hughes LE, Altena E, Barker RA, et al. Perseveration and choice in parkinson’s disease: e impact of progressive frontostriatal dysfunction on action decisions. Cerebral Cortex. 2013;23(7):1572–81.

57. Kish S, Shannak K, and Hornykiewicz O. Uneven pattern of dopa- mine loss in the striatum of patients with idiopathic Parkinson’s

diease. Pathologic and clinical implications. New Engl J Med.


58. Rakshi JS, Uema T, Ito K, et al. Frontal, midbrain and striatal dopamin-
ergic function in early and advanced Parkinson’s disease A 3D [(18)F]
dopa-PET study. Brain. 1999;122(Pt 9):1637–50.

59. Schultz W. Behavioral theories and the neurophysiology of reward.
Annu Rev Psychol. 2006;57:87–115.

60. Buckholtz J, Treadway M, Cowan R, et al. Dopaminergic netwrok dif-
ferences in human impulsivity. Science. 2010;329(5991):532.

61. Steeves T, Miyasaki J, Zurowski M, et al. Increased striatal dopaminer- gic release in Parkinson’s patients with pathological gambling: A [11C]
raclopride PET study. Brain. 2009;132(5):1376–85.

62. Ray N, Miyasaki J, Zurowski M, et al. Extrastriatal dopaminergic abnor-
malities of DA homeostasis in Parkinson’s patients with medication- induced pathological gambling: A [11C] FLB-457 and PET study. Neurobiol Dis. 2012;48:519–28.

63. Housden C, O’Sullivan S, Joyce E, et al. Intact reward learning but elevated delay discounting in Parkinson’s disease patients with impulsive-compulsive spectrum behaviors. Neuropsychopharmacol. 2010;35:2155–64.

64. van Eimeren T, Ballanger B, Pellecchia G, et al. Dopamine agonists diminish value sensitivity of the orbitofrontal cortex: A trigger for pathological gambling in Parkinson’s disease? Neuropsychopharmacolo. 2009;34(13):2758–66.

65. Voon V, Gao J, Brezing C, et al H. Dopamine agonists and risk: Impulse control disorders in Parkinson’s disease. Brain. 2011;134:1438–46.

66. Djamshidian A, O’Sullivan S, Wittmann B, et al. Novelty seeking behav- iour in Parkinson’s disease. Neuropsychologia. 2011;49:2483–8.

67. Vonsattel J. Huntington disease models and human neuropathol- ogy: Similarities and di erences. Acta Neuropathol. 2008;115:55–69.

68. Georgiou-Karistianis N, Poudel G, Dominguez R, et al. Functional andconnectivity changes during working memory inHuntington’s disease: 18-month longitudinal data from the IMAGE–HD study. Brain Cognition. 2013;83:80–91.

69. Zimbleman J, Paulsen J, Mikos A, et al. fMRI detection of early neural dysfunction in preclinical Huntington’s disease. J Int Neuropsychol Soc. 2007;13(5):758–69.

70. Wolf R, Sambataro F, Vasic N, et al. Altered frontostriatal coupling in premanifest Huntington’s disease: E ects of increasing cognitive load. Eur J Neurol. 2008;15(11):1180–90.

71. Majid DS, Sto ers D, Sheldon S, et al. Automated structural imaging analysis detects premanifest Huntington’s disease neurodegeneration within one year. Mov Disord. 2011; 26(8):1481–8.

72. Aylward E, Codori A, Rosenblatt A, et al. Rate of caudate atrophy in presymptomatic and symptomatic stages of Huntington’s disease. Mov Disord. 2000;15(3):552–60.

73. Aylward E, Li Q, Stine O, et al. Longitudinal change in basal ganglia volume in patients with Huntington’s disease. Neurology. 1997;48:394–9.

74. Douaud G, Gaura V, Ribeiro M, et al. Distribution of grey matter atrophy in Huntington? s disease patients: A combined ROI-based and voxel-based morphometric study. Neuroimage. 2006;32:1562–75.

75. Tabrizi S, Reilmann R, and Roos R. Potential endpoints for clinical trials in premanifest and early Huntington’s disease in the TRACK– HD study: Analysis of 24 month observational data. Lancet Neurol. 2012;11:42–53.

76. Holl A, Wilkinson L, Tabrizi S, et al. Selective executive dysfunction but intact risky decision-making in early Huntington’s disease. Mov Disord. 2013;28(8):1104–9.

77. Tabrizi SJ, Scahill R, Durr A, et al. Biological and clinical changes in premanifest and early stage Huntington’s disease in the TRACK– HD study: e 12-month longitudinal analysis. Lancet Neurol. 2011;10(1):31–42.

78. Stout J, Paulsen J, Queller S, et al. Neurocognitive signs in prodromal Huntington’s diease. Neuropsychol. 2011;1(25):1–14.

79. Dominguez D, Egan G, Gray M, et al. Multimodal neuroimaging in premanifest and early Huntington’s diease. 18 month longitudinal data from the IMAGE-HD study. PLoS One. 2013;8(9):e74131.

80. De Diego-Balaguer R, Couette M, Dolbeau G, et al. Striatal degenera- tion impairs language learning: Evidence from Huntington’s disease. Brain. 2008;131:2870–81.

81. Holl A, Wilkinson L, Tabrizi SJ, et al. Selective Executive Dysfunction but Intact Risky Decision-Making in Early Huntington’s Disease. Mov Disord. 2013;28:1104–9.

82. Dumas E, Van den Bogaard S, Middelkoop H, et al. A review of cogni- tion in Huntington’s disease. Front Biosci (Schol Ed). 2013;5:1–18.

83. Snowden J, Austin N, Sembi S, et al. Emotion recognition in Huntington’s disease and frontotemporal dementia Neuropsychologia. 2008;46:2638–49.

84. Henley S, Novak M, Frost C, King J, Tabrizi S, and Warren J. Emotion recognition in Huntington’s diease: A systematic review. Neurosci Biobehav R. 2012; 36:237–53.

85. Say M, Jones R, Scahill R, et al. Visuomotor Integration de cits precede clinical onset in Huntington’s disease. Neuropscyhologia. 2011 49:264–70.

86. Enzi B, Edel M-A, Lissek S, et al. Altered ventral striatal activation during reward and punishment processing in premanifest Huntington’s disease: A functional magnetic resonance study. Exp Neurol. 2012;235:256–64.

87. Gray M, Egan G, Ando A, et al. Prefrontal activity in Huntiongton’s diease re ects cognitive and neuropsychiatric disturbances: e IMAGE–HD study. Exp Neurol. 2013; 239:218–28.

88. Georgiou-Karistianis N, Stout JC, Dominguez D, et al. Functional magnetic resonance imaging of working memory in Huntington’s disease: Cross-sectional data from the IMAGE–HD study. Hum Brain Mapp. 2013;35:1847–64.

89. Rosas H, Salat D, Lee S, et al. Cerebral cortex and the clinical expres- sion of Huntington’s disease: Complexity and heterogeneity. Brain. 2008;131:1057–68.

90. Peinemann A, Schuller S, Pohl C, et al. Executive dysfunction in early stages of Huntington’s disease is associated with striatal and insular atrophy: A neuropsychological and voxel-based morphometric study. J Neurol Sci. 2005;239:11–9.

91. Rosas H, Tuch D, Hevelone ND, et al. Di usion tensor imaging in presymptomatic and early Huntington’s disease: Selective white mat- ter pathology and its relationship to clinical measures. Mov Disord. 2006;21:1317–25.

92. Bohanna I, Georgiou-Karistianis N, Sritharan A, et al. Di usion Tensor Imaging in Huntington’s disease reveals distinct patterns of white mat- ter degeneration associated with motor and cognitive de cits. Brain Imaging and Behavior. 2011;5:171–80.

93. Burrell J, Hodges J, and Rowe J. Cognition in corticobasal syndrome and progressive supranuclear palsy. Mov Disord. 2014;29(5):684–93.

94. Schrag A, Selai C, Davis J, et al. Health-related quality of life in patients with progressive supranuclear palsy. Mov Disord. 2003;18(12):1464–9.

95. Steele J, Richardson J, and Olszewski J. Progressive supranuclear palsy: A heterogeneous degeneration involving the brain stem, basal ganglia and cerebellum, with vertical gaze and pseudobulbar palsy, nuchal dystonia and dementia. Arch Neurol. 1964;10:333–59.

96. Bensimon G, Ludolph A, Agid Y, et al. Riluzole treatment, survival and diagnostic criteria in Parkinson plus disorders: e NNIPPS study. Brain. 2009;132(Pt 1):156–71. Epub 2008/11/26.

97. Rittman T, Ghosh BC, McColgan P, et al. e Addenbrooke’s Cognitive Examination for the di erential diagnosis and longitudinal assess- ment of patients with parkinsonian disorders. J Neurol Neurosur Ps. 2013;84(5):544–51.

98. Pillon B, Dubois B, and Agid Y. Severity and speci city of cognitive impairment in Alzheimer’s, Huntington’s, and Parkinson’s diseases and progressive supranuclear palsy. Ann NY Acad Sci. 1991;640:224–7. Epub 1991/01/01.

99. Litvan I, Hauw JJ, Bartko JJ, et al. Validity and reliability of the pre- liminary NINDS neuropathologic criteria for progressive supranuclear palsy and related disorders. J Neuropathol Exp Neurol. 1996;55(1):97– 105. Epub 1996/01/01.

CHAPTER 7 the basal ganglia in cognitive disorders 79

80 SECTION 1 normal cognitive function

100. Cordato NJ, Duggins AJ, Halliday GM, et al. Clinical de cits correlate with regional cerebral atrophy in progressive supranuclear palsy. Brain. 2005;128(Pt 6):1259–66.

101. Karbe H, Grond M, Huber M, et al. Subcortical damage and cortical dysfunction in progressive supranuclear palsy demonstrated by posi- tron emission tomography. J Neurol. 1992;239(2):98–102. Epub 1992/ 02/01.

102. Whitwell JL, Avula R, Master A, et al. Disrupted thalamocortical connectivity in PSP: A resting-state fMRI, DTI, and VBM study. Parkinsonism Relat Disord. 2011;17(8):599–605. Epub 2011/06/15.

103. Gardner RC, Boxer AL, Trujillo A, et al. Intrinsic connectivity network disruption in progressive supranuclear palsy. Ann Neurol. 2013;73(5):603–16. Epub 2013/03/29.

104. Ghosh BC, Carpenter RH, and Rowe JB. A longitudinal study of motor, oculomotor and cognitive function in progressive supranu- clear palsy. PLoS One. 2013;8(9):e74486. Epub 2013/09/24.

105. Robbins TW, James M, Owen AM, et al. Cognitive de cits in progres- sive supranuclear palsy, Parkinson’s disease, and multiple system atro- phy in tests sensitive to frontal lobe dysfunction. J Neurol Neurosur Ps. 1994;57(1):79–88.

106. Grafman J, Litvan I, Gomez C, et al. Frontal lobe function in progres- sive supranuclear palsy. Arch Neurol. 1990;47(5):553–8. Epub 1990/ 05/01.

107. Dubois B, Pillon B, Legault F, et al. Slowing of cognitive processing in progressive supranuclear palsy. A comparison with Parkinson’s disease. Arch Neurol. 1988;45(11):1194–9. Epub 1988/11/01.

108. Lagarde J, Valabregue R, Corvol JC, et al. Are Frontal Cognitive and Atrophy Patterns Di erent in PSP and bvFTD? A Comparative Neuropsychological and VBM Study. PLoS One. 2013;8(11):e80353. Epub 2013/11/28.

109. O’Kee e FM, Murray B, Coen RF, et al. Loss of insight in frontotem- poral dementia, corticobasal degeneration and progressive supranu- clear palsy. Brain. 2007;130(Pt 3):753–64. Epub 2007/03/10.

110. Brown RG, Lacomblez L, Landwehrmeyer BG, et al. Cognitive impairment in patients with multiple system atrophy and progressive supranuclear palsy. Brain. 2010;133(Pt 8):2382–93.

111. Pillon B, Blin J, Vidailhet M, et al. e neuropsychological pattern of corticobasal degeneration: Comparison with progressive supranuclear

palsy and Alzheimer’s disease. Neurology. 1995;45(8):1477–83. Epub

112. Bak TH, Crawford LM, Hearn VC, et al. Subcortical dementia revis-

ited: Similarities and di erences in cognitive function between pro- gressive supranuclear palsy (PSP), corticobasal degeneration (CBD) and multiple system atrophy (MSA). Neurocase. 2005;11(4):268–73.

113. Cordato NJ, Pantelis C, Halliday GM, et al. Frontal atrophy correlates with behavioural changes in progressive supranuclear palsy. Brain. 2002;125(Pt 4):789–800.

114. Blin J, Baron JC, Dubois B, et al. Positron emission tomography study in progressive supranuclear palsy. Brain hypometabolic pattern and clinicometabolic correlations. Arch Neurol. 1990;47(7):747–52. Epub 1990/07/01.

115. Looi J, Macfarlane M, Walterfang M, et al. Morphometric analysis of subcortical structures in progressive supranuclear palsy: in vivo evidence of neostriatal and mesencephalic atrophy. Psychiatry Res Neuroimaging. 2011;194:163–75.

116. Verny M, Duyckaerts C, Agid Y, et al. e signi cance of cortical pathology in progressive supranuclear palsy. Clinico-pathological data in 10 cases. Brain. 1996;119 (Pt 4):1123–36. Epub 1996/08/01.

117. Williams DR, Holton JL, Strand C, et al. Pathological tau burden
and distribution distinguishes progressive supranuclear palsy- parkinsonism from Richardson’s syndrome. Brain. 2007;130:1566–76.

118. Halabi C, Halabi A, Dean DL, et al. Patterns of striatal degen- eration in frontotemporal dementia. Alzheimer Dis Assoc Disord. 2013;27(1):74–83. Epub 2012/03/01.

119. Garibotto V, Borroni B, Agosti C, et al. Subcortical and deep corti- cal atrophy in frontotemporal lobar degeneration. Neurobiol Aging. 2011;32:875–84.

120. Seeley WW, Crawford RK, Zhou J, et al. Neurodegenerative diseases target large-scale human brain networks. Neuron. 2009;62(1):42–52.

121. O’Callaghan C, Bertoux M, and Hornberger M. Beyond and below the cortex: e contribution of striatal dysfunction to cognition and behav- iour in neurodegeneration. J Neurol Neurosur Ps. 2014;85(4):371–8.

122. Dalton M, Weikert T, Hodge JR, et al. Impaired acquisition rates of probabilistic associative learning in frontotemporal dementia is associated with fronto-striatal atrophy. NeuroImage: Clinical. 2013;2:56–62.


Principles of white matter organization Marco Catani


Connectional neuroanatomy delineates the origin, course, and ter- mination of white matter pathways in the central nervous system. In clinical practice, understanding white matter anatomy can help to improve early diagnosis, optimize treatment strategies, and predict outcomes. In this chapter, the reader will be introduced to meth- ods for studying white matter anatomy, a modern classi cation of the major brain pathways underlying cognition and behaviour, and principles of white matter organization and function. A particu- lar emphasis is given to more recent tractography approaches and their application to the in vivo study of white matter anatomy in the healthy and pathological brain.

e study of white matter anatomy

e term white matter applies to the substance of the brain that contains axonal bres connecting neurons located in the grey mat- ter. In fresh tissue, white and grey matter appear di erent in colour due to the presence of a whitish myelin sheath around the axonal bres. Myelinated axons tend to group together into small bundles and several bundles gather into larger tracts called fasciculi.

Several methods have been applied to the study of white mat- ter connections in the animal and human brain (Table 8.1).1–4 e techniques developed by early neuroanatomists for gross blunt dis- sections of white matter tracts led to important anatomical insights, including the identi cation of most of the white matter tracts con- tributing to higher cognitive functions.5–7 Blunt dissections are performed on postmortem brains using specimens preserved in alcohol5,6 or frozen for several days.8,9 ese procedures harden the white matter and permit manual separation of di erent tracts with the blunt back of a knife or a spatula. One of the limitations of these methods is the proneness to artefacts (i.e. o en separation does not occur along natural cleavages) and the di culty to obtain quantita- tive measurements. Also, blunt dissections require neuroanatomi- cal knowledge, experience, and patience to achieve reliable results.

e study of white matter made a signi cant leap forward with the introduction of myelin staining methods for degenerating bres (e.g. Weigert–Pal or Marchi staining).10 e observation of serial sections of stained specimens permitted visualization of tracts in the brains of patients with cortico-subcortical lesions (mainly vas- cular) or in experimentally lesioned animal brains. Compared to blunt dissections, the histological methods are able to show the anatomy of bres and their terminations in more detail. However,

most of these methods have the same limitations as blunt dissec- tions and the reconstruction of speci c tracts in the human brain is highly dependent on the availability of pathological specimens with precisely localized lesions.

In the 1960s, a signi cant increase in knowledge about connec- tivity arose from the use of cellular transport mechanisms to detect connections between nerve cells.11 Once injected, the tracers enter the neuron and are transported from the body of the neuron to its terminations (i.e. anterograde direction), or in the opposite direc- tion (i.e. retrograde direction).3 ese methods show the anatomy of connections at the level of the single axons and remain the gold standard to understand connectivity of the animal brain. e pos- sibility of combining multiple tracers o ers also a unique advantage for depicting multiple pathways at the same time (e.g. feed-forward and feedback connections from and to a speci c area).

In the 1990s, viruses were adopted as transneuronal tracers12 with the possibility of visualizing di erent axonal pathways com- posing an entire functional system (e.g. rst, second, and third order neurons). Unfortunately, these methods are invasive and cannot be applied to the human brain. Also, correlative analysis between anatomical features of individual connections and behav- ioural performances are di cult to perform.

In the last 15 years tractography based on di usion magnetic res- onance imaging has been developed for the in vivo quanti cation of certain microstructural characteristics of a tissue13 and the vir- tual reconstruction of white matter trajectories.14–17 Tractography studies are based on the measurement of water di usion, typically within a cubic voxel in which the microstructural organization of the cerebral tissue hinders the free movement of water. In voxel- containing parallel axons, water di usion is higher in the direction parallel to the bres and restricted in the perpendicular direction. The diffusion tensor is a useful way to describe the three- dimensional displacement of water molecules and obtain an estimate of the microstructural organization of the bres.18

Tractography is based on algorithms that link together the prin- cipal tensor orientation of adjacent voxels in a continuous trajec- tory. One advantage of this method is the possibility of quantifying di usion properties of white matter in the living human brain that relate to underlying biological features (e.g. tract volume, myelina- tion. etc.)13 and correlate them with behavioural performances.19–22 Like other methods, tractography su ers some limitations, includ- ing artefactual reconstructions and the di culty of interpreting cur- rent di usivity indices in relation to pathological changes.4

82 SECTION 1 normal cognitive function Table 8.1 Methods for studying brain connections




Blunt dissections

◆  Applicable also to human brains

◆  Direct anatomical method

◆  Identify large tracts

◆  Only for postmortem tissue

◆  Operator-dependent

◆  Variable quality of the prepared sample

◆  Destructive

◆  Qualitative analysis only

◆  Limited ability to visualize crossing bundles and cortical projections (false negatives)

◆  Produce artefactual trajectories (false positives)

◆  Time consuming

Staining degenerating myelin (e.g. Marchi’s method)

◆  Direct anatomical method

◆  Identify large and small tracts ◆ Operator-independent

◆  Only for postmortem tissue

◆  Fibre delineation limited to the lesion site and extension

◆  Variable quality of the prepared sample

◆  Destructive

◆  Qualitative analysis only

◆  Time consuming

◆  3D reconstruction limited


◆  Direct anatomical method

◆  Used to identify details of local networks

◆  Allows to distinguish the bres’ neurochemical properties (e.g. cholinergic vs dopaminergic)

◆  Only for postmortem tissue

◆  Small eld of view

◆  3D reconstruction limited

◆  Time consuming

◆  Destructive

Axonal tracing

◆  Direct anatomical method

◆  Identify large and small tracts

◆  Allow direct testing of speci c hypotheses (e.g. connectivity of individual cortical regions)

◆  Can reveal bre directionality

◆  Possibility to combine multiple tracers

◆  Not suitable for humans

◆  Fibre delineation depends on the injection site

◆  Variable quality of results depending on the tracer used

◆  Qualitative analysis is di cult

◆  Limited number of tracts per sample

◆  Destructive

◆  Time consuming

◆  3D reconstruction limited

Viral tracers

◆  Visualization of multisynaptic pathways

◆  Can reveal bre directionality

◆  Spurious labelling of neurons due to cell lysis (false positives)

◆  Weak labelling due to low viral concentration (false negatives)

◆  Tropism of viruses varies according to animal species

◆  Quantitative analysis is di cult


◆  In vivo

◆  Applicable to human and animal brains

◆  Noninvasive

◆  Timee cient

◆  Allows the study of large populations

◆  Correlationwithbehaviouralandotherfunctionalmeasures

◆  Quantitative

◆  Multiple hypothesis testing

◆  Notdestructive

◆  Indirect anatomical method

◆  Low spatial resolution

◆  Presenceofartefacts

◆  Operator-dependent

◆  Limited visualization of bending, merging, and crossing bres

◆  Indirect quantitative indices of bre volume and integrity

Classi cation of white matter pathways

White matter connections can be classi ed into three major groups: association, commissural, and projection pathways.23 ese three groups are composed of long-range connections medi- ating connectivity between distant regions. A fourth group of

connections, the U-shaped bres, is responsible for the local con- nectivity between neighbouring gyri, usually within the same lobe (intralobar) or between lobes (interlobar).24 Additional tracts that do not t into the classical nomenclature have been described.24–27 ese tracts are intermediate between long association pathways and short U-shaped bres as they connect distant regions but

within the same lobe (i.e. the vertical occipital tract of Wernicke or the frontal aslant tract in the frontal lobe).24,25,28–30

Association pathways

Association pathways connect cortical regions within the same hemisphere and their bres have either a posterior–anterior or an anterior–posterior direction.17 e terminology used to indicate the association tracts o en refers to their shape (e.g. the uncinate from the Latin uncinatus meaning ‘hook-like’), their origin and termina- tion (e.g. inferior fronto-occipital fasciculus), or their course and location (e.g. inferior longitudinal fasciculus). Most of the long asso- ciation tracts are composed of short and long bres. e short bres run more super cially, closer to the cortex, and connect neighbour- ing regions. ese short bres can also be classi ed separately as individual U-shaped tracts.24,27 e long bres run just underneath the U-shaped bres and the depth of their course varies according to the distance they travel (the deepest bres travel furthest distance).

e association tracts are involved in higher cognitive functions, such as language, praxis, visuospatial processing, memory, and emotion.31 e major association tracts of the human brain are the arcuate fasciculus, the superior longitudinal fasciculus, the cingu- lum, the uncinate fasciculus, the inferior longitudinal fasciculus, and the inferior fronto-occipital fasciculus (Fig. 8.1).

e arcuate fasciculus (AF) is a dorsal association tract connect- ing perisylvian regions of the frontal, parietal, and temporal lobe. In humans two parallel pathways have been distinguished within the arcu- ate fasciculus. e medial direct pathway (i.e. the arcuate fasciculus sensu strictu or direct long segment) connects Wernicke’s region in the


Group1 strong lateralization (60%)

CHAPTER 8 principles of white matter organization 83 ASSOCIATION

(b) 18



6 2


(c) 80 70

60 50


Superior longitudinal


Inferior longitudinal


Inferior fronto-occipital

Fig. 8.1 Tractography reconstruction of the major association pathways of the human brain.
Adapted from Catani, Marco, iebaut de Schotten, Michel, Atlas of Human Brain Connections, Copyright (2012), with permission from Oxford University Press..

temporal lobe (BA 41, 42, 22, 37) with Broca’s region in the frontal lobe (BA 6, 44, 45). e indirect pathway consists of an anterior segment linking Broca’s to Geschwind’s region in the inferior parietal lobule (BA 39, 40) and a posterior segment linking Geschwind’s to Wernicke’s region.32 e direct long segment of the arcuate fasciculus is larger on the le hemisphere compared to the right in about 80 per cent of the population. e remaining 20 per cent shows a bilateral distribution.19

Among the le lateralized people the degree of asymmetry is quite heterogeneous with 60 per cent of them showing an extreme degree of le lateralization and the remaining 20 per cent a moderate le asymmetry (Fig. 8.2). In general, those who have a more bilateral

Group2 bilateral, left lateralization (20%)

Group3 bilateral, symmetrical (20%)


females males






0123 0 Groups

123 Groups


Fig. 8.2 Lateralization of long segment of the arcuate fasciculus and behavioral correlates. (a) Distribution of the lateralization pattern of the direct long segment (red). (b) Distribution of the lateralization groups between genders. (c) Performances in the CVLT according to the three lateralization groups (*, P = 0.01 versus Group 1;
†, P = 0.001 versus Group 1).
Adapted from Proc Natl Acad Sci USA. 104(43), Catani M, Allin MP, et al. Symmetries in human brain language pathways correlate with verbal recall, pp. 17163–8, Copyright (2007), with permission from PNAS.

No. of subjects

CVLT (tot score)

84 SECTION 1 normal cognitive function

distribution of the long segment connections perform better on a verbal memory task that relies on semantic clustering for retrieval (i.e. California verbal learning test, CVLT).19 Furthermore, the direct long segment in the le hemisphere mediates auditory-motor integration, which is crucial during early stages of language acqui- sition and word learning.22 e role of the indirect pathway could be more complex and related to linking semantics and phonology,33 processing syntactically complex sentences,34,35 and various aspects of verbal working memory.36 e role of the direct and indirect pathways in word repetition remains to be clari ed.37,38

e superior longitudinal fasciculus (SLF) has three distinct branches as originally described in the monkey brain using axonal tracing methods.39 In humans, the rst branch of the superior lon- gitudinal fasciculus (SLF I) connects the superior parietal lobule and precuneus (BA 5 and 7) to the superior frontal (BA 8, 9, 32) and perhaps to some anterior cingulate areas (BA 24). e SLF I processes the spatial coordinates of trunk and inferior limbs and contributes to the preparatory stages of movement planning (e.g. anticipation),40 oculomotor coordination,41 visual reaching,42 and voluntary orientation of attention.43

e second branch (SLF II) originates in the anterior intrapa- rietal sulcus and the angular gyrus (BA 39) and terminates in the posterior regions of the superior and middle frontal gyrus (BA 6, 8, 9). In the le hemisphere, the SLF II is involved in processing the spatial coordinates of the upper limbs, and in other functions similar to the SLF I.40,44 In the right hemisphere the SLF II partici- pates in attention,45,46 visuospatial processing,47 and spatial work- ing memory.48

e third branch (SLF III) connects the intraparietal sulcus and inferior parietal lobule to the inferior frontal gyrus (BA 44, 45, 47). e SLF III corresponds to the anterior segment of the arcuate fas- ciculus and the two terms are currently used interchangeably.24 Future studies will be necessary to establish whether, according to its functional role, the SLF III/anterior segment should be consid- ered as part of the sensory-motor SLF system or the arcuate lan- guage network.

In the human brain the three branches have a di erent pattern of lateralization (Fig. 8.3).21 In right-handed subjects the SLF I is symmetrically distributed between le and right hemispheres; the SLF II shows a trend of right lateralization and the SLF III is sig- ni cantly right lateralized. Most importantly, the lateralization of the SLF II correlates with asymmetry in behavioural performances for visuospatial tasks (Figs 8.3c and d). In particular, the majority of the people have a larger SLF II volumes on the right hemisphere and show a greater deviation to the le (i.e. pseudo-neglect e ect) in the line bisection, whereas those subjects deviating to the right show an opposite pattern of lateralization (i.e. larger volume of the le SLF II). Moreover, the same the correlation was found between the lateralization of SLF II volumes and the performances on a modi ed Posner paradigm, a task that measures spatial orienting of attention. Again, larger SLF II volumes in the right hemisphere corresponded to faster detection times of stimuli ashed in the le hemi eld.

It is unknown how di erences between the two hemispheres in SLF II volume can lead to asymmetrical processing of visual scenes. A larger tract in the right hemisphere could depend on several



7 5 4 2 0

–2 –4

–5 –7


0.07 0.04 0 –0.04 –0.07

–0.4 –0.2
SLF II lateralization index




r = –0.734***

–0.2 0 0.2 0.4 SLF II lateralization index

r = –0.471*






–0.3 –0.2 –0.1 0 0.1 0.2 0.3

Left lateralized Right lateralized Lateralization index (volume)

0 0.2 0.4


Fig. 8.3 Asymmetry of the superior longitudinal fasciculus (SLF) and correlations with behavioral lateralizations. (a–b) In the human brain the three SLF branches show varying degrees of asymmetry (95% con dence intervals). (c–d) e asymmetry of the SLF II correlates with the deviation on the line bisection task (c), and the lateralization of the detection time (d). *P < 0.05 and ***P < 0.001.
Adapted from Nat Neurosci. 14(10), iebaut de Schotten M, Dell’Acqua F, et al. A lateralized brain network for visuospatial attention, pp. 1245–6, Copyright (2011), with permission from Nature Publishing Group.

Lateralization index of detection time

Line bisection (mm)

factors, including greater bre myelination, more axons, and larger axonal diameter which are correlated with conduction speed or greater recruitment of cortical areas.49,50 Similar results have been found with other visuospatial attentional tests.104 Overall these ndings suggest that right hemispheric specialization for spatial attention might, in part, be explained by an unbalanced speed of visuospatial processing along the SLF II.

e cingulum is a sickle-shaped tract composed of bres of di er- ent length. e longest bres run from the amygdala, uncus (BA35), and parahippocampal gyrus (BA36 and 30) to subgenual areas of the orbitofrontal lobe (BA 25 and 11).51–53 Shorter bres, that join and leave the cingulum along its length, connect to adjacent areas of the cingulate cortex (BA 23 and 24), superior medial frontal gyrus (BA 32, 6, 8, and 9), paracentral lobule (BA4), precuneus (BA 7), cuneus (BA 19), lingual (BA 18 and 19), and fusiform gyri (BA 19 and 37).

e cingulum can be divided into a dorsal and a ventral com- ponent.54,55 e dorsal component connects areas of the dorsome- dial default-mode network.56,57 is consists of a group of medial regions whose activity decreases in the transition between a ‘rest- ing state’ and the execution of goal directed tasks, irrespective of the nature of the task. e default-mode network has been linked to a number of functions including working memory, focusing attention to sensory-driven activities, understanding other people’s intention (mentalising or theory of mind), prospective thinking (envisioning the future), and memory for personal events (autobio- graphic memory).57–59 e ventral cingulum connects amygdala and parahippocampal cortex to retrosplenial regions and forms a network dedicated to spatial orientation.60,61

e uncinate fasciculus (UF) is a hook-shaped tract that connects the anterior part of the temporal lobe (BA 38) with the orbital (BA 11 and 47) and polar (BA 10) frontal cortex.17 e bres of the unci- nate originate from the temporal pole (BA 38), uncus (BA 35), para- hippocampal gyrus (BA 36 and 30), and amygdala. A er a U-turn, the bres of the uncinate enter the anterior oor of the external/ extreme capsule between the insula and the putamen. Here, the uncinate runs inferiorly to the fronto-occipital fasciculus before entering the orbital region of the frontal lobe, where it splits into a ventro-lateral branch, which terminates in the lateral orbitofrontal cortex (BA 11 and 47), and an antero-medial branch that continues towards the cingulate gyrus (BA 32) and the frontal pole (BA 10).51

Whether the uncinate fasciculus is a lateralized bundle is still debated. An asymmetry of the volume and density of bres of this fasciculus has been reported in a human postmortem neurohis- tological study in which the uncinate fasciculus was found to be asymmetric in 80 per cent of subjects, containing on average 30 per cent more bres in the right hemisphere compared to the le .62 However, di usion measurements have shown higher fractional anisotropy in the le uncinate compared to the right in children and adolescents,63 but not in adults.21 e uncinate fasciculus connects the anterior temporal lobe to the orbitofrontal region and part of the inferior frontal gyrus and may play an important role in lexical retrieval, semantic association, naming, and social cognition.35,65–67

e inferior longitudinal fasciculus (ILF) does not constitute a single pathway, but contains bres of di erent length. e occipi- tal branches of the inferior longitudinal fasciculus connect with a number of regions dedicated to vision, including the extrastriate areas on the dorso-lateral occipital cortex (e.g. descending occipi- tal gyrus), the ventral surface of the posterior lingual and fusiform gyri, and the medial regions of the cuneus.64 ese branches run

anteriorly parallel and lateral to the bres of the splenium and optic radiation and, at the level of the posterior horn of the lateral ven- tricle, gather into a single bundle. In the temporal lobe, the infe- rior longitudinal fasciculus continues anteriorly and projects to the middle and inferior temporal gyri, temporal pole, parahippocam- pal gyrus, hippocampus, and amygdala.

An observation originally emphasized by Campbell,68 and con- sistent with axonal tracing2 and tractography ndings, is that long associative bres, such as those of the inferior longitudinal fascicu- lus, arise from the extrastriate cortex but not the calcarine striate cortex. e inferior longitudinal fasciculus carries visual informa- tion from occipital areas to the temporal lobe and plays an impor- tant role in visual object and face recognition, reading, and in linking object representations to their lexical labels.69–71

In humans, the inferior fronto-occipital fasciculus (IFOF) is a long-ranged bow-tie-shaped tract that originates from the infe- rior and medial surface of the occipital lobe (BA 19 and 18), with a minor contribution probably from the medial parietal lobe.9,17,74 As it leaves the occipital lobe and enters the temporal stem, the inferior fronto-occipital fasciculus narrows in section and its bres gather at the level of the external/extreme capsule just above the uncinate fasciculus. As it enters the frontal lobe, its bres spread to form a thin sheet, curving dorsolaterally, that terminates mainly in the ventrolateral frontal cortex (BA 11) and frontal pole (BA 10).17 Smaller bundles terminate in the rostral portion of the superior frontal gyrus (rostral portion of BA 9).2,39

ere are signi cant simian–human di erences in the anatomy of the inferior fronto-occipital fasciculus.75,76 Axonal tracing stud- ies in monkey suggest that frontal bres running through the extreme capsule do not reach the occipital lobe. For this reason, the term extreme capsule tract is a preferred name for the mon- key brain.2 e inferior fronto-occipital fasciculus may have a role in reading, writing, and other semantic and syntactic aspects of language.28,72–74

Commissural Pathways

Commissural pathways are composed of bres connecting the two halves of the brain. e major telencephalic commissures of the human brain include the corpus callosum, the anterior com- missure, and the hippocampal commissure (Fig. 8.4). A general assumption underlying the concept of commissural connections is that the information is transferred between homologous corti- cal or subcortical regions. ere are, however, a signi cant num- ber of heterotopic commissural bres connecting non-homologous regions, at least in the corpus callosum.77

e corpus callosum is the largest commissural tract in the human brain, consisting of 200–300 million axons of varying size and degrees of myelination.78,79 e corpus callosum forms the roof of the lateral ventricles and its bres are conventionally divided into an anterior forceps (or forceps minor) in the frontal lobe, a middle portion (body) in the frontoparietal region, and a posterior forceps (or forceps major) in the occipital lobe; on either side of the brain the tapetum stretches out into the temporal lobes. Other criteria have been adopted to subdivide the corpus callosum.

e most common methods segment the corpus callosum as seen in mid-sagittal section. Classical anatomical subdivisions of the corpus callosum include (from anterior to posterior) the ros- trum (orbitofrontal cortex), genu (prefrontal cortex), body (motor and premotor cortex), isthmus (temporal cortex), and splenium

CHAPTER 8 principles of white matter organization 85


normal cognitive function

Corpus callosum

Anterior commissure

radiate anteriorly to the frontal cortex (anterior thalamic peduncle), superiorly to the precentral frontal regions and parietal cortex (superior thalamic peduncle), posteriorly to the occipito-temporal cortex (posterior thalamic peduncle), and infero-anteriorly to the temporal cortex and amygdala (inferior thalamic peduncle).

e three major descending cortico-subcortical projection sys- tems of the corona radiata are the corticospinal and corticobulbar tracts, the cortical e erents to the basal ganglia and the cortical e er- ents, via the pons, to the cerebellum.90,91 e projections to the basal ganglia and cerebellum are indirectly reciprocal, so that the cortex also receives projections from these centres via the thalamus, to cre- ate complex cortico-basal ganglion and cortico-cerebellar circuits. ese projection systems are only partially segregated anatomically as they share several subcortical relay stations (e.g. the thalamus).92

e fornix is also considered as a projection tract for its projec- tions to the hippocampus, mammillary bodies, and hypothalamic nuclei. e fornix is part of the limbic system dedicated to memory and its bres connect the hippocampus with the mammillary body, the anterior thalamic nuclei, and the hypothalamus; it also has a small commissural component known as the hippocampal com- missure.17,51,60 Fibres arise from the hippocampus (subiculum and entorhinal cortex) of each side, run through the mbria, and join beneath the splenium of the corpus callosum to form the body of the fornix. Other mbrial bres continue medially, cross the mid- line, and project to the contralateral hippocampus (hippocampal commissure). Most of the bres within the body of the fornix run anteriorly beneath the body of the corpus callosum towards the anterior commissure.

Above the interventricular foramen, the anterior body of the for- nix divides into right and le columns. As each column approaches the anterior commissure it diverges again into two components. One of these, the posterior columns of the fornix, curves ventrally in front of the interventricular foramen of Monroe and posterior to the anterior commissure to enter the mammillary body (post- commissural fornix), adjacent areas of the hypothalamus, and anterior thalamic nucleus. e second component, the anterior columns of the fornix, enters the hypothalamus and projects to the septal region and nucleus accumbens.60 e fornix also contains some a erent bres to the hippocampus from septal and hypotha- lamic nuclei.52

Short association pathways

A number of short U-shaped bres and intralobar assocation tracts have been described in the human brain using postmortem dissec- tions and, more recently, tractography.107 e role of these tracts is largely unknown. Among the short intralobar association tracts connections, the frontal aslant tract, the frontal orbito-polar tract, and the vertical occipital bundle of Wernicke have been well char- acterized using tractography (Fig. 8.6).

e frontal aslant tract connects the most posterior part of Broca’s territory (i.e. precentral cortex, BA 6, pars opercularis, BA 44) in the inferior frontal gyrus with the pre-supplementary motor area (SMA) in the superior frontal gyrus (BA 8 and 6), the medial prefrontal cor- tex, and the anterior cingulate cortex.26,29,30 is tract is le later- alized in most right-handed subjects, suggesting a role in language. Medial regions of the frontal lobe facilitate speech initiation through direct connections to the pars opercularis and triangularis of the infe- rior frontal gyrus. Patients with lesions to these areas present with various degrees of speech impairment from a total inability to initiate

Fig. 8.4 Tractography reconstruction of the major commissural pathways of the human brain.
Adapted from Catani, Marco, iebaut de Schotten, Michel, Atlas of Human Brain Connections, Copyright (2012), with permission from Oxford University Press.

(occipital and temporal cortex). More recently, di usion tensor imaging has been used to divide the corpus callosum into di erent subregions according to the pattern of its cortical projections.80–84

e anterior commissure is a small bundle of bres shaped like the handlebars of an old bicycle straddling the midline. It is a famil- iar landmark in neuroradiology (e.g. distances in Talairach coor-


e commissural pathways allow the transfer of inputs between the two halves of the brain and play a signi cant role in the func- tional integration of motor, perceptual, and cognitive functions between the two hemispheres.88,89 Several callosal disconnection syndromes have been described in neurology, from anarchic hand syndrome to alien hand syndrome.54

Projection pathways

Projection pathways connect the cortex to subcortical neurons and are usually divided into ascending and descending bres (Fig. 8.5). e largest projection tracts of the cerebral hemispheres are the corona radiata and the fornix.

Within the hemispheres sensory information travels through a complex system of ascending thalamic projections. A er a short course within the internal capsule, the thalamic radiations enter the corona radiata and terminate in the cortex of the ipsilateral hemi- sphere. e e erent thalamic projections to the cerebral cortex

dinates are measured from the anterior commissure as origin). It crosses the midline as a compact cylindrical bundle between anterior and posterior columns of the fornix and runs laterally, at rst through the anterior perforated substance, and then between the globus pallidus and putamen before dividing into an anterior and posterior branch. e more anterior bres connect the amyg- dalae,86 hippocampal gyri, and temporal poles,87 while more poste- rior bres connect the ventral temporal and occipital regions.

Corona radiata


Fig. 8.5 Tractography reconstruction of the major projection pathways of the human brain.
Adapted from Catani, Marco, iebaut de Schotten, Michel, Atlas of Human Brain Connections, Copyright (2012), with permission from Oxford University Press.

Frontal aslant tract Fronto-orbitopolar tract Vertical occipital tract

Fig. 8.6 Tractography reconstruction of three short intralobar bres of the frontal and occipital lobe.

speech (i.e. mutism) to mild altered uency.93,94 e frontal aslant tract is damaged in patients with a non- uent/agrammatic variant of primary progressive aphasia, PNFA,67 and in traumatic brain injury patients with di culties in response inhibition control.105

e frontal orbito-polar bundle is a ventral tract connecting posterior (BA 25 and 11) and anterior orbitofrontal gyri (BA 11) and the frontal pole (BA 10). e posterior orbital gyrus receives inputs from the limbic regions (i.e. amygdala, hippocampus, nucleus basalis of Meynert, olfactory cortex, and insula) and plays an important role in processing olfactory and gustatory inputs and integration of emotions and memories associated with sensory experiences.95

e anterior orbitofrontal cortex receives direct auditory and vis- ual inputs from posterior occipital and temporal cortex through the inferior fronto-occipital and uncinate fasciculus.74,96 e frontal orbito-polar tract represents a transmodal network for binding memories and emotions with olfactory, taste, visual, and auditory inputs. is multisensory association and limbic integration could guide more complex cognitive and behavioural functions, such as reward behaviour associated with sensory and abstract reinforcers (e.g. monetary gain and loss)97 or response inhibition (e.g. go/no-go tasks).98

The vertical occipital bundle of Wernicke was originally described by Sachs in 1892 as an intralobar group of bres con- necting the inferior occipital gyrus (BA 19, 37) with dorsolateral occipital cortex (BA 19) and perhaps posterior parietal cortex (BA 39).25 is tract links dorsal and ventral visual streams and is likely to be involved in reading.27,28

Contribution of white matter to cognition

and behaviour

Optimal cognitive processes rely on an e cient propagation of the action potential along the axons.99 Higher speed of conduction is important, for example, to guarantee a quick response to exter- nal stimuli or to propagate signal to distant regions without delay. e function of white matter tracts is not limited to information transmission but also includes aspects that impact on information processing. Collateral axons, for example, branch o the main axon and generally feed back onto their own neuronal bodies or cortical inhibitory neurons. rough these collateral axons, neu- rons mediate self-modulation of their own ring. Collateral axons and branching are also important to lter, amplify, and distribute signal to multiple cortical and subcortical targets.100 Hence, in a modern view of white matter networks, axonal bres constitute not only conducting devices but also nexuses of convergence and divergence, feedback loops, feed-forward connections, and tran- sition points from serial to parallel processing.101

Historically, the study of white matter function has been hin- dered by the lack of methods for in vivo quantitative measurements of bre anatomy in the central nervous system. Most of the proper- ties of bres have been derived from studies of peripheral nerves, but this may not apply directly to bres of the central nervous sys- tem.50 Tractography can indirectly measure properties of white matter bundles that in uence the speed of signal propagation. Indeed, preliminary evidence of a direct correlation between dif- fusion-derived anatomical features of individual tracts and behav- ioural performances are forthcoming. e two most important biological axonal features a ecting the speed of conduction of the nervous signal are the axonal diameter and its myelination. In gen- eral, axons with larger diameter o er a weaker resistance along the longitudinal axis and therefore facilitate faster conduction along a direction longitudinal to the main axis. Similarly, heavily myelin- ated axons increase the resistance across the membrane and exped- ite faster longitudinal conduction.49,50

While the axonal diameter of bres is generally determined by maturational processes that occur during early brain development and plateau in adolescence, the degree of myelin produced by oli- godendrocytes changes quite rapidly in relation, for example, to the frequency of ring of speci c groups of bres engaged in certain cognitive processes. is explains, for example, why changes in myelin can occur a er intense training.102

Tractography can help advancing our understanding of cogni- tive disorders. In older age, white matter changes occur in relation to reduced number of myelinated bres, gliosis, and ischaemic damage. Depending on the location, white matter changes have a signi cant impact on cognition.103 e study of white matter connections with tractography is becoming an important tool for quantifying tissue damage, perhaps in regions where white mat- ter changes are not visibile on conventional MRI. Furthermore, the use of tractography or tractography-derived atlases could improve localization of white matter damage along critical path- ways. Finally, individual di erences in tract anatomy (e.g. lateral- ization) could have important implications for understanding variability in cognitive and behavioural performances. It may also help to identify patterns of vulnerability and resilience to brain disorders.106


1. Vercelli A, Repici M, Garbossa D, et al. Recent techniques for tracing pathways in the central nervous system of developing and adult mam- mals. Brain Res Bull. 2000;51(1):11–28.

2. Schmahmann JD and Pandya DN. Fiber Pathways of the Brain. Oxford: Oxford University Press, 2006.

3. Morecra RJ, Ugolini G, Lanciego JL, et al. Classic and Contemporary Neural Tract Tracing Techniques. In: H Johansen-Berg and

CHAPTER 8 principles of white matter organization 87

88 SECTION 1 normal cognitive function

TE Behrens. Di usion MRI: From Quantitative Measurement to In Vivo

Neuroanatomy. London: Elsevier, 2009, pp. 273–308.

4. Dell’Acqua F and Catani M. Structural human brain networks: hot top-
ics in di usion tractography. Curr Opin Neurol. 2012;25(4):375–83.

5. Catani M and ytche DH. e rises and falls of disconnection syn-
dromes. Brain. 2005;128(10):2224–39.

6. Reil JC. Die vördere Commissur im großen Gehirn. Archiv für die
Physiologie. 1812;11:89–100.

7. Burdach K. Vom Baue und Leben des Gehirns und Rückenmarks.
Leipzig: Dyk, 1819–26.

8. Ludwig E and Klingler J. Atlas Cerebri Humani. e Inner Structure
of the Brain Demonstrated on the Basis of Macroscopical Preparations.
Boston, MA: Little Brown, 1956.

9. Martino J, Brogna C, Robles SG, et al. (2010). Anatomic dissection of
the inferior fronto-occipital fasciculus revisited in the lights of brain
stimulation data. Cortex. 2010;46(5):691–9.

10. Marchi V and Algeri EG. Sulle degenerazioni discendenti consecutive
a lesioni in diverse zone della corteccia cerebrale. Riv Sper Freniatr Med
Leg Alien Ment. 1886;141–59.

11. Lanciego JL and Wouterlood FG. Neuroanatomical tract-tracing
methods beyond 2000: what’s now and next. J Neurosci Methods.

12. Kuypers HG and Ugolini G. Viruses as transneuronal tracers. Trends
Neurosci. 1990;13(2):71–5.

13. Beaulieu C. e Biological Basis of Di usion Anisotropy. In: H
Johansen-Berg and TE Behrens. Di usion MRI: From Quantitative Measurement to In Vivo Neuroanatomy. London: Elsevier, 2009, pp. 105–26.

14. Conturo TE, Lori NF, Cull TS, et al. Tracking neuronal ber pathways in the living human brain. Proc Natl Acad Sci USA. 96(18):10422–7.

15. Mori S, Crain BJ, Chacko VP, et al. ree-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann Neurol. 1999;45(2):265–9.

16. Basser PJ, Pajevic S, Pierpaoli C, et al. In vivo ber tractography using DT-MRI data. Magnet Resonance Med. 2000;44(4):625–32.

17. Catani M, Howard RJ, et al. Virtual in vivo interactive dissec- tion of white matter fasciculi in the human brain. Neuroimage. 2002;17(1):77–94.

18. Basser PJ, Mattiello J, and LeBihan D. MR di usion tensor spectroscopy and imaging. Biophysical Journal. 1994;66(1):259–67.

19. Catani M, Allin MP, Husain M, et al. Symmetries in human brain language pathways correlate with verbal recall. Proc Natl Acad Sci USA. 2007;104(43):17163–8.

20. Kontis D, Catani M, Cuddy M, et al. Di usion tensor MRI of the corpus callosum and cognitive function in adults born preterm. Neuroreport. 2009; 20(4):424–8.

21. iebaut de Schotten M, Dell’Acqua F, Forkel SJ, et al. A later- alized brain network for visuospatial attention. Nat Neurosci. 2011;14(10):1245–6.

22. Lopez-Barroso D, Catani M, Ripollés P, et al. Word learning is mediated by the le arcuate fasciculus. Proc Natl Acad Sci USA. 2013;110(32):13168–73.

23. Meynert T. A Clinical Treatise on Diseases of the Fore-brain based upon a Study of its Structure, Functions, and Nutrition (trans Bernard Sachs). New York, NY: GP Putnam’s Sons, 1885.

24. Catani MF, Dell’acqua F, Bizzi A, et al. Beyond cortical localization in clinico-anatomical correlation. Cortex. 2012;48(10):1262–87.

25. Sachs H. Das Hemisphärenmark des menschlichen grosshirns.

29. Lawes INC, Barrick TR, Murugam V, et al. Atlas-based segmenta- tion of white matter tracts of the human brain using di usion tensor tractography and comparison with classical dissection. Neuroimage. 2008;39(1):62–79.

30. Ford A, McGregor KM, Case K, et al. Structural connectivity of Broca’s area and medial frontal cortex. Neuroimage. 2010;52(4):1230–7.

31. Catani M. Di usion tensor magnetic resonance imaging tractography in cognitive disorders. Curr Opin Neurol. 2006;19(6):599–606.

32. Catani M, Jones DK, and ytche DH. Perisylvian language networks of the human brain. Ann Neurol. 2005;57(1):8–16.

33. Newhart M, Trupe LA, Gomez Y, et al. Asyntactic comprehension, working memory, and acute ischemia in Broca’s area versus angular gyrus. Cortex. 2012;48(10):1288–97.

34. Perani D, Saccuman MC, Scifo P, et al. Neural language networks at birth. Proc Natl Acad Sci USA. 2011;108(38):16056–61.

35. Wilson SM, Galantucci S, Tartaglia MC, et al. (2011). Syntactic process- ing depends on dorsal language tracts. Neuron. 72(2):397–403.

36. Jacquemot and Scott
37. Breier JI, Hasan K, Zhang W, et al. Language dysfunction a er stroke

and damage to white matter tracts evaluated using di usion tensor

imaging. Am J Neuroradiol. 2008;29(3):483–7.
38. Fridriksson J, Kjartansson O, Morgan PS, et al. Impaired speech repeti-

tion and le parietal lobe damage. J Neurosci. 2010;30(33):11057–61. 39. Petrides M and Pandya DN. Projections to the frontal cortex from the posterior parietal region in the rhesus monkey. J Comp Neurol.

40. Leiguarda RC and Marsden CD. Limb apraxias: Higher-order disorders

of sensorimotor integration. Brain. 2000;123(Pt 5):860–79.
41. Anderson EJ, Jones DK, O’Gorman RL, et al. Cortical network for gaze

control in humans revealed using multimodal MRI. Cereb Cortex. 2011. 42. Johnson PB, Ferraina S, Bianchi L, et al. Cortical networks for visual

reaching: physiological and anatomical organization of frontal and

parietal lobe arm regions. Cereb Cortex. 1996;6(2):102–19.
43. Corbetta M and Shulman GL. Control of goal-directed and stimulus- driven attention in the brain. Nature Rev Neurosci. 2002;3(3):201–15. 44. Goldenberg G and Karnath HO. e neural basis of imitation is body

part speci c. J Neurosci. 2006;26(23):6282–7.
45. Lynch JC and Mountcastle VB, Talbot WH, et al. Parietal lobe mecha-

nisms for directed visual attention. J Neurophysiol. 1977;40(2):362–89. 46. Corbetta MF, Miezin FM, Gordon L, et al. A PET study of visuospatial

attention. J Neurosci. 1993;13(3):1202–26.
47. iebaut de Schotten M, Urbanski M, Du au H, et al. Direct evidence

for a parietal-frontal pathway subserving spatial awareness in humans.

Science. 2005;309(5744):2226–8.
48. Levy R and Goldman-Rakic PS. Segregation of working memory

functions within the dorsolateral prefrontal cortex. Exp Brain Res.

49. Hursh JB. Conduction Velocity and diameter of nerve bers.

Am J Physiol. 1939;127:131–39.
50. Waxman SG and Bennett M. Relative conduction velocities of small

myelinated and non-myelinated bres in the central nervous system.

Nat New Biol. 1972;238(85):217–9.
51. Crosby EC, Humphrey T, and Lauer EW. Correlative Anatomy of the

Nervous System. New York, NY: Macmillian Co, 1962.
52. Nieuwenhuys R, Voogd J, Huijzen C van. e Human Central Nervous

System. Berlin: Springer, 2008.
53. Catani MF, Dell’acqua F, and iebaut de Schotten. A revised limbic sys-

tem model for memory, emotion and behaviour. Neurosci Biobehav Rev.

54. Catani M and iebaut de Schotten M. Atlas of Human Brain

Connections. Oxford: Oxford University Press, 2012.
55. Jones DK, Christiansen KF, Chapman RJ, et al. Distinct subdivisions

of the cingulum bundle revealed by di usion MRI bre tracking: implications for neuropsychological investigations. Neuropsychologia. 2013;51(1):67–78.

56. Raichle ME, MacLeod AM, Snyder AZ, et al. A default mode of brain function. Proc Natl Acad Sci USA. 2001;98(2):676–82.

Leipzig: Verlag Von Georg ieme, 1892.

26. Oishi K, Zilles Z, Amunts K, et al. Human brain white matter atlas:
identi cation and assignment of common anatomical structures in
super cial white matter. NeuroImage. 2008;43(3):447–57.

27. Guevara P, Poupon C, Rivière D, et al. Robust clustering of massive
tractography datasets. Neuroimage. 2011;54(3):1975–93.

28. Yeatman JD, Rauschecker AM, Wandell BA, et al. (2013). Anatomy the visual word form area: adjacent cortical circuits and long-range


white matter connections. Brain Lang. 2013;125(2):146–55.

57. Raichle ME and Snyder AZ. A default mode of brain function: a brief history of an evolving idea. Neuroimage. 2007;37(4):1083–90; discussion 1097–9.

58. Amodio DM and Frith CD. Meeting of minds: the medial frontal cortex
and social cognition. Nat Rev Neurosci. 2006;7(4):268–77.

59. Broyd SJ, Demanuele C, Debener S, et al. Default-mode brain dysfunc-
tion in mental disorders: a systematic review. Neurosci Biobehav Rev.

60. Aggleton JP. EPS Mid-Career Award 2006. Understanding antero-
grade amnesia: disconnections and hidden lesions. Q J Exp Psychol
(Colchester). 2008;61(10):1441–71.

61. Vann SD, Aggleton JP, Maguire EA, et al. What does the retrosplenial
cortex do? Nat Rev Neurosci. 2009;10(11):792–802.

62. Highley JR, Walker MA, Esiri MM, et al. Asymmetry of the uncinate fasciculus: a post-mortem study of normal subjects and patients with
schizophrenia. Cereb Cortex. 2002;12(11):1218–24.

63. Eluvathingal TJ, Hasan KM, Kramer L, et al. Quantitative di usion
tensor tractography of association and projection bers in normally
developing children and adolescents. Cereb Cortex. 2007;17(12):2760–8.

64. Catani M, Jones DK, Donato R, et al. Occipito-temporal connections in
the human brain. Brain. 2003;126(Pt 9):2093–107.

65. Craig MC, Catani M, Deeley Q, et al. Altered connections on the road
to psychopathy. Molecular Psychiatr. 2009;14(10):946–53.

66. Papagno C, Miracapillo C, Casarotti A, et al. What is the role of the
uncinate fasciculus? Surgical removal and proper name retrieval. Brain.
2011;134(Pt 2):405–14.

67. Catani M, Mesulam MM, Jakobsen E, et al. A novel frontal path-
way underlies verbal uency in primary progressive aphasia. Brain.
2013;136(Pt 8):2619–28.

68. Campbell AW. Histological Studies on the Localisation of Cerebral
Function. Cambridge, Cambridge University Press, 1905.

69. Epelbaum S, Pinel P, Gaillard R, et al. Pure alexia as a disconnection
syndrome: new di usion imaging evidence for an old concept. Cortex.

70. Fox C, Iaria G, and Barton J. Disconnection in prosopagnosia and face
processing. Cortex. 2008;44(8):996–1009.

71. ytche DH, Blom JD, and Catani M. Disorders of visual perception.
Journal of neurol, Neurosur Psych. 2010;81(11):1280–7.

72. Du au H, Gatignol P, Mandonnet E, et al. New insights into the
anatomo-functional connectivity of the semantic system: a study using
cortico-subcortical electrostimulations. Brain. 2005;128(Pt 4):797–810.

73. Anwander A, Tittgemeyer, von Cramon DY, et al. Connectivity-based
parcellation of Broca’s area. Cereb Cortex. 2007;17(4):816–25.

74. Forkel SJ, iebaut de Schotten M, Kawadler JM, et al. e anatomy of
fronto-occipital connections from early blunt dissections to contempo-
rary tractography. Cortex. 2014;56:73–84.

75. Catani M. From hodology to function. Brain. 2007;130(Pt 3):602–5.

76. Schmahmann JD, Pandya DN, Wang R, et al. Association bre pathways
of the brain: parallel observations from di usion spectrum imaging and
autoradiography. Brain. 2007;130(Pt 3):630–53.

77. Clarke S. e Role of Homotopic and Heterotopic Callosal Connections in
Humans. Cambridge, MA: MIT Press, 2003.

78. Tomasch J. Size, distribution, and number of bres in the human corpus
callosum. Anat Rec. 1954;119(1):119–35.

79. Aboitiz F, Scheibel AB, Fisher RS, et al. (1992). Fiber composition of the
human corpus callosum. Brain Res. 1992;598(1–2):143–53.

80. Huang H, Zhang J, Jiang H, et al. DTI tractography based parcellation of white matter: application to the mid-sagittal morphology of corpus
callosum. Neuroimage. 2005;26(1):195–205.

81. Hofer S and Frahm J. Topography of the human corpus callosum
revisited—comprehensive ber tractography using di usion tensor
magnetic resonance imaging. Neuroimage. 2006;32(3):989–94.

82. Zarei M, Johansen-Berg H, Smith S, et al. (2006). Functional anatomy
of interhemispheric cortical connections in the human brain. J Anat.

83. Park HJ, Kim JJ, Lee SK, et al. Corpus callosal connection mapping
using cortical gray matter parcellation and DT-MRI. Hum Brain Mapp. 2008;29(5):503–16.

84. Chao YP, Cho KH, Yeh CH, et al. Probabilistic topography of human corpus callosum using cytoarchitectural parcellation and high angular resolution di usion imaging tractography. Hum Brain Mapp. 2009;30(10):3172–87.

85. Talairach J and Tournoux P. Co-planar Stereotaxic Atlas of
the Human Brain: 3-Dimensional Proportional System—An Approach to Cerebral Imaging.
New York, NY: Thieme Medical Publishers, 1988.

86. Turner BH, Mishkin M, Knapp ME, et al. Distribution of the anterior commissure to the amygdaloid complex in the monkey. Brain Res. 1979;162(2):331–7.

87. Demeter S, Rosene DL, Van Hoesen GW, et al. Fields of origin and pathways of the interhemispheric commissures in the temporal lobe of macaques. J Comp Neurol. 1990;302(1):29–53.

88. Gazzaniga MS. Cerebral specialization and interhemispheric com- munication: does the corpus callosum enable the human condition? Brain. 2000;123(Pt 7):1293–326.

89. Glickstein M and Berlucchi G. Classical disconnection studies of the corpus callosum. Cortex. 2008;44(8):914–27.

90. Dejerine J. Anatomie des Centres Nerveux. Paris: Rue et Cie, 1901. 91. Newton JM, Ward NS, Parker GJ, et al. Non-invasive mapping of

corticofugal bres from multiple motor areas—relevance to stroke

recovery. Brain. 2006;129(Pt 7):1844–58.
92. Schmahmann JD and Pandya DN. Disconnection syndromes of

basal ganglia, thalamus, and cerebrocerebellar systems. Cortex.

93. Pen eld W and Rasmussen T. Vocalization and arrest of speech. Arch

Neurol Psychiatry. 1949;61(1):21–7.
94. Bizzi A, Nava S, Ferrè F, et al. Aphasia induced by gliomas growing

in the ventrolateral frontal region: assessment with di usion MR tractography, functional MR imaging and neuropsychology. Cortex. 2012;48(2):255–72.

95. Rolls E. e Functions of the Orbitofrontal Cortex. Oxford: Oxford University Press, 2002.

96. Price JL. De nition of the orbital cortex in relation to speci c connec- tions with limbic and visceral structures and other cortical regions. Ann NY Acad Sci. 2007;1121:54–71.

97. Kringelbach ML. e human orbitofrontal cortex: linking reward to hedonic experience. Nature Rev Neurosci. 2005;6(9):691–702.

98. Iversen SD and Mishkin M. Perseverative interference in monkeys fol- lowing selective lesions of the inferior prefrontal convexity. Exp Brain Res. 1970;11(4):376–86.

99. Filley CM. Neurobiology of hite matter disorders. In: DJ Jones (ed.). Di usion MRI. New York, NY: Oxford University Press, 2011, pp. 19–30.

100. Waxman SG. Regional di erentiation of the axon: a review with spe- cial reference to the concept of the multiplex neuron. Brain Research. 1972;47:269–88.

101. Catani M and MM Mesulam. What is a disconnection syndrome? Cortex. 2008;44(8):911–3.

102. Scholz J, Klein MC, Behrens TE, et al. Training induces changes in white-matter architecture. Nat Neurosci. 2009;12(11):1370–1.

103. Lamar M, Catani M, et al. (2008). e impact of region-spe- ci c leukoaraiosis on working memory de cits in dementia. Neuropsychologia. 2008;46(10):2597–601.

104. Chechlacz M, Gillebert CR, Vangkilde SA, et al. Structural variability within frontoparietal networks and individual di erences in atten- tional functions: an approach using the theory of visual attention. J Neurosci. 2015;35(30):10647–58.

105. Bonnelle V, Ham TE, Leech R, et al. Salience network integrity pre- dicts default mode network function a er traumatic brain injury. Proc Natl Acad Sci USA. 2012;109(12):4690–5.

106. Forkel SJ, iebaut de Schotten M, Dell’Acqua F, et al. Anatomical predictors of aphasia recovery: a tractography study of bilateral peri- sylvian language networks. Brain. 2014;137(7):2027–39.

107. Catani MF, Dell’Acqua F, Vergani F, et al. Short frontal lobe connec- tions of the human brain. Cortex. 2012;48(2):273–91.

CHAPTER 8 principles of white matter organization 89


function. ey may alternatively change voltages in ion channels so as to alter the excitability of the cell. Additionally, the concentra- tion of neurotransmitter in the synaptic cle is regulated not only by catabolic enzymes, for example, monoamine oxidases in the case of the monoamines and acetylcholine esterase in the case of acetylcho- line, but also pre-synaptic transporters that enable reuptake of the released neurotransmitter back into the pre-synaptic cell.

Many factors contribute to the ‘ delity’ of the signalling imping- ing on the post-synaptic cells and involve, for example, neuro- modulatory neurotransmitters that act conditionally on the cell, depending on its current state (see reference 3). ese neuromodu- lators, which include the classical monoamines dopamine (DA), noradrenaline (NA), and serotonin (or 5-hydroxytryptamine, 5-HT), usually tend to have a spatially and temporally less precise mode of action than the amino acid ‘fast signalling neurotransmit- ters’, and may operate over a longer timescale than glutamate or GABA. ey too may work via several receptors, there being over 15 serotonin receptors, for example.2

It is also now clear that more than one neurotransmitter may be released from a single neuron, in contradistinction to Henry Dale’s original principle. is principle of co-transmission, which gener- ally involves a neuropeptide as the co-transmitter, has been shown to hold, for example, for dopamine cells (where the neuropeptide is cholescystokinin), noradrenaline (neuropeptide Y), and acetylcho- line (Ach), vasoactive intestinal polypeptide (VIP). As these neuro- peptides may also play some role in the peripheral nervous system, this exempli es the principle of central and peripheral signalling by the same molecule acting as a hormone as well as a neurotransmit- ter. For more detail on basic neurochemistry and neuropharmacol- ogy the reader is urged to consult Cooper, Bloom, and Roth.2 e main neurotransmitters mentioned above are listed in Table 9.1.

Functions of neurotransmitter systems

and pathways

Although neurotransmitters may participate in a range of func- tions, their distribution nevertheless is not all random in the brain and their anatomical pathways may be quite speci c, o en for evo- lutionary reasons that are not entirely clear (Fig. 9.1). For example, there are two distinct ascending noradrenergic pathways, only one of which richly innervates the neocortex and forebrain. However, there is very sparse innervation of the basal ganglia by noradrena- line, which by contrast receive rich dopaminergic and serotonin- ergic inputs. Indeed, the discoveries concerning innervation of the caudate-putamen by the dopaminergic pathways of the substantia nigra and the production of Parkinson’s disease by degeneration of


Neurochemistry of cognition

Trevor W. Robbins

Cognition and behaviour are among the more obvious outputs of brain functioning and are inextricably linked, not only to themselves, but to neuronal networks that depend ultimately on chemical neurotransmission.1 In fact, less than 70 years ago it was considered controversial to believe that the brain used chemical neurotransmitters at all. It was shortly agreed that only two such substances existed (with excitatory and inhibitory functions), and we have now come to realize that the brain employs probably over 50 such molecules, sometimes in the same neurons.2 e 1960s saw enthusiasm for the ‘chemical coding’ of behaviour, doubtless stimulated by the discovery of the triplet genetic code. However, this is now considered to be a rather naïve viewpoint, given that neurotransmitters can be dispersed in many di erent neuroana- tomical locations in distinct neuronal circuitries with obviously di erent functions, including, for example, the peripheral nervous system, and the now common observation that the same molecule can function as a blood-borne hormone as well as a speci c neuro- transmitter. Incidentally, this does of course imply that a drug spe- ci cally a ecting a single neurotransmitter is bound to a ect more than one function, producing obvious side-e ects of medications.

ere are now agreed criteria for classifying chemical neuro- transmitters, depending on considerations such as whether they are synthesized in neurons, released following action potentials into the synapse, where they may bind to receptor proteins and are eventually metabolized or recycled for example by so-called reup- take systems utilizing transporter molecules.2

Today, most classi cations of neurotransmitters agree that there are ‘fast signalling’ molecules, generally working directly on ion channel (‘ionotropic’) membrane receptors and responsible for the functioning of large-scale neural networks such as those in the cer- ebral cortex, hippocampus, striatum, and cerebellum.2,3 Glutamate is the most prevalent excitatory amino acid neurotransmitter and gamma aminobutyric acid (GABA) the major inhibitory amino acid transmitter employed in such networks. ey have major functions in the control of cortical neuronal activity, including oscillations at various frequencies, and are implicated in such diverse functions as learning and memory and speech on the one hand, and the control of epileptiform activity on the other.

Although it is quite common for computational modelling of neu- ral networks to operate on the assumption that nodes of connec- tions may be switched on or o , corresponding to the likely modes of action of glutamate and GABA respectively, it is evident that these and other neurotransmitter systems function in a far more sophis- ticated way, o en at multiple receptors, both pre- and postsynap- tic and involving biochemical e ects on G-proteins essential to cell

92 SECTION 1 normal cognitive function Table 9.1 Major chemical neurotransmitters

potentiation (LTP), the incremental response shown by neurons consequent upon prior experience of high-frequency, tetanizing stimulation.6 (A decremental response is termed complementarily, long-term depression (LTD).)

ese phenomena were originally found in hippocampal cir- cuitry (dentate gyrus and CA1-3) but have now been characterized in many regions, including the neocortex (including both visual cortex and prefrontal cortex), the amygdala, parts of the striatum, and cerebellum. ese brain regions are of course implicated in diverse aspects of perception and memory as well as other com- ponents of cognition. However, the question is to what extent LTP/ LTD processes actually re ect behavioural learning?

is question was addressed in an important study in which it was shown that D-2-amino-5-phosphonopentanoic acid (AP-5), a competitive antagonist at the glutamate N-methyl-D-asparate (NMDA) receptor subtype, signi cantly impaired learning in a spatial navigation escape task sensitive to hippocampal damage in the rat when infused into the ventricle at doses also blocking LTP measured in vitro in tissue slices.7 Pre-trained, established per- formance was una ected, indicating that the e ects could not be attributed to ancillary processes such as motivation, perception, or motor function. us it was concluded that the NMDA receptor, probably acting as a ‘coincidence detector,’ mediated plasticity or associative learning mechanisms.

ese results have now been con rmed for a number of other learning paradigms, from aversive contextual Pavlovian condition- ing,8 fear-potentiated startle,9 discriminated approach behaviour10 including ‘autoshaping’,11 and experience shaping the development of the visual cortex12 to conditioned taste aversion, and the chick imprinting response.13 ese observations are all consistent with a role for glutamate receptors in many forms of learning and mem- ory, dependent on several distinct brain regions.14

e relative contributions of LTP and LTD to learning in di er- ent systems remains an interesting question. On the one hand, it appears that quite common molecular mechanisms may be impli- cated in super cially di erent forms of learning and memory. One intriguing possible exception may be stimulus-response habit learn- ing, which is generally associated with circuits including the dorsal striatum (speci cally, the putamen). Lovinger15 has described pos- sibly distinct forms of LTP/LTD implicated in striatal mechanisms of goal-directed, as compared to stimulus-response habit, learning.

e ‘post-trial’ paradigm, where drugs are administered to dis- turb the consolidation of memory at some time following training or experience, can be used to dissect the components of underlying memory processes.16 e e ect of such drugs on memory can be measured in a subsequent retention or retrieval test performed some time a er (usually one to three days) initial training (see Fig. 9.2a). If a drug produces de cits—or improvements—in later retention when administered soon a er training but not at a later time-point, including at the time of retention testing itself, this is good evidence for a speci c e ect on memory consolidation. However, if a drug only a ects retention, then it is likely that it is producing general performance e ects, although possibly on memory retrieval pro- cesses. A great deal of evidence indicates that NMDA receptors are implicated in the initial encoding and consolidation of the memory trace, but not in its subsequent retrieval.14

NMDA receptors are implicated in consolidation and also in a related, hypothetical process of ‘reconsolidation’ (Fig. 9.2b), redis- covered through work in experimental animals that may have

Classical neurotransmitters

‘Fast signalling’


Glutamate (excitatory) (GLU)

NMDA, AMPA, Kainate

Gamma-aminobutyric acid (inhibitory) (GABA)


‘Slow modulatory’

Acetylcholine (Ach)

Nicotinic, muscarinic

Dopamine (DA)


Noradrenaline (NA) (norepinephrine)

alpha1,2; beta 1,2

Serotonin (5-hydroxytryptamine, 5-HT)

At least 15, including 5-HT1a, 5-HT1b, 5HT2a, 5-HT2c, 5-HT3, 5-HT6 etc.


Very slow modulators/co-transmitters

Cholecystokinin (CCK)—co-transmitter for DA


Neuropeptide Y—co-transmitter for NA


Vasoactive intestinal polypeptide (VIP)—co-transmitter for Ach


Oxytocin, Vasopressin, etc


Reproduced from Robbins TW, Cognitive psychopharmacology. In: K Ochsner and
S Kosslyn (eds). Handbook of Cognitive Neuroscience, Copyright (2014), with permission from Oxford University Press.

that pathway have led to a considerable research focus on the role of dopamine in motor control.

In experimental terms, the functions of these systems can be stud- ied by the use of speci c ligands, receptor agonists, and antagonists, and by the use of selective neurotoxins such as 6-hydroxydopamine (for DA- and NA-containing cells), 5,7 dihydroxytryptamine, (5-HT cells), and 192-IgG-saporin, the immunotoxin (Ach cells). Additionally, neurotransmitter systems can be studied in combi- nation with other techniques to achieve correlative analyses with behaviour, including positron emission tomography, electrophysi- ology, microiontophoresis, in vivo microdialysis, in vivo voltamme- try, optogenetics, and transgenic mice with knock-out or knock-in of speci c receptor proteins.1,4

Glutamate systems: e neurochemistry of cognition and learning

Hebb was among the rst to consider the network properties of

the brain and how neuronal circuits might participate in percep- tion and learning. A major insight concerned the possible plastic- ity inherent in such networks and its contribution to learning and memory. In particular, he predicted that the coordinated ring of two or more neurons might result in the storage of a memory trace via transient, reverberating neuronal activity that somehow was converted to a longer-term structural change in the nerve cells, biasing them to re in future to similar inputs. Indirect evidence for this type of change was later provided by the discovery of long-term


Ascending Arousal Systems: Neuromodulatory transmitters in the rat brain










Monoaminergic and cholinergic systems in the brain
















Noradrenaline SC

















Midbrain dorsal tegmental system


Fig. 9.1 Ascending monoaminergic and cholinergic arousal systems in the (a) rat and (b) human brain (sagittal section), based on histochemical and immunocytochemical analysis.91,92 Similar systems are conserved in the primate, including human brain. Abbreviations: (a) PFC, prefrontal cortex; MFB, medial forebrain bundle; CTT, central tegmental tract; DNAB, dorsal noradrenergic ascending bundle; VNAB, ventral noradrenergic bundle. A1–A10, catecholamine cell groups. Cx, cortex. Ms, medial septum. VDAB, vertical limb of the diagonal band of Broca; HDAB, horizontal limb of the diagonal band of Broca. NBM, nucleus basalis magnocellularis (cell group Ch4); tpp, pedunculopontine tegmental nucleus (cell group Ch5); dltn, laterodorsal tegmental nucleus (cell group Ch6); ICj, islands of Calleja; SN, substantia nigra; IP, interpeduncular nucleus; DR, dorsal raphé nucleus. DS, dorsal striatum, VS, ventral striatum. B1–B9, indoleamine cell groups. (b) Monoaminergic and cholinergic systems in the human brain. Abbreviations: PFC, prefrontal cortex; NC, neocortex; OB, olfactory bulb; TH, thalamus; DS, dorsal striatum (caudate-putamen); VS, ventral striatum (nucleus accumbens); S, septum; DB, diagonal band of Broca; NBM, nucleus basalis of Meynert; AMY, amygdala; HC, hippocampus; HT, hypothalamus; SN, substantia nigra; VTA, ventral tegmental area; CER cerebellum (nuclei); CER COR, cerebellar cortex. OLF +ENT, olfactory and entorhinal cortex; LAT TEG, lateral tegmental nuclei; origin of the ventral noradrenergic bundle; LC, locus coeruleus; RN, raphé nuclei; SC, spinal cord.
(a) Reproduced from Robbins TW and Everitt BJ. Arousal systems and attention. In: M Gazzaniga (ed.). e Cognitive Neurosciences. pp. 703–20. Copyright (1995), with permission from MIT Press. (b) Reproduced from Heimer L. e Human Brain and Spinal Cord: Functional Neuroanatomy and Dissection Guide. pp. 232–4. Copyright (1983), with permission from Springer.

SC Acetylcholine

94 SECTION 1 (a)

normal cognitive function

Attention, encoding (working memory)


Consolidation Memory

Post-trial treatments

(working memory)

(b) Retention test, (5 minutes)

Pre-trial treatment

Recent evidence suggests that both destabilization and restabi- lization implicate the NMDA receptor, but intriguingly these two processes can be dissociated pharmacologically by GluN2B and GluN2A receptor antagonists, respectively. us the former pro- tects consolidated CS-fear memories from the e ects of amnesic agents,19,20 whereas it is the GluN2A receptor that is necessary for reconsolidation itself.20

Another important question is the role of other glutamate recep- tor subtypes. For example, the changes in neuronal plasticity e ected by NMDA receptors are ultimately mediated by the fast depolarization of post-synaptic cells via the AMPA receptor sub- type.21 However, AMPA receptor antagonists generally cause more general impairments. us, for example, NMDA-receptor blockade within the hippocampus impaired encoding, but not retrieval of avour-place associative learning in rats. Whereas AMPA receptor blockade using CNQX (6-cyano-7-nitroquinoline-2,3-dione) dis- rupted both encoding and retrieval.22

ese di erential e ects of manipulating the NMDA and AMPA receptor have also been shown for potentially ‘declarative’ forms of memory such as recognition. Winters and Bussey23 infused selective NMDA and AMPA receptor antagonists into the perirhinal cortex of rats at various stages of training and performance of an object rec- ognition task. ey found that the NMDA receptor antagonist did not impair initial encoding of the object but did impact on its con- solidation into long-term memory. However, the same treatment had no e ect when made just prior to the retention test, whereas the AMPA receptor antagonist (CNQX) disrupted retrieval, similar to the e ects of these agents on associative memory in the hippocam- pus. Intriguingly, in the amygdala, AMPA receptor antagonism has been shown to have relatively little e ect on memory destabilization or restabilization, despite also impairing retrieval of a CS-fear asso- ciation.20 us, the glutamate receptor subtypes have remarkably speci c e ects on di erent components of memory processes.

Studies with mice that lack the AMPA receptor subunit A have also been shown to have signi cant e ects on spatial working memory tasks (though not in long-term spatial memory), add- ing to previous evidence of NMDA receptors in working memory functions.24 is is of particular interest given that drugs such as the NMDA non-competitive antagonist (and dissociative anaes- thetic) ketamine causes working memory de cits in humans.24

Roles in processes such as working memory for glutamate recep- tors raise the interesting issue of whether other cognitive functions, including so-called executive functions, are mediated by gluta- mate receptors. us, evidence in rats of apparent impairments in attentional set-shi ing following acute or chronic treatment with NMDA receptor antagonists26 may be related to similar di cul- ties with the Wisconsin Card Sorting test exhibited by patients with schizophrenia. It appears likely that most neocortical functions involving processing and plasticity are in uenced by glutamatergic mechanisms; it is a challenging question whether this conclusion could lead to clinical application.

Potential cognitive enhancing e ects of glutamate

receptor agonists

Many important clinical disorders from epilepsy to schizophrenia and Alzheimer’s disease involve disruptions of glutamatergic sig- nalling and so it is logical to ask whether they could be remedied by drugs with appropriate glutamatergic mechanisms. Obvious and


Home cage context (e.g. 1–7 days)


Acquisition trial, 5 minutes



Memory consolidation/reconsolidation processes

Working memory


Long term memory

Pre-trial treatment

Active State (labile) Reconsolidation Inactive State (Stable)



Fig. 9.2 (a) e one- trial learning, post-trial treatment memory design, in which manipulations are made post-trial to de ne time-limited memory consolidation processes, as measured during the memory retention test (see e.g. reference 16). (b) Symmetrical processes of memory consolidation and reconsolidation. Reactivating former consolidated memory traces (e.g. by reminder stimuli) can render their retrieval vulnerable to disruption, e.g. by NMDA receptor antagonists or protein synthesis inhibition, thus ‘erasing’ the memory trace (see also reference 17).

clinical implications in the treatment of neuropsychiatric disor- ders such as post-traumatic stress disorder and drug addiction. Reconsolidation is said to occur when a previously consolidated memory trace becomes ‘active’ upon a reminder cue. It is the pro- cess by which previously consolidated memories become stabi- lized at retrieval and then require ‘restabilization’ to persist in the brain.17

In the destabilized state the memory trace is ‘labile’ and can be disrupted by treatment with protein synthesis inhibitors and other amnesic agents including NMDA receptor antagonists (infused into the amygdala), with the result that memory reten- tion is impaired when tested a few days later. e implication is that when a memory trace becomes active, it undergoes updat- ing and ‘reconsolidation’ or restabilization as an essentially new memory trace.

e reminder cue is necessarily presented in the absence of the event it signals, and so this is akin to one-trial ‘extinction’, an active process by which an association is suppressed (o en resulting in a reduction of behavioural output). Intriguingly, extinction is also NMDA-receptor-dependent. us NMDA antagonists are known to block the extinction of learned fear, again when infused into the amygdala.18 In a complementary fashion, extinction is accelerated by a glutamate receptor agonist, D-cycloserine, a nding that has been used to enhance e ects of behavioural therapy of patients with anxiety disorders.

possibly insurmountable problems include the action of such drugs to produce epileptic seizures and neurodegeneration; however, there are some indications that such ‘cognitive enhancing’ e ects might be feasible. us D-cycloserine, which acts at the strychnine- insensitive glycine recognition site of the NMDA receptor complex to boost NMDA signally, has been shown to improve learning and memory in several situations in rodents and primates. Small bene – cial e ects have also been reported in clinical studies of Alzheimer’s disease and schizophrenia (see reference 14 for a review).

e discovery of another class of glutamate receptors, the metabotropic receptors, also o ers some grounds for optimism in modulation of glutamate-mediated neurotransmission. For exam- ple, animal models of schizophrenia27 and Rett’s syndrome28 have shown bene cial e ects of both mGluR5 receptor potentiators (positive allosteric modulators) and mGluR receptor antagonists. An alternative approach depends on drugs causing positive allos- teric modulations of the AMPA receptor, called ‘AMPA-kines’. ese agents have been tested in both human memory (verbal list learning), where a signi cant improvement was observed in elderly individuals with relatively low baseline levels of performance,29 and also in studies of visual recognition memory in non-human pri- mates. In the latter study, Porrino and colleagues30 demonstrated impressive, dose- and delay-dependent improvements in recogni- tion memory in rhesus monkeys (Fig. 9.3) that were accompanied by changes in cerebral blood ow in the temporal lobe and dorso- lateral prefrontal cortex. However, to date, the use of AMPA-kines as cognitive enhancers has not been validated in a clinical trial.

GABA: Inhibitory neurotransmission

and cognition

GABA is the key inhibitory neurotransmitter in the brain synthe- sised from glutamate by the enzyme glutamic acid decarboxylase (GAD). It is responsible for the e cient functioning of several types of inhibitory interneuron which prevent overactivity in many neural circuits, especially in the cerebral cortex, hippocampus, and striatum (for which GABA-containing medium spiny cells are the major outputs) (see reference 2). Although it is not logically nec- essary for neuronal inhibition to translate into behavioural inhi- bition, it is the case that drugs simulating e ects of GABA-ergic agonists o en have behavioural disinhibitory actions.

Benzodiazepine drugs such as chlordiazepoxide (Librium) and diazepam (Valium) are the best known anxiolytic agents, which also have sedative, amnesic, and anticonvulsant actions. ese drugs act at those GABAA receptors with a particular constella- tion of GABA receptor subunits. us, they act as positive allos- teric modulators and enhance phasic inhibition by improving the e cacy of GABA itself in opening inhibitory chloride channels. e sedative, anticonvulsant, anxiolytic, and amnesic e ects of benzodiazepines appear to depend on di erent con gurations of subunits at the benzodiazepine receptor which are prevalent in dif- ferent brain regions.31 For example, it is thought that the anxiolytic actions depend to a large extent on GABA receptors in the amyg- dala, which is classically associated with fear and anxiety.

By contrast, the amnesic actions appear to be linked to an alpha- 5 subunit in GABA receptor subtypes mainly in the hippocampus. A drug acting speci cally as an inverse agonist at this GABA recep- tor subtype has been shown to antagonize the amnesic e ects of alcohol which partly depend on the activation of GABA receptors.32

CHAPTER 9 neurochemistry of cognition 95 Normal Vehicle

80 **







2 Images


40 C

100 80 60 40


5 *p<0.01, **p<0.001 vs 1–5 sec 6 p<0.01, p<0.001 vs 2 Image


1–5 6–10

11–15 16–20 Delay (sec)

Normal + CX717

21–25 26–30


++ ++

++ ++

(0.8 mg/kg)


1–5 6–10

11–15 16–20 Delay (sec)

Dose-dependent improvements in recognition memory in rhesus monkeys following treatment with an AMPA-kine (CX-717). Recognition memory was measured in a delayed non-matching to sample test that also varies memory load (the length of the list of visual objects that has to be remembered before retention testing). Monkeys were required to remember which of two visual discriminanda is more novel and choose it in a 2-choice test over a previously presented, and hence ‘familiar’ stimulus after various delays between presentation of the sample and the choice test.
Reproduced from PLoS Biology. 3(9), Porrino LJ, Daunais JB, Rogers GA, et al. Facilitation of
task performance and removal of the e ects of sleep deprivation by an ampakine (CX717)
in nonhuman primates. pp. e299, Copyright (2005), with permission from PLOS, reproduced under the Creative Commons CC BY License.

Intriguingly, the amnesic e ects of benzodiazepines do not appear to be secondary to the drugs’ sedative actions as the sleep-inducing or hypnotic actions of certain benzodiazepines (such as triazolam or Halcion) are dependent on an independent GABA receptor subunit population in hind-brain sites distinct from the hippocampus.31

GABA in inhibitory neurons plays an important role in the gen- eration of so-called gamma oscillations in the gamma rhythm com- ponents of the electro-encephalograph (EEG).33 Gamma rhythms are observed in many brain regions during states of wakefulness and sleeping, yet their precise functions and mechanisms are still unknown. Gamma-band rhythms are produced by neuronal inhibi- tion. Gamma oscillations are usually transient and are the product of a coordinated interaction of neuronal excitation and inhibition, detected as local eld potentials. Gamma rhythm is generally cor- related with the irregular ring of single neurons, and the network frequency of gamma oscillations varies extensively.

Gamma oscillations per se have to be distinguished from mere increases of gamma-band power and spiking activity, and their magnitude is modulated by slower rhythms which may serve to

Fig. 9.3

p<0.001 vs 2 Image 21–25 26–30

*p<0.01, **p<0.001 vs Normal Vehicle


Mean % Correct Mean % Correct

96 SECTION 1 normal cognitive function

‘couple’ activity in di erent cortical circuits. Gamma oscillations are thus thought to be important mechanisms for coordinating activity across widespread neural networks such as the hippocam- pus and prefrontal cortex in such behavioural processes as working memory.34 us, cognitive de cits in disorders such as schizophre- nia probably result from the disruption of neuronal population dynamics as a consequence of cortical pathology, including the loss of parvalbumin containing GABA-ergic cortical interneurons.35

Monoamines: Serotonin

(5-hydroxytryptamine, 5-HT)

Serotonin is a ubiquitous and ancient neurotransmitter (even being present in invertebrates such as Aplysia) with over 15 distinct recep- tors. It rami es extensively from cell bodies in the mid-brain dorsal and raphé nuclei to virtually all regions of the mammalian brain (see Fig. 9.1). It has been implicated as a neuromodulator in virtu- ally all behavioural processes from sensory input to motor output, including motivation and cognition.2

Serotonin also plays a central role in mood and emotion, but it is part of major paradox in being sometimes associated with anx- iety when up-regulated and depression when down-regulated, even though these two states overlap considerably.36 Depression—and many anxiety disorders including panic—is o en treated with selective serotonin reuptake inhibitors (such as uoxetine or Prozac), their chronic e ects being associated with up-regulation of serotoninergic function. By contrast, anxiety is sometimes treated with drugs that reduce serotonin release; for example, by acting as agonists at 5-HT autoreceptors (buspirone).

Classically, in animal studies serotonin has also been associated with enhancing the activity of a punishment system, as opposed to a hypothetical (dopamine-modulated) reward system, which medi- ates behavioural suppression or inhibition. is is also consistent with evidence that depletion of serotonin is also linked to behav- ioural disinhibition, in the form of both impulsive behaviour (i.e. premature or risky behaviour), and compulsive behaviour (in the form e.g. of obsessive–compulsive disorder (OCD); OCD is o en treated with high doses of selective serotonin reuptake inhibitors (SSRIs)).37

ese diverse e ects of serotonin are generally considered to be explained by its modulation of distinct systems, perhaps via dif- ferent receptors, but the evidence for this hypothesis is still quite fragmentary. e issue is complicated by the fact that serotonin is implicated in processes as diverse as sensory processing (modu- lated by 5-HT2A receptors, and sometimes hallucinogenic e ects, via 5HT2A agonist drugs such as psilocybin and LSD),38 and eating behaviour, probably mediated via 5-HT2C receptors in the hypo- thalamus.39 ese diverse and apparently non-speci c e ects may nevertheless result from rather speci c modulatory roles of sero- tonin. For example, in explaining the sensory e ects of serotonin modulation it is signi cant that the serotoninergic innervation of the neocortex is heavily biased towards layer 4, that is, the thalamic sensory input (contrasting, e.g. with that of noradrenaline which is mainly biased towards the deeper layers).40

Moreover, serotonin is especially implicated in functions of the ventral prefrontal cortex with its rich serotoninergic innerva- tions. is perhaps explains the special role of serotonin in rever- sal learning which is especially linked to the orbitofrontal cortex (OFC) functioning. us, local depletion of serotonin in the OFC

led to signi cant de cits in reversal learning in marmoset mon- keys which had to learn to shi responding from one visual object to another (previously unrewarded) in order to gain reinforce- ment. is was accompanied by apparent perseverative behaviour and by a tendency to be biased in responding to particular cues.41 Intriguingly, this ‘stickiness’ in behaviour did not extend to shi ing attention between di erent visuoperceptual dimensions present in both stimuli.42 It is possible that these de cits simulate some of the problems exhibited by patients with OCD.

Monoamines: Dopamine: Cognition

and activation

Dopamine (DA) has striking links to behaviour, psychopathology, and neurological disease. e seminal mapping of the mesen- cephalic DA pathways into ramifying mesostriatal, mesolimbic, and mesocortical projections (see Fig. 9.1), as well as the identi – cation of several DA receptors and their signalling pathways have raised important questions about the functions of this important neuromodulatory neurotransmitter.43 e possibly misleading tri- adic division of these projections has suggested discrete and even parallel functions in movement (e.g. Parkinson’s disease, dorsal striatum), reward (e.g. drugs of abuse, nucleus accumbens), and cognition (e.g. schizophrenia and attention de cit/hyperactiv- ity disorder (ADHD), prefrontal cortex). However, although this tripartite parcellation is attractively parsimonious, there is con- siderable evidence for overlapping functions (e.g. of cognition in the caudate-putamen and reinforcement in OFC). Similarly, the mediation of reward by DA-dependent functions of the nucleus accumbens also entails an implication in learning and cognitive decision-making processes.

A key issue is under what states or conditions the central DA systems become active and how this activity a ects cognition, behaviour, and movement. ere are considerable neurochemical data indicating that central DA is a ected by such factors as stress and arousal. A particularly useful principle, applied especially to the understanding of the relationship between DA activity and behavioural or cognitive output is the Yerkes–Dodson Law,44 which generally takes the form of an inverted U-shaped function linking level of arousal (or ‘stress’) with behavioural performance (Fig. 9.4). us, whereas performance at low or high values of arousal is rela- tively poor, it is optimal at intermediate values.

When discussing the functions of the dopamine system, we have employed the term ‘activation’ to describe a similar ‘energetic’ con- struct to that of arousal, which is however meant to capture how dopamine a ects the rate and vigour of behavioural (and cognitive, e.g. thinking) output. Unlike ‘arousal’, activation does not connote a simple wakefulness construct associated with neocortical changes, for example in EEG (cf reference 45). As posited in Robbins and Everitt’s review45 of the considerable empirical data already then available, activation is induced by many related states or stimuli, including food deprivation, ‘stress’, psychomotor stimulant drugs, aversive stimuli such as tail-pinch and foot-shock, novelty and conditioned stimuli, including predictors of appetitive events such as food and also aversive events. e function of ‘activation’ is to enhance behaviour in preparation for the presentation of a goal or reinforcer (whether appetitive or aversive).

Activation a ects processing in target structures innervated by the mesolimbic, mesocortical, and mesostriatal pathways,

‘Difficult task’

Optimal performance

that easy tasks were optimally performed at higher levels of arousal than di cult tasks, suggests it might not be. Recent evidence from Parkinson’s disease has shown that therapeutic doses of L-Dopa can improve some aspects of cognition, while impairing others, even in the same patient.54

(ii) Are there inverted-U shaped functions for the sub-cortical DA systems, as well as for prefrontal DA D1 receptors? Some recent evidence55 suggests that this is the case.

(iii) And, relevant to other neuromodulators such as noradren- aline and acetylcholine to be reviewed below, are their actions on behaviour and cognition also to be described in terms of inverted-U-shaped functions, possibly in other brain regions than the prefrontal cortex or striatum?

Monoamines: Noradrenaline

(NA): Cognition and arousal

e central noradrenergic (NA) systems arise from two major systems in the brain-stem, the dorsal and ventral noradrenergic ascending bundles (Fig. 9.1). e former, arising in the locus coer- uleus, is more likely to be implicated in cognitive function, inner- vating as it does, among other structures, the cerebral cortex and hippocampus. is is of considerable clinical interest, given the implication of NA pathology in such varied disorders as Parkinson’s and Alzheimer’s diseases, Korsako ’s syndrome, post-traumatic stress disorder (PTSD), and attention de cit hyperactivity disorder (ADHD). e ventral noradrenergic bundle, by contrast, inner- vates the hypothalamus and portions of the limbic system and is implicated in vegetative functions. ese systems, as for the other monoamines, are implicated in response to stress and arousal. e locus coeruleus itself plays an important role in sleep–waking and in the production of the EEG and the P300 cortical potential (see reference 56 for a recent review).

Electrophysiological investigations have shown that the locus coeruleus responds mainly to salient stimuli, regardless of their precise temporospatial characteristics. is salience is provided especially by the novelty, as well as the intensity, of stimuli from all of the sensory modalities, and also by conditioning. us, familiar stimuli, which lose salience by habituation, do not activate locus coeruleus NA cells. Overall, the coeruleo-cortical NA projections behave like a classical arousal system, being most active in waking, and least active during REM sleep.57

In view of its extensive forebrain projections, NA, like 5-HT, has been implicated in a variety of functions including arousal, stress responses, anxiety, executive control, and memory consolidation. An early theoretical proposal was that the the locus coeruleus functioned akin to the ‘cognitive arm’ of a central sympathetic gan- glion.58 e relationship between arousal (or the noradrenaline sta- tus) and cognition may also operate according to the inverted-U Yerkes–Dodson principle described above, as shown by Arnsten59 in her studies of e ects of adrenoceptor agents on working memory.

However, a notable hypothesis has been that the coeruleo- cortical NA system enhances selective attention by enhancing ‘signal-to-noise’ processing. Precisely how this is done is not abso- lutely clear, although many studies point to the general reduction in neuronal ring produced by microiontophoresis of NA onto cor- tical cells, which may have the e ect of reducing ‘noise’. Segal and Bloom60 have shown that locus coeruleus stimulation can increase

Arousal, Activation, Stress

Fig. 9.4 e Yerkes–Dodson (1908) inverted U-shaped relationship between levels of arousal (or activation, or stress) and levels of performance on a variety of di erent tasks. Note that optimal performance is obtained at intermediate doses of the drug, Note also that optimal levels of arousal are higher for ‘easy’ than for ‘more di cult’ tasks.
Reproduced from Robbins TW, Cognitive psychopharmacology. In: K Ochsner and S Kosslyn (eds). Handbook of Cognitive Neuroscience. Copyright (2014), with permission from Oxford University Press.

essentially in ‘gain-ampli catory’ mode. In the mesolimbic projec- tions, for example to the ventral striatum, including the nucleus accumbens, the role of enhanced DA activity is to increase respon- siveness to cues paired with reinforcement and thus also to enhance appetitive approach to the goal. is is very similar to Berridge’s concept of ‘incentive salience’46 and is related to other earlier writ- ings on the role of DA in motivation.47

Another major empirical advance has been that the fast phasic ring of cells in the ventral tegmental area and substantia nigra appears to encode an error prediction signal.48 Such a neural signal is highly relevant to some models (Pavlovian or temporal di er- ence) about how we learn new information. us, with training, the phasic DA cell ring occurs in response to conditioned stimuli (e.g. visual ash) that are predictive of reward rather than to the reward itself (e.g. food). However, if the reward is omitted, there is a ‘dip’ in ring, as if the signal encodes an error in the prediction. is pattern of activity conforms to the changes in associative learning described by the Rescorla–Wagner rule.48

ere is an evident need to understand the relative functional contribution of such phasic responses—implicated in plasticity and new, mainly appetitive learning of Pavlovian associations— with the tonic mode of action of the same DA systems assumed to underlie the activational (e.g. motivational) e ects of DA.49,50 It is also unclear at present precisely how DA contributes to aversive learning.

e Yerkes–Dodson principle has been o en criticized in experi- mental psychology for its apparent capacity to account for diverse datasets rather too readily. However, it does conform to many dose- response relationships found for drug e ects on behaviour, which o en have characteristic inverted-U shape functions. e principle was applied initially to important data suggesting that the level of DA D1 receptor activity produced Yerkes–Dodson-like e ects on working memory in both rats and monkeys.51 A more recent manifestation of the principle was shown in work on the catechol- O-methyl transferase polymorphism which hypothetically modu- lates prefrontal DA function and produces a predictable pattern of e ects on working memory performance.52,53

However, these data raise several important issues:

(i) Is the function relating DA to performance the same for all forms of behaviour? e nding of Yerkes and Dodson (1908)

‘Easy task’

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98 SECTION 1 normal cognitive function

or decrease evoked cell ring within terminal regions of the den- tate gyrus of the hippocampus, depending on the salience of the stimulus.

e evidence linking NA to attentional functions, including vigi- lance, has come from two main sources:

. (i)  E ects on attentional performance in a rodent test of sustained attention, the 5-choice serial reaction time task (5-CSRTT). Speci cally, rats with profound forebrain NA deletion were impaired at detecting visual targets when these were tempor- ally unpredictable or in the presence of distracting noise.61

. (ii)  Electrophysiological recording from locus coeruleus NA cells in monkeys during attentional performance. Here the nding was that optimal attentional performance occurred during tonic ring phases, whereas performance was suboptimal dur- ing heightened tonic ring.62

ese e ects on attention may underlie many of the other actions of central NA on functions such as learning, memory, and cognition. For example, considerable evidence links aversive memory consoli- dation to noradrenergic modulation of the amygdala;16 moreover, memory reconsolidation in rats63 and humans64,65 is blocked by the beta adrenoceptor blocker propanolol.

Central NA also contributes importantly to performance by rats on an attentional set-shi ing task where subjects are required to shi their attention from one aspect or dimension (such as its shape or colour) of a complex stimulus to another (a model of the human Wisconsin Card Sort Test of cognitive exibility and pre- frontal cortical functioning mentioned above).66 Whether similar e ects can be shown in humans will depend on whether drugs that selectively activate noradrenergic receptors can be employed. It is of interest that the psychomotor stimulant drug methylphenidate, used (as Ritalin) in the treatment of ADHD, acts not only to block the actions of the dopamine transporter but also the noradrena- line transporter, and so it is possible that both actions contribute to the e ects of methylphenidate to improve attention and working memory, and also to enhance cognitive control or executive func- tion (see review in reference 67).

Atomoxetine is a drug also used in the treatment of ADHD which has more selective actions in acting mainly to block the noradrenaline transporter, thus avoiding the up-regulation of stri- atal DA that potentially contributes to drug abuse following medi- cation by methylphenidate. Atomoxetine has been shown to have notable actions in reducing impulsive behaviour, and thus enhanc- ing cognitive control, in both rodents and humans.68,69 us, even in healthy volunteers, atomoxetine speeded the stop-reaction time, a measure of the ability to cancel an already-initiated motor response. A similar action has been shown in ADHD.70 Moreover, this apparent improvement in inhibitory control appears to depend on activation of the right inferior frontal gyrus, a cortical region previously implicated in cognitive control.71 It is currently a matter of considerable research interest whether common e ects on atten- tion contribute to these e ects on cognitive control, or whether both functions are independently modulated by central NA.

Acetylcholine (Ach): Roles in attention

and cognition

Acetylcholine (Ach) has been considered as a neurotransmitter for almost a century. Subsequent research in both basic and human

neuroscience has strongly implicated Ach in processes of atten- tion and arousal, parallel to analogous roles for the catecholamines (dopamine and noradrenaline). ere are three major cholinergic tracts, including the midbrain dorsal tegmental system with func- tions in the sleep–waking cycle, the basal forebrain (nucleus basa- lis) system, and the adjacent medial septo-hippocampal projections (Fig. 9.1). However, Ach also functions as a neurotransmitter in interneurons, for example, in the striatum.2

Early work showed bene cial e ects of the anticholinesterase physostigmine on attention in rats as measured in a visual tar- get detection procedure, whereas the antimuscarinic cholinergic receptor antagonist, scopolamine impaired it.72,73 Nicotine was later shown to enhance performance in a sustained attention task in non-smoking humans that required detection of rapidly pre- sented (100/min), speci ed sequences of digits at a single loca- tion.74 Converging evidence in humans from studies of the e ects of scopolamine on cognition also implicated possible e ects of the drug on cholinergically mediated attentional processes.75,76 Soon a er these early behavioural demonstrations of Ach involvement in attention, electrophysiological studies of the V1 area of cat showed apparent e ects of Ach to enhance signal processing in recep- tive elds of visual cortical neurons,77 although some subsequent work78 has failed to con rm this.

Damage to the nucleus basalis in rats using either excitotoxic or immunotoxic lesioning procedures, that typically produced sub- stantial loss of cholinergic terminals in the frontal cortex, sub- stantially disrupted 5-CSRTT performance by rats in terms of impaired detection of brief visual events presented randomly at one of ve locations, de cits later shown to be especially evident at longer test sessions. Such impaired discrimination performance could be remedied by systemic administration of optimal doses of physostigmine or nicotine, as well as by cholinergically enriched neural transplants into the rodent cortex (see review by Everitt and Robbins, reference 79).

Further experiments using intracerebral monitoring of Ach with in vivo microdialysis showed the neurotransmitter to be released in the prefrontal cortex when attentional demands were increased.80 Other experiments using di erent measures of attention in rats and mice have generally con rmed the importance of acetylcholine for attentional function. Sophisticated neurochemical studies involv- ing the monitoring via in vivo voltammetry of choline release as a surrogate index of acetylcholine81 have also been linked to target detection, and its improvement by alpha-4, beta-2 nicotinic ago- nists.82 Indeed, the evidence implicating selective e ects of Ach in attentional performance in rodents is perhaps more convincing than for any of the other major neurotransmitters.

Parallel evidence of cholinergic involvement in attention can be found from investigations of rhesus monkeys with lesions of the nucleus basalis that exhibit speci c de cits in Posner’s test of cov- ert attentional orienting. is nding is consistent with evidence that nicotine enhances attentional orienting in both monkeys and humans, as well as from evidence of augmentation of responses of primary visual cortex neurons in their receptive elds to attended stimuli by iontophoretically applied Ach.83

e demonstration that the intellectual status of patients with Alzheimer’s disease is related to cortical cholinergic loss.84 has highlighted a possible role for cholinergic agents in its remediation. e possible relevance of the basic neuroscience ndings on ace- tylcholine reviewed above was demonstrated by the improvements

produced by the anticholinesterase drug tacrine on performance of patients with probable Alzheimer’s disease on the same ve- choice serial reaction time task as used in rodents, with concomi- tant improvements in clinical rating scales of attention ‘alerting’.85 Subsequent clinical experience has shown that such medications (e.g. rivastigmine) are also e ective in the treatment of the uctu- ating attentional capacities of patients with Lewy body dementia, who tend to have even more profound reductions of cholinergic function than do patients with Alzheimer’s disease.86

Ach is also implicated in memory functions, including work- ing memory, recognition memory, and semantic retrieval, but it remains to be resolved whether its e ects on attention contrib- ute to these actions, as seems plausible, for example, for memory encoding or resisting interference in working memory. ere may be speci c e ects on memory-related processes, perhaps medi- ated by similar neuronal mechanisms to those of attention, but in brain regions more specialized for memory processing, such as the hippocampus.87

New vistas on novel

neurotransmitters: Neuropeptides

is brief review has considered functions in cognition of the main ‘fast signalling’ (i.e. glutamate and GABA) and ‘neuromodula- tory’ (i.e. the monoamines and acetylcholine) neurotransmitters. As mentioned in the introduction to this chapter, there are at least 50 substances that have neurotransmitter properties and more are being discovered by the year. e largest category that we have not considered in any detail are the neuropeptides, whose actions are generally slow but o en speci c and hormone-like.2 Examples include the gut hormones cholescystokinin and vasoactive intesti- nal polypeptide, adrenaline, corticotrophic releasing factor (CRF), vasopressin, and the opioid peptides such as enkephalin and beta endorphin. Many of these substances have functions in aspects of memory, in conjunction, for example with NMDA receptors and central adrenoceptors. However, there is no very great evidence of major roles in cognitive functions per se, although possible roles, for example in stress, will have indirect actions on such cognitive functions as working memory via the Yerkes–Dodson like in u- ence. Analogously, the discovery of orexin, a hypothalamic neu- ropeptide, has been shown to have functions in motivation and arousal that may similarly impinge indirectly on cognition.

Perhaps one of the most intriguing discoveries has been the pos-

sible role of oxytocin in social cognition. is peptide has been

shown to improve social recognition memory not only in ani-

mals, but also in human subjects, where there is evidence of selec-

tive improvement of memory for faces but not non-facial stimuli.89 A classic study indicated that oxytocin administered to humans actually enhanced ‘trust’ in an economic game designed to meas- ure this.90 Such discoveries, with implications for the treatment of disorders such as autism and possibly even of some neurodegen- erative conditions, indicate rich promise for the future study of the psychopharmacology of cognition, and its therapeutic application.

Further reading

Robbins TW. Cognitive psychopharmacology. In: K Ochsner and S Kosslyn (eds). Handbook of Cognitive Neuroscience. Oxford: Oxford University Press, 2013, pp 401–18.

Robbins TW. e neuropsychopharmacology of attention. In: K Nobre and S Kastner (eds). Handbook of Attention. Oxford: Oxford University Press, 2013, pp. 509–40.


1. Meyer J and Quenzer LF. Psychopharmacology: Drugs, e Brain, and Behavior. Sutherland, MA: Sinaeuer Associates, 2005.

2. Cooper JR, Bloom FE, and Roth RH. Biochemical Basis of Neuropharmacology, 8th edn. Oxford: Oxford University Press, 2003.

3. Iversen LL and Goodman EC (eds). Fast and Slow Chemical Signalling in the Nervous System. Oxford: Oxford University Press, 1986.

4. Squire, LR, Berg D, Bloom FE, et al. (eds). (2013) Section II. Cellular and Molecular Neuroscience in Fundamental Neuroscience, 4th edn. New York, NY: Elsevier, 2013.

5. Hebb DO. e Organization of Behavior: A Neuropsychological eory. New York, NY: John Wiley and Sons, 1950.

6. Bliss TV and Collingridge GL. A synaptic model of memory: long-term potentiation in the hippocampus. Nature. 1993;361:31–3.

7. Morris RG. Selective impairment of learning and blockade of long-term potentiation by an N-methyl-D-aspartate receptor antagonist, AP5. Nature. 1986;319:774–6.

8. Young SL, Bohenek DL, Fanselow MS. NMDA processes medi-
ate anterograde amnesia of contextual fear conditioning induced by hippocampal damage: Immunization against amnesia by context pre- exposure. Behavioural Neuroscience. 1994;108:19–29.

9. Miserendino MJD, Sananes CB, Melia KK, et al. Blocking of acquisition but not expression of conditioned fear-potentiated startle by NMDA antagonists in the amygdala. Nature. 1990;345:716–18.

10. Burns LH, Everitt BJ, Robbins TW. Intra-amygdala infusion of the N-methyl-Daspartate receptor antagonist AP5 impairs acquisition but not performance of discriminated approach to an appetitive CS. Behavioural Neural Biology. 1994;61:242–50.

11. Dalley JW, Lääne K, eobald DEH, et al. Time-limited modulation of appetitive Pavlovian memory by D1 and NMDA receptors in the nucleus accumbens. Proc Natl Acad Sci USA. 2005;102:6189–94.

12. Carmignoto G and Vicini S. Activity-dependent decrease in NMDA receptor responses during development of the visual cortex. Science. 1992;258:1007–11.

13. McCabe BJ, Davey, JE, and Horn G. Impairment of learning by local- ized injection of an N-methyl-D-aspartate receptor antagonist into the hyperstriatum ventrale of the domestic chick. Behav Neurosci. 1992;106(6):947–53.

14. Robbins TW and Murphy ER. Behavioural pharmacology: +40 years of progress and a focus on glutamate receptors. Trends Pharmacol Sci. 2006;27:141–8.

15. Lovinger DM. Neurotransmitter roles in synaptic modulation, plasticity and learning in the dorsal striatum. Neuropharmacol. 2010;58:951–61.

16. McGaugh JL. Memory—a century of consolidation. Science. 2000;287:248–52.

17. Nader K. Memory traces unbound. Trends Neurosci. 2003;26(2):65–72. 18. Falls WA, Miserendino M, and Davis M. Extinction of fear-potentiated

startle: Blockade by infusion of an NMDA antagonist into the amyg-

dala. J Neurosci.1992;12:854–63.
19. Ben Mamou C, Gamache G, and Nader K. NMDA receptors are critical

for unleashing consolidated auditory fear memories. Nature Neurosci.

20. Milton AL, Merlo E, Ratano P, et al. Double dissociation of the

requirement for GluN2B- and GluN2A-containing NMDA receptors in the destabilization and restabilization of a reconsolidating memory. J Neurosci.2013;16;33(3):1109–15.

21. Kew JN and Kemp, JA. Ionotropic and metabotropic glutamate receptor structure and pharmacology. Psychopharmacol. 2005;179:4–29.

22. Day M, Langston R, and Morris RGM. Glutamate-receptor- mediated encoding and retrieval of paired-associate learning. Nature. 2003;424:205–09.

CHAPTER 9 neurochemistry of cognition 99

100 SECTION 1 normal cognitive function

23. Winters BD and Bussey TJ. Glutamate receptors in perirhinal cortex mediate encoding, retrieval, and consolidation of object recognition memory. J Neurosci. 2005;25:4243–51.

24. Schmitt WB, Deacon RM, Seeburg PH, et al. A within-subjects, within- task demonstration of intact spatial reference memory and impaired spatial working memory in glutamate receptor-A-de cient mice.
J. Neurosci. 2003; 23: 3953–9.

25. Krystal JH, Karper LP, Selbyl JP, et al. Subanesthetic e ects of
the noncompetitive NMDA antagonist, ketamine, in humans. Psychotomimetic, perceptual, cognitive, and neuroendocrine responses. Arch Gen Psychiatry. 1994;51:199–214.

26. Stefani MR, Groth K, Moghaddam B. Glutamate receptors in the rat medial prefrontal cortex regulate set-shi ing ability. Behavioural Neuroscience. 2003;117:728–37.

27. Gastambide F, Cotel MC, Gilmour G, et al. Remediation of rever- sal learning de cits in the neurodevelopmental MAM model of schizophrenia by a novel mGlu5 positive allosteric modulator. Neuropsychopharmacol. 2012;37:1057–66.

28. Zoghbi HY and Bear MF. Synaptic dysfunction in neurodevelopmen- tal disorders associated with autism and intellectual disabilities. Cold Spring Harbor Perspectives in Biology 2012;4:a009886 1–22.

29. Lynch G. Memory enhancement: e search for mechanism-based drugs. Nature Neurosci. 2002;5(Suppl):1035 –8.

30. Porrino LJ, Daunais JB, Rogers GA, et al. Facilitation of task perform- ance and removal of the e ects of sleep deprivation by an ampakine (CX717) in nonhuman primates. PLoS Biology. 2005;3(9):e299.

31. Mohler H. (2007). Functional relevance of GABA-A receptor subtypes. In: S Enna and H Mohler (eds). e Receptors: e GABA Receptors, 3rd edn. Totowa, NJ: Humana Press, 2007, pp. 23–40.

32. Nutt DJ, Besson M, Wilson SJ, et al. Blockade of alcohol’s amnestic activity in humans by an alpha5 subtype benzodiazepine receptor inverse agonist. Neuropharmacol. 2007;53(7):810–20.

33. Bartos M, Vida I, and Jonas P. Synaptic mechanisms of synchronized gamma oscillations in inhibitory interneuron networks. Nature Rev Neurosci. 2007;8:45–56.

34. Buczaki G. Rhythms of the Brain. New York, NY: Oxford University Press, 2006.

35. Lewis DA, Cho RY, Carter CS, et al. Sub-unit-selective modulation of GABA Type-A receptor neurotransmission in schizophrenia. Am J Psychiat. 2008;165:1585–93.

36. Cools R, Roberts AC, and Robbins TW. Serotoninergic regulation of emotional and behavioural control processes. Trends Cogn Sci. 2008;12:31–40.

37. Boureau YL and Dayan P. Opponency revisited: competition and co- operation between dopamine and serotonin. Neuropsychopharmacol. 2011;36:74–97.

38. Titler M, Lyon RA, and Glennon RA. Radioligand binding evidence implicates the brain 5HT2 receptor as a site of action for LSD and phe- nylisopylamine hallucinogens. Psychopharmacol. 1988;94:213–16.

39. Nonogaki K, Strack AM, Dallman MF, et al. Leptin-independent hyper- phagia and type 2 diabetes in mice with a mutated serotonin 5-HT2C receptor gene. Nature Med. 1998;4:1152–6.

40. Morrison JH. , Foote SL, Molliver ME et al Noradrenergic and serotonergic bers innervate complementary layers in monkey pri- mary visual cortex: an immunohistochemical study Proc. Nat. Acad. Sci,1982: 79:2401–2405.

41. Clarke HF, Dalley JW, Cro s HS, et al. Cognitive in exibility a er pre- frontal serotonin depletion. Science. 2004;304:878–80.

42. Clarke HF, Walker SC, Cro s HS, et al. Prefrontal serotonin depletion a ects reversal learning but not attentional set shi ing. J Neurosci. 2005;25:532–38.

43. Robbins TW. From behaviour to cognition: functions of mesostriatal, mesolimbic and mesocortical dopamine systems. In: LL Iversen, SD Iversen, SB Dunnett, et al. (eds). Dopamine Handbook. Oxford: Oxford University Press, 2010, pp. 203–14.

44. Yerkes RM and Dodson JD. e relation of strength of stimulus to rapidity of habit-formation. Journal of Comparative Neurology and Psychology 1908; 18: 459–82.

45. Robbins TW and Everitt BJ. Functions of dopamine in the dorsal and ventral striatum. In: TW Robbins (ed.). Seminars in the Neurosciences. London: Saunders, 1992, pp. 119–27.

46. Berridge KC. What is the role of dopamine in reward today? Psychopharmacol. 2006;191:391–432.

47. Crow TJ. Speci c monoamine systems as reward pathways. In: A Wauquier and ET Rolls (eds). Brain-Stimulation Reward. Amsterdam: North-Holland, 1976, pp. 211–38.

48. Schultz W. Getting formal with dopamine and reward. Neuron. 2002;36:241–53.

49. Grace A. Phasic versus tonic dopamine release and the modulation of dopamine system responsivity: a hypothesis for the etiology of schizo- phrenia. Neurosci. 1991;41:1–24.

50. Niv Y, Daw ND, Joel D, et al. Tonic dopamine: Opportunity costs and the control of response vigor. Psychopharmacol. 2006;191:507–20.

51. Williams GV and Goldman-Rakic PS. Modulation of memory elds by DA D1 receptors in prefrontal cortex. Nature. 1995;376:572–5.

52. Egan MF, Goldberg TE, Kolachana BS, et al. E ect of COMT Val108/ 158 Met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci USA. 2001;98:6917–22.

53. Mattay VS, Callicott JH, Fera F, et al. Catechol-o-methyltransferase val (158)-met genotype and individual variation in the response to amphet- amine. Proc Natl Acad Sci USA. 2003;100:6186–91.

54. Cools R, Barker R., Sahakian BJ, et al. Enhanced or impaired cognitive function in Parkinson’s disease as a function of dopaminergic medica- tion and task demands. Cerebral Cortex. 2001;11:1136–43.

55. Clatworthy PL, Lewis SJG, Brichard L, et al. Dopamine release in dis- sociable strital subregions predicts the di erent e ects of oral methyl- phenidate on reversal learning and spatial working memory. J Neurosci. 2009;29:4690–6.

56. Chamberlain SR and Robbins TW. Noradrenergic modulation of cogni- tion: erapeutic considerations. J Psychopharmacol. 2013;27:694–718.

57. Aston-Jones G, Chiang G, and Alexinsky T. Discharge of norepinehrine locus coeruleus neurons in behaving rats and monkey suggest a role in vigilance. Prog Brain Res. 1991;8:501–20.

58. Amaral DG and Sinnamon HM. e locus coeruleus. Neurobiology of a central noradrenergic nucleus. Prog Neurobiol. 1977;9:147–96.

59. Arnsten AFT. Stress signalling pathways that impair prefrontal cortex structure and function. Nature Neurosci. 2009;10:410–22.

60. Segal M and Bloom FE. e actions of norpepinephrine in the rat hippocampus. IV e e ects of locus coeruleus stimulation on evoked hippocampal unit activity. Brain Res. 1976;107:513–25.

61. Carli M, Robbins TW, Evenden JL, et al. E ects of lesions to ascending noradrenergic neurones on performance of a 5-choice serial reaction task in rats; implications for theories of dorsal noradrenergic bundle function based on selective attention and arousal. Behav Brain Res. 1983;9:361–80.

62. Rajkowski J, Majczynski H, Clayton E, et al. Activation of Monkey locus coeruleus neurons varies with di culty and performance in a target detection task. J Neurophysiol. 2004;92:361–71.

63. Debiec J and LeDoux JE. Disruption of consolidation but not consoli- dation of auditory fear conditioning by noradrenergic blockers in the amygdala. Neurosci. 2004;129:267–72.

64. Schwabe L, Nader K, Wolf OT, et al. Neural signature of reconsolidation impairments by propanolol in humans. Biol Psychiat. 2012;71:380–6. 65. Lonergan MH, Olivea-Figueroa LA, et al. Propanolol’s e ects on the

consolidation and reconsolidation of long term emotional mem- ory in healthy participants: a meta-analysis. Journal of Psychiatry & Neuroscience 2013;38:222–31.

66. Lapiz MD and Morilak DA. Noradrenergic modulation of cognitive function in rat medial prefrontal cortex as measured by attentional set shi ing capability. Neurosci. 2006;137:1039–49.

67. Del Campo N, Chamberlain SR, Sahakian BJ, et al. e roles of dopa- mine and noradrenaline in the pathophysiology and treatment of attention-de cit hyperactivity disorder. Biol Psychiat 2011;69:145–57.

68. Robinson ESJ, Eagle DM, Mar AC, et al. Similar e ects of the selective noradrenaline reuptake inhibitor atomoxetine on three distinct forms of impulsivity in the rat. Neuropsychopharmacol. 2008;33:1028–37.

69. Chamberlain SR, Müller U, Blackwell AD, et al. Neurochemical modu- lation of response inhibition and probabilistic learning in humans. Science. 2006;311:861–3.

70. Chamberlain SR, Del Campo N, Dowson J, et al. Atomoxetine improved response inhibition in adults with attention-de cit/hyperactivity disor- der. Biol Psychiat. 2007;62:977–84.

71. Chamberlain SR, Hampshire A, Müller U, et al. Atomoxetine modulates right inferior frontal activation during inhibitory control: A pharma- cological functional magnetic resonance imaging study. Biol Psychiat. 2009;65:550–55.

72. Warburton DM and Brown K. Attenuation of stimulus sensitivity induced by scopolamine. Nature. 1971;230:126–7.

73. Warburton DM and Brown K. Facilitation of discrimination per- formance by phsyostigmine sulphate. Psychopharmacologia (Berl.). 1972;27:277–84.

74. Wesnes K and Warburton DM. E ects of scopolamine and nicotine on human rapid information processing performance. Psychopharmacol. 1984;82:147–50.

75. Broks P, Preston GC, Traub M, et al. Modelling dementia: e ects of sco- polamine on memory and attention. Neuropsychologia. 1988;26:685–700.

76. Sahakian BJ. Cholinomimetics and human cognitive performance.
In: LL Iversen, SD Inversen, and SH Snyder (eds). Handbook of Psychopharmacology, Vol 20. New York, NY: Plenum, 1988, pp. 393–424.

77. Sillito AM and Kemp JA. Cholinergic modulation of the functional organization of the cat visual cortex. Brain Res. 1983;289:143–55.

78. Zinke W, Roberts MJ, Guo K, et al. Cholinergic modulation of response properties and orientation tuning of neurons in primary visual cortex of anaesthetized marmoset monkeys. Eur J Neurosci. 2006;24:314–28.

79. Everitt BJ and Robbins TW. Central cholinergic systems and cognition. Annu Rev Psychol. 1997;48:649–84.

80. Dalley JW, McGaughy J, O’Connell MT et al. Distinct changes in cortical acetylcholine and noradrenaline e ux during contingent and

noncontinent performance of a visual attentional task. J. Neurosci.

81. Parikh V, Kozak R, Martinez V, et al. Prefrontal acetylcholine release

controls cue detection on multiple timescales. Neuron. 2007;56:141–54. 82. Hasselmo ME and Sarter M. Modes and models of forebrain cholinergic

modulation of cognition. Neuropsychopharmacol. 2011;36:52–73. 83. Witte EA, Davidson MC, and Marrocco, RT. E ects of altering brain

cholinergic activity on covert orienting of attention: comparison of

monkey and human performance. Psychopharmacol. 1997;132:324–34. 84. Perry E, Walker M, Grace J, et al. Acetylcholine in mind: a neu- rotransmitter correlate of consciousness. Trends in Neuroscience

85. Sahakian BJ, Owen AM, Morant NJ, et al. Further analysis of the

cognitive e ects of tetrahydroaminoacridine (THA) in Alzheimer’s disease: assessment of attentional and mnemonic function using CANTAB. Psychopharmacol. 1993;110:395–401.

86. Emre M, Aarsland D, Albanese A, et al. Rivastigmine for dementia associated with Parkinson’s disease. N Engl J Med. 2004;351:2509–18.

87. Hasselmo ME. e role of acetylcholine in learning and memory. Curr Opin Neurobiol. 2006;16:710–15.

88. Bielsky IF and Young LJ. Oxytocin, vasopressin and social recognition in mammals. Peptides 2004;25(9):1565–74.

89. Rimmele U, Hediger K, Heinrichs M, et al. Oxytocin makes a face in memory familiar. J Neurosci. 2009;2(1):38–42.

90. Kosfeld M, Heinrichs M, Zak P, et al. Oxytocin increases trust in humans. Nature. 2005;435:673–6.

91. Dahlstrom A and Fuxe K Evidence for the existence of monoamine- containing neurons in the central nervous system. Acta Physiol Scand 1964;62:1–55.

92. Woolf NJ, Eckenstein F, and Butcher LL Cholinergic systems in the rat brain: I. projections to the limbic telencephalon. Brain Res Bull. 1984; 13:751–84.

CHAPTER 9 neurochemistry of cognition 101


Cognitive dysfunction


Bedside assessment of cognition

Seyed Ahmad Sajjadi and Peter J. Nestor


As with any clinical problem, the history usually provides the most valuable information for assessing suspected cognitive disorders. e key di erence with a history in suspected dementia, compared to other medical consultations, is that cognitive impairment can mean that history from the patient is incomplete or unreliable. For this reason, collateral history from an informant such as a spouse or other individual with close contact to the patient is essential. is is equally true for patients that fall into the ‘worried well’ category who, although cognitively intact and therefore able to tell their own story, may provide a distorted view of the severity of their symptoms. In such instances, an informant can help by providing independent observation of the patient’s ability to manage in everyday life.

A bedside cognitive assessment complements the history and is used to test hypotheses emerging from the patient/informant inter- view regarding the suspected clinical syndrome. Bedside cognitive testing can be impossible to interpret if one does not have a clear understanding of how cognitive abilities in one domain can have knock-on e ects to other domains. For instance, a test purporting to examine executive function may be impossible for an aphasic patient if the test depends on comprehension of instructions or detailed verbal responses. One must be aware, therefore, that a ‘cognitive hierarchy’ exists. In other words, relatively preserved function in particular cognitive domains can be a prerequisite for satisfactory performance of others.

e most striking example of this hierarchy is the necessity of adequate attention for the reliable assessment of all other cognitive domains. In the outpatient setting, it is seldom relevant to examine attention formally in order to decide if further testing can proceed because it is usually obvious from talking to the patient that a pro- found attention de cit is not present. It is also unlikely that, in the outpatient environment, a patient will attend who is su ering from a major delirium. Inpatient referrals for cognitive assessment, how- ever, frequently have reduced arousal and attention de cits in the context of an acute confusional state (delirium) making further in- depth assessments futile. Severe aphasia should also be viewed as an exclusion to further testing in other domains that are language- dependent. Obviously, it is prudent to ensure satisfactory state of basic visual and auditory abilities prior to embarking upon assess- ments of those aspects of cognitive function that are reliant upon these sensory modalities.

Instruments for global assessment

of cognition

Several cognitive assessment tools are available that provide a global score for cognition. Although more expansive batteries will

provide more information, there will be a time penalty; the choice of which battery to use, therefore, mostly depends on local logistical factors—in other words how much time is available to administer a battery. Table 10.1 provides a summary of the briefer assessment tools that are possible to integrate into a standard consultation, and their main pros and cons.

Importantly, a bedside battery can provide invaluable informa- tion about the stage of illness. To this end, incorporating a global battery is particularly useful as it provides a numerical score that can be used to track change over time and provides a straight- forward way of communicating severity to colleagues. e utility of these points cannot be overemphasized. Compiling a medical report in which cognitive assessment is communicated solely on the basis of what the patient could or could not do over a range of ad hoc bedside cognitive assessments can make it impossible for a third party to judge the severity of the impairment. It is impor- tant to stress, however, that the numerical summary scores derived from these batteries are not directly comparable across di erent dementia syndromes. For instance, a score of 25/30 on the Mini- Mental State Examination (MMSE)1 in a typical presentation of Alzheimer’s disease does not necessarily indicate the same level of impairment in everyday life as it would in a behavioural presen- tation of frontotemporal dementia. Using this example, a patient with Alzheimer’s disease and an MMSE of 25/30 will typically have memory impairment but nonetheless, remains fairly independent, whereas a patient with behavioural variant frontotemporal demen- tia with this score, may require high levels of assistance. Within diagnostic categories, however, these scores can be very useful in forming a mental picture of where a patient stands in the course of the illness and, most helpfully, they can be repeated in individual patients to track change over time.

In many instances, a careful history and a global measure are all one needs to make a reasonably con dent diagnosis. Moreover, in situations where the global measure is not adequate to reach a diag- nosis, the pattern of the patient’s performance provides a starting point to tailor cognitive tests of interest for the individual.

Problem oriented cognitive assessment Attention and orientation

Preserved attention and orientation are prerequisites for normal cognitive function and impaired orientation is one of the hallmarks of delirium. Orientation is typically assessed by testing awareness of time and place (and person). Time orientation is speci cally assessed by asking the date, time of day, day of the week, month, season, and year. Place orientation includes items such as town, state/county, name of the hospital, oor, ward, etc. Most of these questions are well covered by the global assessment instruments

106 SECTION 2 cognitive dysfunction
Table 10.1 Popular global bedside cognitive assessment tools


Description (cut-o point for dementia)




Brief 10-item assessment tool (6–8/10)

Short screening tool for identi cation of cognitive problems; easy to use on general medical wards and in primary care setting

Brevity means it can only be used for very crude staging


Scored out of 30, e most widely used cognitive assessment tool (24/30)

Widely recognized test; objective scoring criteria; very useful staging procedure; brief

Heavily biased to verbal domain; not suitable for di erential diagnosis; not sensitive to very mild impairments


Scored out of 30, aimed at detection of early dementia (26/30)

Relatively comprehensive albeit brief assessment tool; not biased towards particular cognitive domain

Not suitable for patients at the more advanced stages of dementia


Scored out of 100, ACE-III is the most recent version of the test (82–88/100)

Robust validation in various neurodegenerative conditions; appropriate for tracking change; sensitive to subtle cognitive impairment and di erential diagnosis

Too long for some clinical environments

Source data from AMTS: Abbreviated Mental Test Score; MMSE: Mini-Mental State Examination; MoCA: the Montreal Cognitive Assessment; ACE-R: Addenbrooke’s Cognitive Examination-revised.

discussed above. Typically, patients with early degenerative diseases are more impaired in time orientation than place, though the latter is also frequently impaired in more advanced stages especially if the assessment is being carried out far from their home (in which case, patients may o en confuse the home town and local hospital with their present location).

One exception is the syndrome of semantic dementia in which one can occasionally encounter patients who are fully oriented in time, but, owing to the semantic de cit, cannot name town, state/ county, name of hospital, etc. Person orientation (i.e. name) is sel- dom informative in the outpatient setting. When an individual can- not produce their own name in the context of an organic disorder, it typically indicates that they are so demented or delirious as to be unable to respond to any verbal instruction. Apparent ignorance of one’s own name in someone who is otherwise capable of communi- cating typically indicates a psychogenic state.

Common bedside tests of attention include spelling a ve-letter word, such as ‘world’, backwards (included in the MMSE), and serial 7s (‘take 7 from 100 and keep going down by 7’, included in both MMSE and MoCA). Forward and backward digit span and recitation of the months of the year or the days of the week in reverse order are further examples. e choice of the appropri- ate test is partly dictated by the presumed cognitive syndrome. For instance, in suspected dominant (le ) hemisphere syndromes such as various types of aphasia one should opt for less language taxing tests such as digit span. Vigilance is another way of assessing atten- tion and concentration. For instance, the examiner asks the patient to listen for a particular letter of the alphabet whilst they read out a list of random letters with the target letter appearing frequently but unpredictably in the list (included in the MoCA). e patient indicates the occurrence of the target letter by tapping each time the letter is read.

Attention testing is clinically useful to monitor change in patients with delirium, such as metabolic encephalopathies. For this pur- pose, digit span—which measures attention and working memory capacity—can be particularly helpful because it provides a quan- ti able score. In testing digit span, individual numbers should be uttered separately in a monotonous way at a rate of one digit/ second (in contrast to grouping numbers in clusters as one would in giving a telephone number). Normal digit span is at least six

forwards, with backward digit span being one or two digits less than the forward span.

Declarative memory

Episodic memory

Episodic memory refers to memory for speci c events from one’s past—such as what one did this morning, on one’s last holiday, one’s wedding day, and so on. Episodic memory impairment is a de n- ing feature of early-stage typical Alzheimer’s disease and is also frequently observed in non-Alzheimer dementias. It is the most common reported problem in a cognitive disorders clinic. It is, therefore, important to have a plan for how it should be examined.

Episodic memory can, in turn, be divided to retrograde, re ect- ing one’s ability to remember events from before the onset of the memory-impairing disease, and anterograde meaning the ability to acquire new memories a er disease onset. Except for rare exam- ples of highly restricted mesial temporal lobe lesions causing rela- tively pure anterograde de cits, both anterograde and retrograde memory are a ected simultaneously in most amnestic syndromes including Alzheimer’s disease. is is an important and clinically useful point for assessing memory at the bedside. In clinic, one o en hears statements from informants of the type ‘it’s his short- term memory, the long-term memory is perfect’. e rst point to note is that this lay distinction between ‘short-term’ and ‘long-term’ is only a distinction between recent (e.g. recalling events from this morning) and remote (e.g. recalling events from school days) epi- sodic memory. Furthermore, the lay usage should not be confused with the neuropsychological term ‘short-term memory’ which is o en used as a synonym for working memory—the ability not only to hold information in mind but also to manipulate it. e key relevance of highlighting this point is that this frequently reported observation from informants is very o en untrue—understanding the falsehood is particularly useful in bedside memory examina- tion and, in turn, reaching an accurate diagnosis.

e reason that informants report a problem restricted to ‘short- term memory’ presumably relates to a couple of factors. First is that they were eye-witnesses to the events constituting the apparent ‘short-term memory’ de cit, so they have their own recollection to act as a control to the patient’s forgetting. Second is that it is very easy to fool oneself and believe that remote episodic memory is

intact based on the patient producing some generic or over-learned details. For example, a patient with a signi cant remote memory de cit, may have some frequently retold anecdotes from their past life that give the illusion of a good remote memory. Generic memo- ries can also give this illusion; for instance, asking a patient what they did last Christmas can prompt responses about eating too much, seeing family, etc. In this example, the patient is not nec- essarily providing speci c information about what they remember of the event; the information is generic as it could describe many Christmas days.

e relevance of this to episodic memory testing is that asking the patient for details of their past life can be very informative in detecting a de cit. e key is that the examiner sets the agenda rather than letting the patient discuss what they wish to recount. One should ask the patient for speci c details from their past life such as name of their school, rst and subsequent employment positions, where they were married, places they have lived, and so on. Although such examples are not true episodic memories (rather, they are personal semantic details), these simple questions will frequently expose memory gaps in even very early Alzheimer’s disease and will o en provoke a ‘head-turning sign’; the patient turning repeatedly to their spouse hoping for assistance.

True episodic memories can be probed in a similar manner by asking for speci c details of the events of their last holiday, last Christmas, last birthday, wedding day, birth of a child, etc. It takes little practice as an examiner to separate the generic information of a patient attempting to camou age their de cit from true episodic memory impairment. For instance, using the last holiday exam- ple, imagine a patient who always spends their summer holiday at the same seaside resort. In this scenario, responding with generic information such as they went to the beach or ate at restaurants does not indicate true recollection. In contrast, true episodic recall involves recounting details speci c to that trip, for example, ‘one day it rained so we visited the art gallery, there was a photography exhibition’, ‘we took a boat trip to view a seal colony, the sea was rough and our friend became ill’, etc. It is precisely this ne-grained, true episodic memory that people with early Alzheimer’s disease struggle with, and, as such, the utility of including such questions in the examination routine cannot be overemphasized.

e other method of testing memory at the bedside is by giving the patient something to learn and then asking them to recall the information a er a distraction period. Typical examples are word lists or a name/address, and examples exist as subtests in all of the bedside global assessment tools. ere are a few points worth high- lighting with this form of testing. First, the degree of di culty in such tests is in uenced by the amount one has to remember as well as the length of the distraction period. To this end, the memory component of the MMSE—three-word recall a er a distraction period of only a few seconds (while one spells ‘WORLD’ backwards or does serial 7s)—is very easy for intelligent, mildly impaired patients. As such, a perfect score on this measure should not be interpreted as meaning there is no memory impairment.

Second, some of these tests include multiple encoding trials (i.e. repeat the information more than once to enhance learning) and recognition (i.e. a er asking the patient to recall the informa- tion without cue—‘free recall’—asking them to identify previously learned information that was not freely recalled, intermixed with foils that they did not learn earlier). e pro le of de cits across these di erent components is sometimes helpful for di eren- tial diagnosis. For instance, in very mild Alzheimer’s disease, the encoding trials can show no abnormality whereas delayed recall is typically very impaired. In contrast, in dementia with Lewy bod- ies, encoding is o en impaired with patients unable to reach ceiling performance even a er a third trial, yet they o en show little, or no, decline from the third encoding trial to delayed recall (Fig. 10.1).

In general, bedside tests of learning and recall are quite sensi- tive surrogate markers for an episodic memory de cit, and this is even true for the three-word recall in the MMSE. Speci city, how- ever, can be a problem as patients with non-degenerative causes of memory complaints, such as psychiatric disorders, also can score poorly on such measures. is is important because separating degenerative from non-degenerative causes is the commonest clini- cal problem encountered in a memory clinic. It is also one of the most di cult problems, particularly as a diagnosis of depression does not necessarily imply that depression is the primary cause of the symptoms; it is also a common co-morbidity in early demen- tia. It is important to stress that there is no foolproof examination technique to sort out this problem, and sometimes it is only with



Very early AD

Mild DLB

Joseph Barnes
19 Woodland Close Browndale Yorkshire

Joseph Barnes
19 Woodland Close Browndale Yorkshire

Joseph Barnes
19 Woodland Close Browndale Yorkshire

Trial 1

Trial 2

Trial 3

Delayed Recall

CHAPTER 10 bedside assessment of cognition 107


Fig. 10.1 Examples of performance seen in learning and recall of a name and address in very mild Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB).

108 SECTION 2 cognitive dysfunction

follow-up that the diagnosis emerges. at said, the formal exami- nation of personal milestones and episodes, as already described, can be particularly useful because patients su ering depression or anxiety are o en better on these ecological measures.

ese measures can also be very helpful where there is a suspi- cion that a patient’s apparent poor performance on tests of learning and recall is an elaboration (due to a lack of e ort). Such patients may return catastrophic performance when knowing their mem- ory is being formally examined, but demonstrate good memory for real-life past events when questions are presented in what appears to be a general conversation. Another clue to look out for in such situations, is where the patient can go into incredibly ne-grained detail when recounting the circumstances (i.e. minute details of the events leading up to, and following on from, memory lapses), thereby demonstrating good episodic memory.

Semantic memory

Semantic memory refers to knowledge of facts, concepts, and objects. For instance, that Paris is the capital city of France, that an elephant is a large mammal with a trunk, that a ‘hobby’ is a pastime one indulges in for recreation, and so on. ese examples demon- strate the distinction from episodic memory in that such examples are not recollected from a particular time and place. In other words, knowing that Paris is the capital of France is a fact that one encoun- ters in various contexts; recalling the events of a speci c trip that one made to Paris are episodic memories.

Semantic memory can be tested in many ways. Simply naming pictures or objects in the o ce is useful, but it is important to stress that while a semantic de cit will cause naming di culty, a naming problem does not necessarily imply a semantic de cit. e latter can also result from a word-retrieval de cit. e examination can get at this by asking the patient questions about objects they cannot name. For instance, a patient with a word-retrieval de cit may not be able to name a ‘stethoscope’ yet can provide description: ‘the thing the doctor uses to listen to your chest’. Patients with semantic de cit, as seen in the syndrome of semantic dementia (also known as semantic variant primary progressive aphasia), in contrast, will o en respond that they have no idea when asked for a description. Another way to distinguish a semantic de cit from a word-retrieval problem is cue- ing. Performance of a patient with anomia due to a retrieval de cit will bene t from cueing (‘it is a steth …’?) whereas cueing typically is of less help to a patient with a semantic de cit.

Understanding how semantic knowledge deteriorates in neu- rodegenerative disease is crucial to understanding how to test it. Two, somewhat interrelated factors, namely, age of acquisition and word frequency, are important determinants of this process. e semantic material that is most robust is that acquired very early in life and that which occurs at the highest frequency in everyday life. Asking a patient to identify high-frequency items such as a pen or a dog can be done successfully in spite of a signi cant seman- tic decline. One must choose harder items, therefore, to expose the de cit. Even with no special equipment in a medical consultation, this can be achieved with objects such as the stethoscope, a stapler, a paperclip, etc.

Other examples of bedside semantic tests include naming to description (e.g. ‘what do you call the Australian animal that hops and has a pouch?’). To take naming out of the equation, one can give semantically complex commands such as, ‘point to an elec- tronic communication device’. Note that traditional three-stage commands (e.g. ‘take the paper in your le hand, fold it in half, and

lay it on the table’) are not good tests of semantic comprehension as they lack semantic complexity; these are typically taxing work- ing memory by stringing together a sequence of commands but the semantic content (‘paper’, ‘hand’, ‘table’) is very simple.


Naming and semantic knowledge are major components of lan- guage and were covered in the previous section. Other aspects that are useful to assess in reaching a clinical diagnosis include uency and grammatical ability, repetition, and reading.

Speech uency and grammar

Non- uent aphasia is best identi ed by listening to the patient con- verse rather than by doing tests. When severe, the problem is obvi- ous with severely laboured, slow speech. In the very earliest stages of a non- uent aphasia, however, it can be di cult to pick up or can appear as though the patient is su ering from slight anxiety. In such circumstances, it is o en the patient’s own history—and not the informant’s observations—that gives the clue in that they may complain of trouble forming sentences or mispronouncing words. Such complaints should be taken seriously even if they seem to be so subtle as to not be evident in the course of conversation; they are o en the harbinger of a progressive non- uent aphasia.

When non- uent aphasia is evident, it manifests as slow, laboured utterances with reduced sentence length. Phonological and phonetic errors may be evident: the former being incorrect placement of real phonemes (caterpillar capperpillar), the latter being sounds not corresponding to any normally articulated pho- nemes. e latter is a feature of so-called apraxia of speech.

Non- uent aphasia in degenerative disease typically, does not give rise to the agrammatic ‘telegraphic’ speech described in stroke aphasia. Although grammar is impaired on formal tests, the mani- festation in speech is typically to produce correct but very simpli- ed grammar. e speech of Alzheimer-related progressive aphasia (logopenic aphasia) is usually uent in grammatical terms but halt- ing due to frequent word- nding pauses. In semantic dementia, speech is uent and can sound remarkably normal. ese patients o en do not have word- nding di culties apparent in conversa- tion, presumably because word- nding di culty implies that the individual knows the concept for which they are trying to retrieve the word; if the concept is lost, one does not search for it.

Bedside testing of grammar involves asking the patient gram- matically complex, but semantically simple, questions such as reversible passive and centre-embedded sentences. Examples of the former include ‘Jack was sacked by Jill; who was the boss?’, ‘John was hit by Sam; who got hurt?’, and so on. Note here that the revers- ibility refers to the fact that the subject and object of the sentence give no clue as to the correct response, in contrast to a sentence such as ‘the sheep was eaten by the wolf; who survived?’ where, although passive, one could answer correctly simply by knowing that a sheep cannot eat a wolf. Also, note here that if one uses this testing approach, chance performance is 50 per cent, so one needs to present several examples to be sure of a problem. One could also look for a discrepancy between performance on passive construc- tions and easier active constructions (‘Jill sacked Jack; who was the boss?’). Centre-embedded sentences mean embedding a clause between subject and simple predicate, for example ‘the bowl the sh is in is red; what is red?’. e idea here is that the patient strug- gling with grammar might incorrectly answer ‘the sh’ because it occurs close to ‘red’ in the sentence.


Impaired repetition can be either at the single-word level or a prob- lem with sentence repetition. Impairment at the single-word level implies impairment also with sentences. Isolated sentence repeti- tion can occur and implies problems with auditory–verbal work- ing memory. is is thought to be the basis of sentence repetition de cits seen in association with Alzheimer pathology.

e repetition equivalent to testing semantics with lower- frequency items is to ask the patient to repeat long words—little can go wrong in repeating ‘cat’! To create graded di culty one can start with two syllable words ‘gallop’ and ‘rapid’ and proceed to complex multi-syllabic words such as ‘perspiration’ and ‘literary’. Also, by combining repetition with de nition, one has a quick screening test for both articulation and semantics; for example, ask the patient to repeat ‘caterpillar’ then ask for a de nition of a caterpillar; other examples include ‘rhinoceros’, ‘catastrophe’, etc. Asking the patient to repeat one of the complex multisyllabic words such as ‘catastro- phe’ a number of times over and looking speci cally for inconsist- ent repetition mistakes from one trial to the next is considered a sign of apraxia of speech.


Reading orthographically regular and irregular words can also be very helpful and represents a simple bedside test to administer to expose semantic de cits through the phenomenon of ‘surface dys- lexia’. It is particularly useful in the English language, less so in lan- guages with more transparent orthography to pronunciation rules. Irregular words refer to words that are not pronounced as they are

(i) (ii)

written and in order to pronounce them correctly, one requires semantic knowledge. For instance, if knowledge of the word ‘pint’ is lost, it will be pronounced as it is written (to rhyme with ‘hint’). In other words, it is read according to its ‘surface structure’ rather than its deeper meaning, hence, ‘surface dyslexia’. Note that the rule about semantic dementia and high-frequency words applies here as well. One does not observe surface errors to ultra-high-frequency words such as ‘was’ even if it is not pronounced as written. One needs to test by having the patient read lower-frequency words of which, in English, at least, there are many: ‘yacht’, ‘sew’, etc.

Visual perception

Hemianopia and visual neglect are tested as part of the standard neurological examination. De cits in higher-order visual process- ing, particularly spatial processing, are important to test for at the bedside in suspected posterior cortical atrophy. In fact, visuoper- ceptual testing in individuals suspected of having this syndrome is particularly useful because o en patients and informants strug- gle to articulate the nature of the problem clearly. In contrast, the de cit can be quickly exposed with simple bedside tests. Visuo- constructive ability is a useful screening test (i.e. clock, wire-cube drawing, etc.). De cits on such tasks are o en referred to as con- structional apraxia. Drawing such items also has a motor and planning component, so impairment does not necessarily imply a perceptual problem. e hallmark of posterior cortical atrophy is simultanagnosia and this is fairly easily demonstrated with simple bedside tests (Fig. 10.2).


CHAPTER 10 bedside assessment of cognition 109










Fig. 10.2 Tests of simultanagnosia. Panels each represent an A4 sheet. (i) e patient is asked to point to the ‘As’ (then later ‘Bs’). Typically they nd the small letters, but miss the large ones. In (ii) the patient is asked to read the word. ey typically struggle, having to read letter by letter down the page, or cannot manage it at all, whereas when the word is written normally (iii) it can be read. Note in both examples that the impairment cannot be attributed to a visual acuity problem as the patient fails to identify the larger items. (iv) simultanagnosia can mean that patients only pick details out of pictures when naming. In the example shown, a simultanagnosic patient (posterior cortical atrophy) named this item as ‘chopsticks’. When asked to explain, it became evident that they were only noticing the rotor-blades of the helicopter. is is important to be aware of as apparently bizarre answers can lead to the incorrect belief that the patient is simulating their de cits.

110 SECTION 2 cognitive dysfunction

Fig. 10.3 Examples of meaningless gestures to test apraxia. Note that ‘meaningless’ is culture-speci c, and items should be chosen to avoid o ensive gestures in the target population!

Dressing apraxia is another useful bedside test that accompanies de cits in perception. It is easily assessed by asking the patient to put on a sweater or jacket that has had one of its sleeves turned inside out.

Limb apraxia

Limb apraxia is the inability to execute motor responses despite intact basic motor functions (see also chapter 6). It is therefore important to have rst con rmed that basic motor (and sensory) functions are intact from the general neurological examination. Limb apraxia is a prominent feature of the corticobasal syndrome and can be examined by having the patient copy meaningless hand gestures (Fig. 10.3). Having the patient imitate meaningful actions (pretending to stir a cup of co ee or comb one’s hair, etc.) can also be tested. is form of apraxia has a semantic and a motor com- ponent and, in the authors’ experience, such testing does not add meaningfully to the assessment of apraxia.

Executive function and ‘frontal’ behaviour

Executive function covers problem solving, abstraction, multitask- ing, and so on. Impairments are o en thought of as synonymous with frontal lobe dysfunction. While it is true that the frontal lobes are critical for these functions, these kinds of complex tasks really require the whole cognitive brain; they are the strongest example of needing all cognitive faculties working and this is seldom the case in degenerative disease.

ere are a multitude of bedside tests purporting to test executive function. Popular examples include:

◆  Go–no go: ‘When I tap the table once, you tap the table once; if I tap the twice, you do not tap’, the idea being that the stimulus- bound patient cannot suppress the impulse to tap twice in the latter condition

◆  Proverb interpretation: the patient cannot abstract the proverbial message and provides a literal interpretation

◆  Cognitive estimates: asking questions in which one would not normally know the answer but could make a reasonable guess, e.g. ‘How fast can a racehorse gallop?’ or ‘How far is London from Paris?’, etc.

◆  Di erences and similarities: ‘In what way are a sculpture and a piece of music similar?’ or ‘What is the di erence between a dwarf and a child’?
ere are problems with all of these tests when used to aid diag- nosis. Ideally, for example, they should be sensitive and speci c to the behavioural form of frontotemporal dementia but they typically fail on both counts. One of the problems is the fact that tests such as proverbs, cognitive estimates, and di erences/similarities tend to be in uenced by premorbid intelligence. To this end, it is not uncommon to nd members of the normal population who will explain the meaning of proverbs in a concrete manner or who may make grossly inaccurate cognitive estimates. ere is also the con- sequential problem of deciding how gurative a response should be for it to be deemed non-literal. Perhaps the main problem is

20 15 10



the same for a semantic category. For instance, words beginning with the letter ‘P’ and animals beginning with any letter. ere is some variability in the number that healthy people can produce, but the pattern of the two tasks rather than the absolute score is o en informative. Healthy people typically can produce at least 15 P-words and do slightly better than their letter uency score in the animal uency condition. In early Alzheimer’s disease, one o en sees a reversal of this pattern even if the absolute scores are not particularly low, perseverations are also common; in semantic dementia there is typically a profound reduction in animal word uency; in behavioural variant frontotemporal dementia there is o en a disproportionate reduction in letter uency; in progressive supranuclear palsy this is usually extreme, o en as few as only one P-word in one minute (Fig. 10.4).


In summary, much valuable diagnostic information can be gleaned from a thoughtful cognitive examination. If more detailed, quan- titative information is needed across the cognitive domains, a formal neuropsychological evaluation is an appropriate next step. is is particularly true in clinically ambiguous situations, such as where de cits are so subtle as to be of uncertain signi cance. Neuropsychological scores in such instances can act as an invalu- able baseline that can be repeated at a future time-point to assess change. Referral for neuropsychological assessment should not be used, however, as a substitute to a careful assessment. e best chance of making an accurate diagnosis lies in a careful history, and cognitive examination and this should be viewed as the foundation to inform interpretation for ancillary tests including neuropsychol- ogy, imaging, and laboratory investigations.

Further reading

Larner AJ (ed.). Cognitive Screening Instruments: A Practical Approach. London: Springer-Verlag, 2013.

Hodges JR. Cognitive Assessment for Clinicians, 2nd edn. Oxford: Oxford University Press, 2007.


1. Qureshi K and Hodkinson M. Evaluation of a 10 question mental test of the institutionalized elderly. Age Ageing. 1974;3:152–7.

2. Folstein M, Folstein S, and McHugh P. ‘Mini-Mental State’: A practi- cal method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189–98.

3. Nasreddine Z, Phillips N, Bédirian V, et al. e Montreal Cognitive Assessment (MoCA): A brief screening tool for mild cognitive impair- ment. J Am Geriatr Soc. 2005;53:695–9.

4. Mioshi E, Dawson K, Mitchell J, et al. e Addenbrooke’s Cognitive Examination Revised (ACE-R): A brief cognitive test battery for dementia screening. Int J Geriatr Psychiatry. 2006;21:1078–85.

CHAPTER 10 bedside assessment of cognition 111





Fig. 10.4 Patterns of performance on letter uency versus animal uency (y-axis indicates words produces in one minute) in the early stages of the respective disorders: AD, Alzheimer’s disease; SD, semantic dementia; bvFTD, behavioural variant frontotemporal dementia; PSP, progressive supranuclear palsy.

that the behavioural changes, associated most typically with frontal lobe degeneration, are extremely complex, and so, try as these tests might, they are just too simpli ed to capture this complexity.

A far more robust approach to identifying behavioural variant frontotemporal dementia and other frontal lobe conditions is to take note of the patient’s actual behavior in the social setting of the consultation. Careful observation and recording of how the patient appears, interacts, and the content of their conversation are essen- tial to reach an accurate diagnosis. In this regard, the examina- tion is highly similar to the mental state examination (MSE) that forms a routine part of a psychiatric assessment. e reason this is important is because although the details of personality change will come from an informant—hence the informant’s account is essential to identifying the characteristic changes of frontotemporal dementia—if one relies solely on the informant’s account, there is a risk of making a false-positive diagnosis.

is risk is minimized by corroborating the informant’s history with careful observation of the patient. e changes one might observe include restlessness, such as being unable to remain seated and preferring to get up and wander; impulsively wanting to ter- minate the consultation; not respecting personal space; being dis- tracted by environmental stimuli such as going to the window to look at tra c or wanting to see what is on a computer monitor. At it most severe, utilization behaviour may be observed in which the patient will start using anything handed to them; giggling fatu- ously; repetitive use of a catchphrase or cliché in conversation; making disinhibited remarks about people in the clinic, and so on.

One nal bedside test that has some utility in frontotemporal dementia and also for a range of other conditions is verbal u- ency: asking the patient to produce as many di erent words as they can think of in one minute that begin with a certain letter and then

Animal Letter


Neuropsychological assessment

Diana Caine and Sebastian J. Crutch


Neuropsychological assessment of patients presenting with cogni- tive disorders provides crucial information on which to base diag- nosis as well as evaluate whether there have been changes in an individual’s condition. For example, while ‘dementia’ is de ned as a cognitive syndrome a ecting memory, thinking, behaviour, and the ability to perform everyday activities, intensive neuropsycho- logical research has resulted in the identi cation of di erential and pathognomonic patterns of cognitive decline in di erent condi- tions.1,2 Particularly in the early stages of disease, dementia syn- dromes with di erent underlying aetiologies o en selectively a ect speci c functional systems, consistent with the characteristic sites and distribution patterns of the relevant pathology.3 A number of dementia syndromes therefore have what might be regarded as a characteristic cognitive signature.

Neuropsychological assessment, especially in the earliest disease stages of disease, when a patient is rst being investigated for cogni- tive failure in daily life, is directed towards (i) establishing whether or not the patient’s complaints are more likely to be neurogenic than psychogenic; and (ii) characterizing a patient’s cognitive status with a view to determining whether the cognitive pro le is consist- ent with one or another of these cognitive signatures. is chapter will address how this assessment is done and will include some case studies. It also seeks to expand the ‘psychological’ in ‘neuropsy- chological’ to address, albeit brie y, the impact of those cognitive changes on the patients’ sense of themselves and on their relations with others.

e aim of neuropsychological assessment is to demonstrate the presence or absence of cognitive decline on objective measures of cognitive function. In the context of dementia, notwithstanding advances in neuroimaging, the documentation of cognitive change on neuropsychological assessment not infrequently precedes posi- tive ndings on other investigative measures. e usefulness of neuropsychological testing for diagnosis rests on interpretation of the pattern of performance across tests of the di erent cognitive domains, rather than on the result of any particular test or any par- ticular cognitive domain on its own. For that reason, neuropsycho- logical assessment typically includes a range of measures including current general intellectual function as well as tests of performance in the major cognitive domains: memory, language comprehension and production, executive function, visuoperceptual and visuospa- tial function, attention, and processing speed. At the same time, while an assessment needs to be comprehensive it also needs to be e cient, in the interest of the patient’s well-being and cooperation on the one hand, and practicality on the other.

Test selection, structure, and properties

e selection of neuropsychological tests for an assessment will depend on a variety of factors including the nature of the referral (e.g. evaluation for evidence of cognitive impairment, monitoring of disease progression), the patient’s clinical status (e.g. under inves- tigation, diagnosed, dementia type/syndrome, disease severity), the availability of information about their cognitive status (e.g. bedside cognitive screening, previous neuropsychological assessment), and the overall context of the assessment (e.g. clinical, research, clinical trial, medico-legal). Appropriate test selection is important in all contexts.

Within the standard clinical setting, there is freedom to choose tests but also pressure for the psychologist to work reactively, adapt- ing the roster of assessments according to the patient’s presentation and emerging cognitive pattern. Such responsive practice is essen- tial to identify and verify apparent de cits and build up a meaning- ful pro le of the individual within the time and other constraints of a given service. By contrast, group research studies and clinical trials usually involve the administration of a predetermined battery of tests. In this context, careful selection to ensure appropriateness of the tasks for the target population and the frequency they are administered is critical to ensure that patients are not repeatedly confronted with tasks which are too di cult and may cause frus- tration and distress, and to avoid practice e ects (see section on practice e ects).

Whilst test selection is o en dictated by mundane factors such as test availability or local service traditions, familiarity with the structure and psychometric properties of di erent neuropsycho- logical measures is critical in maximizing the validity and e ective- ness of the assessment.

Task di culty, and ceiling and oor e ects

e di culty of a particular task can determine its suitability for use in particular situations. For example, demanding uncued and cued recall tests of episodic memory may be required to discrimi- nate between healthy individuals and those with pre-symptomatic Alzheimer’s disease (AD) (e.g. free and cued selective remind- ing test (FCSRT)4–5 (see also chapter 32). By contrast, evaluation or monitoring of memory impairment in mild to moderate AD patients may be more appropriately assessed using forced choice recognition procedures (e.g. recognition memory test).6 Dedicated tools for the assessment of those with more severe cognitive impairment are also available (e.g. Severe Impairment Battery).7 Some tasks o er alternate forms with di erent degrees of di culty (e.g. long, short, and easy forms of the recognition memory test).


cognitive dysfunction

20 19 18 17 16 15 14 13 12 11 10

9 8 7 6 5 4 3 2 1 0


Time 1

Time 2

Fig. 11.1 Illustration of ceiling and oor e ects and their impact on the interpretation of longitudinal assessment data. e gure describes the cases of three putative patients all administered an imagined test at two time-points. Patient 1 exhibits ceiling e ects at both time 1 and time 2, making it impossible to assess from this data alone whether (a) there is any impairment in this function, (b) performance is worsening over time, or (c) the task is simply too easy to detect (a) and/or (b). Likewise, Patient 3’s score at or near oor at both time-points, indicating a de cit but preventing any meaningful evaluation of further decline over time. Only the performance of Patient 2 is adequately captured within the di culty level/dynamic range of this task.

Appropriate task di culty (or use of tasks with a wide dynamic range or which are graded in di culty; see section on dynamic range and graded di culty test structure) limits the occurrence of ceiling e ects (where maximal scores mask subtle de cits) and oor e ects (where minimal scores mask residual abilities; see Fig. 11.1).

Dynamic range and graded di culty test structure

Tasks with a wide dynamic range permit the evaluation of multi- ple levels of cognitive de cit through the use of continuous meas- ures (e.g. response time) or through variability in the di culty of discrete test items (see Fig. 11.2). As the term suggests, graded di culty tasks order discrete items from easy to hard, so that dis- continuation rules can be employed to prevent unnecessary admin- istration of overly di cult items. Consequently, such tasks protect against ceiling and oor e ects and are ideally suited to cognitive domains in which there is considerable inter-individual variability in the healthy population (e.g. vocabulary size, calculation skills), and where longitudinal evaluation of cognitive change over multi- ple time-points is required.

Confounding and collateral de cits

Composite scores

Some neuropsychological assessment goals or research questions may be addressed best using composite scores rather than indi- vidual tests or between-test pro les. For example, the designers of outcome measures for some early-stage and preventative AD trials advocate use of composite measures (which may include a com- bination of tests such as the ADAS delayed word list recall,8 logi- cal memory delayed paragraph recall,9 Wechsler Adult Intelligence Scale—Revised (WAIS–R) digit symbol substitution,10 and mini- mental state examination11). Such composites require validation for use in phase 3 trials, but composites have a long pedigree in clinical neuropsychology (e.g. WAIS IQ scales are a composite of multiple subtests; see Fig. 11.2).

Practice e ects

Many neuropsychological tasks are subject to practice e ects when administered on more than one occasion. Whilst the magnitude of the e ects has been evaluated for some tasks,12 other tasks attempt to minimize practice e ects by using parallel stimulus sets (e.g. Graded Di culty Spelling Test).13 In many longitudinal studies, disease e ects are determined from the absence of practice e ects rather than reductions in absolute tests scores (i.e. a divergence over time between patient and control groups). However, the inter- pretation of changes between initial and follow-up assessment per- formance in individual clinical patients (relative to a single set of cross-sectional normative data) is more problematic.

e strategy of neuropsychological


Neuropsychological investigation begins with an evaluation of the patient’s estimated optimal level of function prior to any recent

Few neuropsychological tests tap a single type of cognitive process; many tasks possess inherent sensory, linguistic, and attentional- executive demands such that poor performance may occur for a number of di erent reasons. Picture-naming tests are a simple example; nominally a measure of word-retrieval skills, the task also requires visuoperceptual, semantic, executive control, and articu- latory skills. e impact of collateral cognitive de cits not only necessitates the interpretation of the target test in the context of the broader cognitive pro le, but also motivates the test selection (e.g. evaluating word retrieval in posterior cortical atrophy by naming to verbal description rather than naming to visual confrontation).

Patient 1 Patient 2 Patient 3

Number correct (/20)

Standard deviations

Percentile ranks

T scores Standard scores

(SD = 15) Scale scores

(SD = 3)


–1σ Mean



Deficient 0.13%


Low 2.14%

Low average

13.59% –2σ

Average 34.13%

High average

13.59% +1σ

Superior 2.14%

Very Superior 0.13%


CHAPTER 11 neuropsychological assessment 115


Test score


1 5102030507080909599


10 20 30 40 50 60 70 80 90

55 70 85 100 115 130 145

1 4 7 10 13 16 19


Fig. 11.2 Comparison of standardized scores [standard deviations (z scores), percentile ranks, T scores, standard scores (commonly termed ‘IQ scores’) and scale scores] across the normal distribution. Standardized scores provide a means for e cient comparison of performance levels across di erent tasks and domains. Note: not all neuropsychological tests yield normally distributed scores in healthy populations; the relative value or meaningfulness of standardized scores is reduced in tasks where the normative data are positively or negatively skewed.

change or decline. In addition to information elicited about the patient’s education and employment history, which is very o en a useful guide in this regard, an estimation of pre-morbid IQ is also based on performance on a reading test known to be highly cor- related with IQ. e National Adult Reading Test (NART)14 is such an instrument, comprising 50 words all of which have low sound– spelling correspondence. Performance on this test, in native English speakers—and in many, but not all, neurological conditions—is thought to be relatively robust to brain damage. e exception is any condition in which reading may itself be a prominent symptom; for instance, semantic dementia. e interpretation of test results depends crucially upon establishing whether the patient’s perfor- mance is at variance with the level of performance expected based on this estimation of optimal functional level. Failure to do this risks underestimating decline in patients of better than average intellect or, conversely, overestimating deterioration in patients whose gen- eral intellectual function has always been lower than average.

Identi cation of cognitive de cits is accomplished in the rst instance by comparing a patient’s scores with those of age—and sometimes also education-matched—normative scores, taking into account the patient’s premorbid IQ. In addition to the scores them- selves, the qualitative features of a patient’s performance and the nature of the errors can also be illuminating as to the nature of the de cit. us, for instance, errors on a test of object naming may arise from visuoperceptual problems (e.g. seeing a pair of handcu s as ‘spectacles’ or ‘a bicycle’) or from semantic loss (e.g. calling a pic- ture of an anteater ‘a dog’).

In describing our approach to neuropsychological assessment below mention is made of tests which represent just a small sample of the many tests currently available (for reference to speci c tests see reference 15). A comprehensive neuropsychological assessment should include evaluation of the following:

General intellectual function

e neuropsychological assessment should evaluate the extent to which there may be a discrepancy between a patient’s current level

of intellectual of function and the optimal pre-morbid level that has been estimated. e Wechsler Adult Intelligence Scale,16 now in its fourth incarnation, has for decades been regarded as the gold standard for testing general intellectual function. e full battery of tests is very long but robust estimates of current IQ can be obtained from shortened versions, as recognized by the test-makers them- selves in the form of the Wechsler Abbreviated Scale of Intelligence (WASI)17 which comprises four subtests from which verbal, per- formance, and full-scale IQ (VIQ, PIQ, and FIQ) scores can all be generated. In addition to providing estimates of current global intel- lectual function, much useful information can be gathered from a patient’s performance on individual subtests and/or discrepancies between scales or subtests. For example, individuals with semantic dementia typically exhibit signi cantly lower VIQ than PIQ (with especially weak performance on vocabulary and similarities; see case study 2 this chapter), whilst conversely individuals with poste- rior cortical atrophy typically struggle with the visual demands of many performance subtests (e.g. matrix reasoning, see case study 1 this chapter).


From a theoretical point of view, memory is a complex cognitive domain comprising a number of components including registra- tion, encoding, retention, and retrieval. Memory complaints are by far the commonest reason for referral for neuropsychological assessment, although in the layperson’s vocabulary ‘memory’ func- tions as a catch-all for almost any self-reported cognitive change. From the perspective of assessment, two aspects of memory are of particular importance: episodic memory, the encoding and recall of new information; and semantic memory, the knowledge of concepts, facts, and meanings, which is usually considered in the context of language rather than memory as such (see section on language). Episodic memory is typically assessed with tests of rec- ognition (e.g. recognition memory test (RMT)6 tests for words and faces, and recall of both verbal and visual information (e.g. BIRT Memory and Information Processing Battery BMIPB;18 Doors and

Number of cases

116 SECTION 2 cognitive dysfunction

People Test).19 Impairment on tests of delayed recall is a particu- larly sensitive measure of memory decline and by far the most com- mon presenting feature in typical AD.20 Working memory can also be tested in both verbal and visuospatial domains using digit span or its analogue, spatial span (Wechsler Memory Scale–III).21


In the context of dementia, language complaints are less common than concerns about memory but, as is very well documented, can be the symptom that heralds primary progressive aphasia.22 Apart from attention to the patient’s spontaneous speech for evidence of word- nding di culty, paraphasic errors, or problems with articu- lation or speech production, screening for language de cits in the context of neuropsychological assessment of dementia usually relies on tests of naming and uency in addition to verbal compre- hension tasks within the general intellectual assessment (e.g. the vocabulary or similarities subtests of the WAIS).

e naming of line drawings of objects and animals (e.g. Graded Naming Test)23 is a sensitive test of semantic knowledge24 as well as being a test of lexical access.25 Category uency (commonly, the number of animal names a patient is able to produce in 60 seconds) is another easily administered task that has also been shown to be a robust measure of semantic memory.26 Although not designed to do so, both are also liable to elicit phonological di culties or problems with articulation or apraxia of speech, where they are present. Where de cits on these tests, in the context of relative preservation of per- formance on other tasks, suggest that language is a prominent early symptom of decline, other language tasks including tests of repeti- tion, reading, spelling, and sentence comprehension are also admin- istered. In the primary progressive aphasias a disturbance of one or another aspect of language is the most prominent feature early in the course of the disease, with the particular pattern of the disturbance indicating which progressive aphasic disorder is in question.

Visuospatial function

De cits in visual processing can also sometimes be amongst the earliest presenting signs in a dementing process.27–28 Elementary visuospatial function can be assessed using the ‘visuospatial’ com- ponents of the visual object and space perception (VOSP) battery:29 position discrimination, dot counting, number location, or cube analysis. In addition, the copy condition of the BMIPB complex gure-recall task (or similar) also acts as a test of visuoconstructive task which might be a more sensitive measure of early visuospatial decline in some patients.

Visuoperceptual function

this function. Visual processing problems are characteristically the earliest signs of disease in posterior cortical atrophy, irrespective of the underlying pathogenesis.


Apraxia refers to a loss of the ability to execute or carry out pur- poseful movements, whether meaningful or not, despite intact motor and sensory capacity. Although not usually part of routine neuropsychological assessment, it can constitute a signi cant com- ponent of a dementing syndrome (e.g. corticobasal degeneration, Creutzfeldt–Jakob disease), and where there are symptomatic com- plaints which suggest it may be present, it should be systematically evaluated (see, for example, reference 30 and chapter 16 for further details).

Frontal and executive function

e frontal lobes can be thought of as mediating two di erent aspects of behaviour: (i) the rst is executive function, the ability to plan, organize, monitor, and voluntarily alter responses, in addition to abstract thinking, reasoning, and problem-solving; and (ii) social behaviour, the ability successfully to interact with others through empathy, understanding what others have in mind, conversational turn-taking, and so on. e rst of these is assessed using tests which require cognitive exibility (for example, Trail Making Test),31 strategy formation (letter uency); abstract concept formation (for example, modi ed card sorting test),32 and the inhibition of pre- potent responses in favour of alternative competing responses (for example, Stroop test,33 Hayling sentence completion34). e latter is not so easily tested in a standard neuropsychological assessment but these are features that are readily elicited from the history or, indeed, from the patient’s behaviour during testing. Tests of social cognition or theory of mind (e.g. e Awareness of Social Inference Test;35 Reading the Mind in the Eyes36) can be useful where this is the most prominent feature of a presentation.

Information-processing speed

A reduction in the rate at which cognitive or psychomotor tasks are performed is a common feature of any kind of brain impair- ment, while psychomotor retardation is also a known feature of depression. Reduced information-processing speed may also be particularly prominent in individuals with pronounced subcortical damage (e.g. some forms of vascular dementia). While measures of speed are therefore not always helpful in di erential diagnosis, they do help in understanding a patient’s competencies and di culties in daily life. ere are numerous measures amongst the most com- mon of which are timed-number or letter-cancellation tasks.


Mood, which can independently have an impact on the e cacy of cognition, can consequently also be a signi cant factor in the diag- nostic process. In the rst instance, di erentiation of the impact of mood from possible organic causes of cognitive decline is frequently a crucial question in the early diagnostic work-up for dementia. Second, both anxiety in response to cognitive failure and depres- sion in response to awareness of cognitive decline and its implica- tions can exacerbate impaired performance. us, in addition to formal measures of cognition, the neuropsychological assessment should include evaluation, by both interview and questionnaire,

Inability correctly to name line drawings might arise from semantic memory loss—loss of knowledge of what a thing is—or from a fail- ure of visual perception, sometimes a di cult distinction to make. A failure to perceive an object accurately may re ect loss of stored object-speci c structural representations (e.g. inability to perceive common objects from unfamiliar angles) or because of more basic impairments of edge, form, and colour processing which deprive intact structural representations of the necessary input. e VOSP also comprises tests of visuoperceptual function (object decision, incomplete letters, silhouette naming) and of more basic visual processing (shape detection) which evaluate this domain. As sug- gested earlier, the nature of errors on other tasks with a perceptual component, such as object naming, represent further assessment of

of the patient’s mood. Commonly used instruments include the Beck Depression Inventory,37 Geriatric Depression Scale,38 and the Cornell Scale for Depression in Dementia.39 Here, the history of the symptomatology can be key in determining whether a mood disorder is the primary diagnosis or whether disturbed mood is a response to cognitive decline.

Interpretation of test results

In interpreting test results, both quantitative and qualitative features need to be considered. From the quantitative point of view, the pat- tern of results—the pattern of intact and impaired scores—across the whole range of tests administered is considered in addressing the question of whether the pattern obtained ts with one of the known dementia syndromes. Qualitatively, the patient’s behaviour during testing (e.g. signs of impulsivity, restlessness, and agitation, level of insight and awareness, bewilderment, comprehension or recall of task instructions) as well as the nature of the errors made (e.g. evidence of semantic rather than visual errors on naming; phonological or semantic paraphasias; confabulation on memory tests) may contribute signi cantly to interpretation of test results.

A patient who presents with memory or other cognitive com- plaints of insidious onset o en also presents with low mood. Here, again, the pattern of performance—for example, reduced scores on tests of attention, poor immediate recall without further loss over time—as well as the patient’s behaviour during testing can both be helpful in discriminating between neurogenic and psychogenic dis- orders. Of course, these may not be mutually exclusive; frequently mood is low precisely because the person is aware that their cogni- tion is failing.

Case studies
1. CaseMC:Posteriorcorticalatrophy

MC was a 53-year-old, right-handed senior civil servant who pre- sented with concerns about memory. She had a bachelor’s degree in the humanities and the postgraduate certi cate in education teach- ing quali cation. She was able to give a clear and coherent account of her di culties. ere was no relevant past medical history and took no medication. About ve years prior to presentation, she had gone through a very stressful period involving antisocial behav- iour directed towards her home and family. She developed panic attacks and recalled an occasion when she was in a supermarket, feeling overwhelmed, nauseated, and disorganized. ese symp- toms recurred and progressed to the extent that over the six months prior to the initial neurology consultation she began to feel that she was not coping at work: she found her job—which she had been doing competently and comfortably to that point—stressful. She did not always get the gist of meetings. She had started trying to write things down but nonetheless felt she was always covering up for herself. She became concerned about her ability to multitask, or to understand e-mails. She missed a couple of appointments and was more reliant on her diary.

She was managing the housework without di culties but reported that forgetfulness and losing things were an issue. Most notably, she found she became rather panicky whilst trying to fol- low routes, instructions, and maps. As well as di culties with maps she had bumped the car on a few occasions and lost con dence somewhat whilst driving. She felt that her ability to do mental

arithmetic had perhaps declined. She reported no problems with speech, her sleep was normal, and she had no hallucinations. She did not smoke and drank alcohol occasionally. ere was no family history of cognitive impairment. She described being stressed and feeling depressed particularly over the previous six months.

Her scores on neuropsychological assessment can be seen in Table 11.1 (see also Fig. 11.3). Estimated optimal level of premor- bid function, based on education, employment history, and from her performance on the NART reading test was thought to be in the high-average range. From the scores in Table 11.1 it is clear that nei- ther verbal (average) nor performance (impaired) IQ scores are at premorbid levels, but that the decrement is much more striking in the non-verbal domain, with scores poorer than expected on all three non-verbal tests administered. She scored in the impaired range on both recognition memory tests, con rming her subjective account of forgetfulness in daily life. Object naming, category uency, and visuoperceptual function were all intact while visuospatial function

Table 11.1 Neuropsychology scores for patient MC

CHAPTER 11 neuropsychological assessment 117



Estimated Premorbid Functioning



Current Intellectual Functioning


Verbal IQ

Vocabulary Similarities Arithmetic Digit Span

Average High-average Average Average

Performance IQ

Picture completion Block design
Picture arrangement

67 Borderline Impaired Impaired


WRMT—words WRMT—faces

<5th %ile <5th %ile


Graded naming test Semantic uency (‘animals’)

50th %ile 25–50th %ile

Visuoperceptual Skills

VOSP inc. letters

>5th %ile cut-o

Visuospatial Skills

VOSP position discrimin. AMIPB gure copy

<5% cut o <10th %ile

Executive Function

Fluency—‘S’ Stroop test

90th %ile 72nd %ile

Processing Speed

Counting backwards


118 SECTION 2 cognitive dysfunction Posterior cortical atrophy (Patient MC)

Semantic dementia (Patient NA)

≥50th %ile 25–50th %ile

5–25th %ile <5th %ile

Visuospatial processing

Functional cognitive symptoms (Case ID)


Executive function

Processing speed

≥50th %ile 25–50th %ile

5–25th %ile <5th %ile

Visuospatial processing



Executive function

Processing speed



Executive function

Processing speed

≥50th %ile 25–50th %ile

5–25th %ile <5th %ile

Visuospatial processing




Fig. 11.3 Target diagrams summarizing the contrasting cognitive pro les of MC, NA, and ID across several cognitive domains. Cognitive impairment (estimated from percentile scores) is represented by the retreat of colour in each segment into the centre of the circle.

was very poor on both the VOSP test of spatial perception and the visuoconstructional task of gure copying. She was unable to place the numbers or hands correctly on a clock face and could not copy interlocking pentagons. In contrast, executive function was strikingly robust. Processing speed on a test that was not reliant on visual pro- cessing was normal. She scored in the mild range for both depression and anxiety on the Hospital Anxiety and Depression Scale (HADS), most likely underestimating somewhat low mood.


Although possibly exacerbated by mood, the pro le is clearly organic. is was evident because of the relative speci city of her de cits; the nature of the di culties she had with visual tasks which would not be seen in a functional disorder; and in her good scores on e ortful verbal tests which indicated that level of e ort was not at issue. Here, the pro le was quite focal. Poor visuospatial function was the principal feature, with other aspects of cognition relatively intact apart from memory, which is usually but not always relatively spared in posterior cortical atrophy. is pro le was con rmed on magnetic resonance imaging (MRI) which showed focal symmetri- cal volume loss in the parietal region bilaterally, in addition to some hippocampal atrophy which was also symmetrical.

2. Case NA: Semantic dementia

NA was a 71-year-old, right-handed professional woman who pre- sented with a three- to four-year history of progressive di culty thinking of words, especially nouns. She reported di culty reading or following what she was watching on television. She had forgot- ten how to cook. Spontaneous speech was marked by word- nding di culty and insertion of general substitutions (e.g. ‘thingy’) and semantic paraphasias (e.g. ‘knife’ for ‘scissors’). Articulation and prosody were both preserved.

On formal examination, her score on the NART reading test sug- gested an estimated optimal premorbid IQ in the low-average range, clearly an underestimate given her education and employment his- tory (see Table 11.2 and Fig. 11.3). e nature of her errors—trying to read the words by their spelling producing what are called ‘regu- larization’ errors—is a classic sign of semantic dementia.

In striking contrast to the previous patient, NA showed exactly the reverse nding on the verbal and performance IQs of the WAIS–III: here, the patient scored in the impaired range on the

verbal scale and in the high-average range on the non-verbal scale of the battery. e discrepancy points to very speci c verbal de cits particular in relation to the vocabulary (production of de nitions to words) and similarities (generation of abstract concepts which link two words) subtests. By the same token, recognition mem- ory for words was impaired while recognition memory for faces remained intact. Unsurprisingly, object naming was profoundly impaired. Given the very prominent language impairment, addi- tional language testing showed that single word comprehension was impaired (British Picture Vocabulary Test 22/32 correct) while repetition of both words and sentences was intact. Both visuoper- ceptual and visuospatial processing remained intact while execu- tive function and processing speed were both reduced.


e pro le was consistent with a diagnosis of semantic dementia, with the MRI showing selective, severe atrophy of the cortex and white matter of the anterior, medial, and inferior aspects of the le temporal lobe against a background of generalized atrophy.

3. Case ID: Functional cognitive symptoms

is 44-year-old man presented with complaints of forgetfulness in daily life dating back over the previous three to four years, possibly more noticeable in the months preceding the assessment. He had no other cognitive complaints although he did report a single con- versational lapse while drinking with friends. Estimated optimal level of function based on NART and on his education and employ- ment history was thought to be in the average range (see Table 11.3 and Fig. 11.3). Both verbal and performance IQ were in this range, indicating robust general intellectual function.

Recognition memory for words was quite robust (75–90th per- centile) while recognition memory for faces was a little weaker, although still within normal limits (10–25th percentile). Both immediate and delayed recall of a short story were rather more impoverished than expected (both 10–25th percentile), with reten- tion also a little weak (10–25th percentile). In contrast, both imme- diate and delayed recall of a complex gure were quite adequate (both 25–50th percentile) and here, retention a er a delay was actually better than immediate recall (retention > 75th percentile)! Inconsistencies amongst memory tests pointed to attentional uc- tuations and lapses that were most marked in response to complex





































Table 11.2 Neuropsychology scores for patient NA

CHAPTER 11 neuropsychological assessment 119 Table 11.3 Neuropsychology scores for patient ID



Estimated Premorbid Functioning



Current Intellectual Functioning


Verbal IQ

Vocabulary Similarities Arithmetic Digit Span

69 Borderline Impaired Low-average Low-average

Performance IQ

Picture completion Block design
Picture arrangement

111 High-average High-average Average


WRMT—words WRMT—faces

<5th %ile

50th %ile

D&P verbal recall Immediate Delayed

<10th %ile 10th %ile

D&P visual recall Immediate Delayed

10–25th %ile 25th %ile


Graded naming test Semantic uency (‘animals’)

<1st %ile <10th %ile

Visuoperceptual Skills

VOSP inc. letters

>5th %ile cut-o

Visuospatial Skills

Doors and people copy

No errors

Executive Function

Fluency—‘S’ Weigl sorting

<1st %ile
1⁄2 categories

Processing Speed

Letter cancellation

4th %ile



Estimated Premorbid Functioning



Current Intellectual Functioning


Verbal IQ

Vocabulary Similarities Arithmetic Digit span

108 High-average High-average Average Average

Performance IQ

Picture completion Block design
Picture arrangement

95 Average Average Average


WRMT—words WRMT—faces

75–90th %ile 10–25th %ile

AMIPB story recall Immediate Delayed

10–25th %ile 10–25th %ile

AMIPB gure recall Immediate Delayed

25–50th %ile 25–50th %ile


Graded naming test Semantic uency (‘animals’)

25–50th %ile 25–50th %ile

Visuoperceptual Skills

VOSP object decision

>5th %ile cut-o

Visuospatial Skills

AMIPB gure copy

No errors

Executive Function

Fluency—‘S’ Stroop test

11th %ile

2–4th %ile

Processing Speed


47th %ile

auditory verbal material. However, conversational speech was u- ent with no lapses and no word- nding di culties.

Object naming was intact. ere was no evidence of visuoper- ceptual or visuospatial impairment. Performance on executive tasks was a little poorer than expected. He was slow to complete the incongruent condition of the Stroop colour–word test, although he made only one error (2nd–4th percentile). Letter uency was reduced (S: 11th percentile) in comparison with relatively intact category uency (animals: 25–50th percentile). He scored in the moderate average range on the Hayling sentence completion task. Processing speed was normal.

ID expressed considerable anxiety about what he perceived to be the changes in his memory. Although the problems occurred more prominently at work, he reported that his mood was inclined to be low when he was away from the workplace. On a formal mood inventory he scored in the normal range for both anxiety and depression. Although there were no overt features of low mood and although he was generally cooperative and responsive on test- ing, there were several occasions in the course of the assessment when he seemed to give up in the face of an attention-demanding task. e MRI scan of the brain was normal with no evidence for atrophy.

120 SECTION 2 cognitive dysfunction


e neuropsychological pro le is therefore one of erratic scores on memory tests together with some executive ine ciency in the con- text of otherwise normal cognition. e overall impression, from the inconsistencies amongst the test scores and from his behav- iour on testing, was that these lower than expected scores are most unlikely to be neurogenic in origin.

Psychological impact

Cognitive de cits can have a profound impact on the psycho- logical dynamics of a couple and a family, particularly in the con- text of dementia as the patient’s cognitive, a ective, and mnestic processes disintegrate. Speci c cognitive problems impact on a person’s ability to function in particular ways: poor day-to-day memory makes it di cult to plan, organize, or anticipate what is going to happen, or to participate in the give-and-take of very much day-to-day conversation; visuospatial de cits may make it di cult to navigate familiar environments, even at home, or to function e ectively in terms of knowing where to nd things; apraxia may make it di cult to dress or to use everyday equip- ment (pens, cutlery) or appliances (remote control devices, microwave).

Di culty with such everyday activities—with concomitant reli- ance and dependence on others to negotiate even simple aspects of daily life—dramatically a ects a person’s sense of themselves in the world and in their relations with others. Such changes can be profoundly distressing as well as anxiety-provoking to the patient. On the other hand, in some cases—most notably behav- ioural variant frontotemporal dementia (bvFTD)—the patient’s unawareness of de cit is itself pathognomic of the disease, pos- ing the problem of dramatic changes for the carer and family but to which the patient appears indiferent. e neuropsychological assessment can therefore also be helpful in guiding the patient’s and/or the patient’s family’s understanding of the de cits, the development of strategies to assist in management of de – cits where possible, and the basis of supportive psychotherapy towards adaptation and adjustment to very changed relationship dynamics.


1. Hodges JR, Patterson K, Oxbury S, et al. Semantic dementia. Progressive uent aphasia with temporal lobe atrophy. Brain. 1992;115:1783–806.

2. Neary D, Snowden JS, Northen B, et al. Dementia of frontal lobe type. J Neurol Neurosur Ps. 1988;51:353–61.

3. Snowden JS, ompson JC, Stopford CL, et al. e clinical diagnosis of early-onset dementias: diagnostic accuracy and clinicopathological relationships. Brain. 2011;134:2478–92.

4. Buschke H. Cued recall in Amnesia. J Clin Exp Neuropsyc. 1984;6(4):433–40.

5. Grober E and Buschke H. Genuine memory de cits in dementia. Dev Neuropsychol. 1987;3:13–36.

6. Warrington EK. Recognition Memory Test. Windsor: NFER-Nelson Publishing Co Ltd, 1984.

7. Saxton J, McGonigle KL, Swihart AA, et al. e Severe Impairment Battery. Su olk: ames Valley Test Company, 1993.

8. Rosen WG, Mohs RC, and Davis KL. A new rating scale for Alzheimer’s disease. Am J Psychiatry. 1984 Nov;141(11):1356–64.

9. Wechsler D. Wechsler Memory Scale—Revised. New York, NY: Harcourt Brace Jovanovich, 1987.

10. Wechsler D. e Wechsler Adult Intelligence Scale—Revised. New York, NY: Harcourt Brace Jovanovich, 1981.

11. Folstein MF, Folstein SE, and McHugh PR. Mini-mental state. A practi- cal method for grading the cognitive state of patients for the clinician.
J Psychiat Res. 1975;12(3):189–98.

12. Bird CM, Papadopoulou K, Ricciardelli P, et al. Test-retest reliability, practice e ects and reliable change indices for the recognition memory test. Br J Clin Psychol. 2003 Nov;42(Pt 4):407–25.

13. Baxter DM and Warrington EK. Measuring dysgraphia: A graded- di culty spelling test. Behav Neurol. 1994;7(3–4):107–16.

14. Nelson HE. e National Adult Reading Test. Windsor: NFER-Nelson Publishing Co. 1991.

15. Lezak MD, Howieson DB, and Loring DW. Neuropsychological Assessment, 4th edn. New York, NY: Oxford University Press, 2004.

16. Wechsler D. Wechsler Adult Intelligence Scale, 4th edn. San Antonio, TX: Pearson, 2008.

17. Wechsler D. Wechsler Abbreviated Scale of Intelligence, 2nd edn (WASI- II). San Antonio, TX: NCS Pearson, 2011.

18. Coughlan AK, Oddy M, and Crawford JR. e BIRT Memory and Information Processing Battery (BMIPB). West Sussex: BIRT, 2009.

19. Baddeley A, Emslie H, and Nimmo-Smith I. Doors and People Test: A test of visual and verbal recall and recognition. Bury St Edmunds: ames Valley Test Company, 1994.

20. Welsh KA, Butters N, Hughes JP, et al. Detection and Staging of Dementia in Alzheimer’s Disease: Use of the Neuropsychological Measures Developed for the Consortium to Establish a Registry for Alzheimer’s Disease. Arch Neurol. 1992;49(5):448–52.

21. Wechsler, D. Wechsler Memory Scale, 3rd edn. San Antonio, TX: e Psychological Corporation, 1997.

22. Rohrer JD, Knight WD, Warren JE, et al. Word- nding di – culty: a clinical analysis of the progressive aphasias. Brain. 2008 Jan;131(Pt 1):8–38.

23. McKenna P and Warrington EK. Graded Naming Test. Windsor: NFER- Nelson Publishing Co. 1983.

24. Lambon Ralph MA, Patterson K, and Hodges JR. e relationship between naming and semantic knowkedge for di erent categories in dementia of Alzheimer’s type. Neuropsychologia. 1997;35(9):1251–60.

25. Dell GS, Schwartz, MF, Martin, N, et al. Lexical access in aphasic and nonaphasic speakers. Psychol Rev. 1997;104(4):801–38.

26. Baldo JV, Schwartz S, Wilkins D, et al. Role of frontal versus temporal cortex in verbal uency as revealed by voxel-based lesion symptom mapping. J Int Neuropsych Soc. 2006;12: 896–900.

27. Benson DF, Davis RJ, and Snyder BD. Posterior Cortical Atrophy. Arch Neurol. 1988;45(7):789–93.

28. Crutch SJ. Seeing why they cannot see: Understanding the syn- drome and causes of posterior cortical atrophy. J Neuropsychol. 2013. doi:10.1111/jnp.12011.

29. Warrington EK and James M. Visual Object and Space Perception Battery. Bury St Edmunds: ames Valley Test Company, 1991.

30. Goldenberg G. Imitating gestures and manipulating a mannikin— e representation of the human body in ideomotor apraxia. Neuropsychologia. 1995;33(1):63–72.

31. Reitan RM. Validity of the Trail Making test as an indicator of organic brain damage. Percept. Mot Skills. 1958;8:271–76.

32. Nelson H. A modi ed card sorting test sensitive to frontal lobe defects. Cortex. 1976;12:313–24.

33. DelisDC,KaplanE,andKramerJH.Delis–KaplanExecutiveFunction System (D–KEFS). San Antonio, TX: e Psychological Corporation, 2001.

34. Burgess P and Shallice T. e Hayling and Brixton Tests. Test manual. Bury St Edmunds, UK: ames Valley Test Company, 1997.

35. McDonald S, Flanagan S, Rollins J, et al. TASIT: A New Clinical Tool for Assessing Social Perception a er traumatic brain injury Journal of Head Trauma Rehabilitation. 2003;18:219–38.

36. Baron-Cohen S, Wheelwright S, Hill J, et al. e ‘Reading the Mind in the Eyes’ Test revised version: a study with normal adults, and adults with Asperger syndrome or high-functioning autism. J Child Psychol Psychiatry. 2001 Feb;42(2):241–51.

37. Beck AT, Steer RA, and Brown GK. Manual for the Beck Depression Inventory–II. San Antonio, TX: Psychological Corporation, 1996.

38. Sheikh JI and Yesavage JA. Geriatric Depression Scale (GDS): Recent Evidence and Development of a Shorter Version. Clinical Gerontology: A Guide to Assessment and Intervention. New York, NY: e Haworth Press, 1986.

39. Alexopolous GS, Abrams RC, Young RC, et al. Cornell Scale for Depression in Dementia. Biological Psychiatry. 1998;23:271–84.

CHAPTER 11 neuropsychological assessment 121


Acquired disorders
of language and speech
Dalia Abou Zeki and Argye E. Hillis


Although the words ‘speech’ and ‘language’ are o en used inter- changeably, each of these systems has a distinct function, relies on a distinct set of representations and processes, and engages a distinct neural network.

Language is a non-instinctive, culturally driven system of volun- tarily produced symbols, comprising receptive and expressive abili- ties allowing comprehension and communication of information respectively. Understanding and processing sound, word, phrase, sentence, and conversation involves retrieving vocabulary, con- cepts, grammar, and, on a higher scale, processing abstract infer- ences, idioms, or verbal problem-solving. ere are ve linguistic domains that comprise language (see Box 12.1).

Speech consists of the highly coordinated rapid motor func- tion responsible for the actual act of vocal expression of language. Regulation of speech occurs via basal ganglia, cerebellum, and cortical systems, with the corticobulbar tracts via the nuclei of the vagal, hypoglossal, facial and phrenic nerves maintaining con- trol and coordination of the muscles involved in speaking. ose include laryngeal, pharyngeal, palatal, lingual, oral, and respiratory muscles. Typically, the utterance of 2 words per second by a nor- mal speaker is equivalent to 14 linguistically distinct sounds (pho- nemes), each one requiring the contraction or relaxation of 100 muscles.1 Speech entails the combination of phonation (voicing), resonance (nasality), and articulation. It is also o en characterized by uency and prosody (Box 12.2).

Box 12.1 Linguists refer to ve domains that comprise the language system

1. Phonology: the sound system and linguistic rules of sound combinations, pronunciation, and perception.

2. Morphology: the linguistic rules of word structure and construction.

3. Semantics: the systematic meaning of words re ecting con- tent and utterance intent.

4. Syntax: the linguistic rules of sentence-element relationship or grammar.

5. Pragmatics: the rules for maintaining a conversation in terms of responsiveness, relevance, and so on.

Language localization

e outward production of language is a re ection of neural acti- vation in vast network of brain structures and regions in the cor- tex, basal ganglia, cerebellum, and brainstem. ere is clinical and imaging evidence of overlap in that network or with other networks of specialization that is responsible for the wide symptom spectrum following an acquired lesion. One lesion in an area can result in multiple de cits; lesions from multiple di erent sites can produce similar de cits; and multiple lesions4in elements of the same net- work can severely impact function. One of the most surprising ndings from functional neuroimaging studies is that the ‘language network’ is remarkably similar across language tasks and across individuals (Fig. 12.1).

Box 12.2 Speech consists of the following overlaid functions

1. Phonation: production of vocal sounds in relation to the length and mass of the membranous parts of the vocal cords. e duration of opening or closing of the vocal folds to pro- duce a voiced versus voiceless consonant is o en briefer than 20 msec.2 Intratracheal pressure must be held long enough so that the ‘ballistic opening gesture’ produces the desired consonant.3

2. Articulation: interruption of vocal sounds by pharyngeal, palatal, lingual, and oral muscle contractions. Phonemes, or speech sounds, like [m], [b], and [p] are labial; [l] and [t] are lingual. While consonants are produced by this mechanism, vowels are solely laryngeal in origin.

3. Fluency: speech uency (unlike language uency) o en refers to the ability to speak e ortlessly, and smoothly, without forward ow interruption. In some cases it refers to rate of speech. On average, a normal speaker utters 120 words per minute during a conversation; that is, 2 words per second.

4. Variations in pitch, loudness, and duration of syllables in speech: these can be used to convey meaning (e.g. sarcasm versus factual content), a ect (angry versus happy feeling), or even whether an utterance is a statement or a question (e.g. you are coming?).

cognitive dysfunction



Fig. 12.1 e ‘language network’—areas that are activated across a variety of language tasks across most healthy individuals. ese areas include posterior inferior frontal cortex (Brodmann’s area (BA) 44 and 45), a more dorsal posterior frontal area in BA 6, posterior middle/superior temporal cortex (in BA 22 and often BA 20/21), angular gyrus (BA 39), and posterior inferior temporal cortex (in BA 37). Panel (a) Areas activated during word generation.131 Panel (b) Areas of activation throughout picture naming.132 Panel (c) Areas of activation during passive watching and listening to video with language.

Yet, lesions to di erent nodes in the language tasks produce very di erent language impairments that are fairly predictable immedi- ately a er the lesion. However, the degree to which language will recover a year or more later is not predictable. Despite huge lesions that cover all of the ‘language network’, some individuals are able to recover language a year or so a er stroke. ese results allow two conclusions: (1) many areas that are recruited across all language tasks are not equally necessary for those tasks, and (2) it seems likely that there are no areas of the brain that are truly necessary for recovery of language at one year.

Certain manipulations in task paradigms allow functional mag- netic resonance imaging (fMRI) or positron emission tomography (PET) to reveal areas more important for some language tasks than others. Lesion studies allow one to test what areas are normally ‘necessary’ for a task; that is, one assumes that when function on a task is impaired only when a particular area is damaged, that area is necessary for the task. However, lesion studies depend on identify- ing a su cient number of people with lesions in all of the possible locations to test the hypotheses (or creating temporary lesions with transcranial magnetic stimulation, for example). Using a combina- tion of these methods, some organization of the language network has been revealed. For example, ventral and dorsal language path- ways have been proposed by some authors.5,6 It has been suggested that the ventral temporal pathway might be critical for mapping sound to lexical representations and meanings of words, while the dorsal frontoparietal pathway has been proposed to be critical for syntactic and articulatory processes.

Using a variety of techniques, it has been established that core language functions are le -lateralized in the majority of both right- and le -handers (95 per cent and 75 per cent, respectively).7 Only humans have this hemispheric specialization, most likely because of our reliance on language. While nearly all animal species com- municate in some form, language is what sets us apart as a species. However, some aspects of language, such as conceptual semantics, may be broadly and even bilaterally distributed.

124 SECTION 2 (a)

Disorders of language

Aphasia (in Greek ἀφασία, i.e. speechlessness) encompasses difficulty producing and/or understanding spoken language. Impairments in reading (alexia) and writing (agraphia) are o en associated with aphasia. Much of our understanding of aphasia has come from the study of vascular cases, although the principles arising from such cases have o en pro tably been applied to other causes, including neurodegenerative disorders which are dealt with in detail elsewhere (see chapter 34).

Vascular aphasia syndromes have not typically corresponded to linguistic domains because lesions typically involve vascular ter- ritories, rather than being restricted to the ‘dorsal frontoparietal language network’ or the ‘ventral temporal’ language network, for example. e vascular syndromes refer to a collection of frequently co-occurring symptoms that are observed together because they represent functions that depend on tissue supplied by the same cer- ebral vessel (which can be occluded and cause a stroke), therefore each vascular aphasia syndrome is also associated with other neu- rological de cits (e.g. Broca’s aphasia with right arm spastic mono- plegia or right spastic hemiplegia).

Terminology for the vascular syndromes may vary. Broca’s apha- sia, for example, is also referred to as ‘anterior’, ‘motor’, or ‘non- uent’ aphasia. Wernicke’s aphasia, on the other hand, is sometimes termed, ‘posterior’, ‘sensory’, or ‘ uent’ aphasia. e classic Broca– Wernicke–Lichtheim–Geschwind model was the result of the e orts of Broca, Wernicke, and Lichtheim in the nineteenth cen- tury, with later modi cation by Geschwind in 1967. Broca pro- posed that part of the second or third convolutions of the le inferior frontal gyrus has a role in speech production, or what he, and Bouillaud before him, called the faculty of spoken language.8,9 Wernicke observed that lesions in the posterior aspect of the supe- rior temporal gyrus resulted in impaired comprehension and uent but gibberish speech. He suggested this posterior superior tempo- ral gyrus has a role in speech perception through its connections with other language areas.10 Lichtheim synthesized the previous claims, adding an interfacing conceptual area.11 Comprehension, language uency (based on grammaticality, e ortful articulation, prosody, and melody), repetition, naming, reading, and writing are the language domains that characterize the vascular aphasia syn- dromes described in the next section.

Vascular aphasia syndromes Broca’s aphasia

Broca’s aphasia occurs a er a lesion or dysfunction in the poste- rior inferior frontal cortex, the distribution of the superior divi- sion of the le middle cerebral artery, now known as Broca’s area (see below). It is de ned as arduous, non- uent, telegraphic speech output, interrupted by word- nding pauses. Both speech and writing are characterized by agrammatic sentences, revealed by substitution and omission of function words (e.g. the, an) such as prepositions, in exions, and auxiliary verbs. ree character- istics constitute the hallmark of this syndrome: (1) agrammatism, (2) verbal apraxia, and (3) preserved comprehension. Apraxia of speech is a disturbance in motor programming of speech articula- tion. Patients are aware of their problem and struggle to try and correct their misarticulation by trial-and-error, repetitively yet

uneventfully. Groping articulatory movements are o en produced instead.

It has long been recognized that infarction solely a ecting Broca’s area causes a brief de cit in motor speech (‘apraxia of speech’) that recovers very quickly.12 Even lesions involving Broca’s area and its immediate surrounding areas deep into the brain, cause mutism that is replaced by a rapidly improving dyspraxic and e ortful artic- ulation, but no signi cant disturbance in language function per- sists.13 Lesions in this area typically cause de cits in action naming that are more severe than de cits in object naming. Infarctions that involve other structures beyond Broca’s area in this vascular terri- tory can cause the full-blown clinical syndrome of Broca’s aphasia. e structures most commonly associated with this presentation are the rolandic operculum, capsulostriatal and periventricular areas. When the entire territory is involved there may be a persis- tence of some symptoms.

Transcortical motor aphasia

Transcortical motor aphasia, also known as adynamic or extrasyl- vian motor aphasia, occurs following an injury to a ‘watershed area’ between the le middle cerebral artery (MCA) and the le anterior cerebral artery (ACA), in the mesial frontal lobe, also referred to as the supplementary motor area (SMA),14–16 is syndrome is char- acterized by poor spontaneous speech, with relatively good repeti- tion and comprehension.

Wernicke’s aphasia

Ten years a er Paul Broca’s description of the e ect of motor area lesion on the proper speech output, Karl Wernicke proposed that the le superior posterior temporal lobe is an area critical for lan- guage comprehension and processing. More recently, it has been recognized that other areas are critical for language comprehen- sion as well. Nevertheless, lesions in the inferior division of the le MCA, which supplies the posterior part of the temporal lobe and inferior parietal lobule, cause impairments in word meaning with- out disrupting uency of speech articulation, resulting in mean- ingless jargon in both spontaneous speech and repetition, now termed Wernicke’s aphasia. is syndrome consists of comprehen- sion and repetition impairments, anomia, semantic paraphasias (semantically related word substitutions) and phonemic parapha- sias (phonologically related word or nonword substitutions), and neologisms (jargon words). Alexia and agraphia are noted. ese individuals, in contrast to those with Broca’s aphasia, have poor insight regarding their de cits and seem unconcerned. Box 12.3 provides a case example of an individual with Wernicke’s aphasia at onset of stroke.

Lastly and interestingly, cases of crossed Wernicke’s aphasia in right-handed patients following lesions in the homologous area in the right hemisphere are reported.17

Transcortical sensory aphasia

is aphasia type is characterized by uent, circumlocutory speech with semantic jargon and poor comprehension. e key feature that distinguishes it from Wernicke’s aphasia is preserved repetition. It has been proposed that relatively spared repetition is due to pre- served integrity of arcuate fasciculus,16 but there is little direct evi- dence for this proposal. Others have proposed a right hemisphere contribution in language repetition given that transcortical sensory aphasia can occur post massive infarction involving the perisylvian


Transcortical mixed aphasia

Also known as isolation aphasia (or ‘isolation of the speech area’), it combines features of both transcortical sensory and motor aphasia. Repetition is preserved but there is reduced spontaneous speech, echolalia, and palilalia, or even mutism, along with impaired com- prehension, reading, and writing.21–24

Transcortical mixed aphasia, the term rst coined by Goldstein,14 follows lesions isolating the perisylvian language areas, thus the name ‘syndrome of isolation of the speech area’.25 Infarctions typi- cally include the watershed territory between the le ACA and MCA in addition to the watershed territory between the le MCA and PCA. Lesions in the le thalamus, putamen, and periventricu- lar white matter, and thalamo-mesancephalic infarcts have also been described.24,26

Prognosis is generally poor with persisting non- uency and unrecovered comprehension.

Conduction aphasia

ree major characteristics comprise the vascular syndrome of conduction aphasia: a relatively uent, though phonologically para- phasic speech; poor repetition, rst described by Lichtheim;11 and relatively spared comprehension.14,27–32 Repetitive self-corrections, word- nding di culties, and paraphrasing are attempts to approx- imate target phonemes, termed ‘conduit d’approche’.

In 1874, Wernicke indicated that the symptoms in one of his patients might possibly be due to the disconnection between the superior temporal and the inferior frontal gyri.10 is theory was later elaborated by Geschwind in 1968, giving rise to what is called the Wernicke–Geschwind model of aphasia.25 He considered that

CHAPTER 12 acquired disorders of language and speech 125

Box 12.3 A case of Wernicke’s aphasia

Mr T awoke from cardiac surgery and seemed ‘confused’. He was unable to follow even simple directions. His speech was uent and well-articulated, but consisted only of jargon. When asked to state the month, he said, ‘I haven’t seen her (frip) (freep) around here, I know that.’ He was not able to name any objects orally or in writing correctly although he gestured correctly their use. He called many of them ‘another ap thing or something’. He was guessing on both spoken and written word/picture-matching tasks. His repetition was similar to his spontaneous speech: u- ent, well-articulated English jargon, with occasional neologisms. MRI of the brain showed severe hypoperfusion of the le tem- poral cortex, including Wernicke’s area. He was not a candidate for thrombolytics due to his recent surgery but underwent inves- tigational therapy to increase perfusion. Repeat MRI on day 3 showed that he had a reperfused le temporal cortex (either a result of the intervention or due to spontaneous recanalization; Fig. 12.2). Repeat language testing on day 3 showed resolution of his language impairment, with good comprehension, repetition, naming, and spontaneous speech.

Transcortical sensory aphasia is typically caused by poste- rior lesions involving the anterolateral thalamus, temporoparieto- occipital junction (watershed territory between the MCA and the posterior cerebral artery (PCA) territories), or second and third temporal gyri.20 Semantic variant PPA, Alzheimer’s disease, and Creutzfeldt–Jakob disease can cause a similar syndrome.


126 SECTION 2 cognitive dysfunction

Fig. 12.2 Scans of individual with Wernicke’s aphasia at day 1, which resolved by day 3. Top panel: Di usion-weighted image (left) showing small acute infarct in left insula and perfusion-weighted image (right) at day 1, showing hypoperfusion of left temporal cortex, including Wernicke’s area. Lower panel: Di usion-weighted image (left) and perfusion-weighted image (right) at day 3, showing reperfusion of left temporal cortex.

lesions to the arcuate fasciculus, a large bundle of bres connect- ing the frontal and posterior temporal cortex (and angular gyrus), caused the repetition impairments in this so-called disconnection syndrome.33–35 However, most recent aphasiologists have ascribed the repetition impairment to limited working memory, and have found the associated lesions to be in areas critical for working memory: inferior parietal lobule (supramarginal and angular gyri), inferior frontal cortex, posterior temporal lobe, and/or their white matter connections. Box 12.4 describes a case of an individual with conduction aphasia.

On language testing, Mrs M’s speech was well-articulated but she made some phonological errors that were self-corrected, and she had hesitations. Sentences were short and had simple syntax. She was accurate in following simple commands, but made errors on three-step commands. She understood simple, active sentences, but guessed at comprehension of passive sentences. Repetition of monosyllabic and bisyllabic words was accurate, but repetition of polysyllabic words and of sentences was completely incorrect. She o en paraphrased the sentence rather than repeating it. (e.g. ‘It’s a sunny day in Baltimore’ was repeated as ‘it’s nice out’.). Her forward digit span was three; her backward digit span was two. Her naming

was mildly impaired. She had di culty spelling and reading unfa- miliar words (pseudowords) but correctly read and spelled words. She had language therapy ve days per week for three weeks, and her language de cits resolved.

Box 12.4 Case study of conduction aphasia

Mrs M is a 72-year-old woman who noted sudden di culty in conversing on the telephone. Her friend mentioned the title of book they were going to read for book club, and she was una- ble to repeat it correctly or write down the name of the book. She reports that she was ‘stuttering’ and having trouble nding words. She looked up the phone number of her physician and could read it, but was not able to retain it long enough to cor- rectly dial the number. She decided to wait until her husband got home from work. When he arrived four hours later her speech was unchanged so he called an ambulance. On arrival to the hos- pital, she was found to be in atrial brillation. An MRI showed an acute infarct (and comparable perfusion defect) in the le parietal cortex, including supramarginal gyrus, thought to be embolic (Fig. 12.3).

Global aphasia

Destruction of anterior and posterior language areas causes reduc- tion of all faculties of language, including comprehension and speech output.27 Even though the most common cause behind this debilitating language disorder is a large le hemisphere ischae- mic stroke due to carotid artery or middle cerebral artery steno- sis or occlusion, cases following smaller haemorrhagic strokes are reported.36 Global aphasia can be the initial presentation in a patient who later recovers into Broca’s aphasia or transcortical motor aphasia. In this case, there is generally evidence of spared Wernicke’s area.37 Early comprehension recovery may result from reperfusion of Wernicke’s area,38 while later recovery of compre- hension may result from reorganization of the language network such that another area of the brain assumes of the function of the damaged area.39 Broca’s and Wernicke’s area may thus be hypoper- fused in the acute period, such that the area is dysfunctional, caus- ing global aphasia. When the area becomes reperfused through development of collateral blood ow or through treatment, the individual may show the vascular syndrome corresponding to the infarct rather than the initial vascular syndrome corresponding to the hypoperfused tissue (see Fig. 12.4).

Subcortical aphasia

Subcortical lesions have been reported to cause language de cits, ranging from anomia to global aphasia.40–46 Fluctuating jargon aphasia with impaired uency is o en observed in patients with thalamic lesions.47

Two distinct mechanisms can account for subcortical aphasia. One is that plaques in the middle cerebral artery cut o blood sup- ply to the lenticulostriate arteries, causing infarcts in the basal gan- glia and subcortical white matter, but also cause hypoperfusion of the cortex, causing a variety of aphasia syndromes.48 Aphasia due to cortical hypoperfusion has been demonstrated with single pho- ton emission computed tomography (SPECT),49 positron emission tomography (PET),45,50,51 and perfusion-weighted imaging.48,52 Improvement in cortical perfusion and metabolism corresponds to recovery of aphasia.48,52–57 It has been also shown that recanaliza- tion of an occluded M1 branch of MCA in subjects with aphasia and a striatocapsular infarct can reverse the aphasic syndrome.45

Diaschisis, distant cortical hypometabolism caused by reduced input from the infarcted area, can account for aphasia due to tha- lamic lesions54,58 and perhaps aphasia due to other subcortical lesions.59–61

CHAPTER 12 acquired disorders of language and speech 127

Fig. 12.3 Di usion-weighted image (left) and perfusion-weighted image (right) at day 1 of individual with acute conduction aphasia.

Fig. 12.4 Di usion-weighted image (left) showing infarct in superior division MCA territory that included Broca’s area, and perfusion-weighted image (right) showing larger area of hypoperfusion that included Wernicke’s area in a patient who had global aphasia acutely. When he showed reperfusion of Wernicke’s area, his comprehension improved, thus he had a Broca’s aphasia.

128 SECTION 2 cognitive dysfunction Alexia and agraphia

Alexia is de ned as the loss of reading ability following a brain insult while agraphia is impairment in writing ability following brain damage. Both these syndromes are discussed in more detail in the chapter concerning alexia and agraphia but are brie y con- sidered here for sake of completeness within the framework of lan- guage disorders (chapter 18).

Pure alexia is at times referred to as visual alexia or word blind- ness, given that reading activates the le lateral occipitotemporal sulcus, mainly the so-called visual word form area (VWFA) area.62 is area is reliably activated in reading tasks, but is also activated in spelling and other lexical tasks (see reference 63 for review of this controversial issue). Spelling dyslexia or surface dyslexia refers to a patient who tries to spell or sound each word and guess its meaning from the way it sounds. is presentation follows occipitotemporal damage.64

A neural model for reading and writing was first suggested by Dejerine in 189265 and supported in 1965 by Geschwind.66 This model distinguishes between alexia without agraphia fol- lowing occipital lobe lesions involving the splenium and its radiations, and alexia with the agraphia following a lesion to the angular gyrus. In the latter, other parietal signs are com- mon on presentation (e.g. apraxia, anomia, and Gertsmann syndrome). Although Geschwind hypothesized that the angular gyrus is crucial for differentiating letters, Japanese researchers have argued that the neural circuit for this faculty is far more complicated. Ideographic (Kanji) and syllabic (Kana) reading and writing can be affected by various lesion areas, offering an additional emphasis on this extensive processing neuronal net- work. The latter was then specified as dual process, considering the angular gyrus as a the node for letter phonological process- ing and the posterior inferior temporal area as a node for letter semantic processing.67

Although ischaemia in the territory of the posterior cerebral artery is the most reported aetiology behind this reading impair- ment, compression to this artery by tentorial herniation or tumours is also reported.68,69 Transitory alexia without agraphia was reported in an HIV-positive patient with toxoplasma encephalitis and another with neurocycticercosis.70,71

In agraphia, spelling can normally be accomplished via a direct lexical method of recalling a word’s spelling or via a sublexical pho- nological method of sounding out its phonemes (speech sounds) and transforming them to graphemes (abstract letter identities). Retrieval of the learned spelling is likely to be important for the spelling of most familiar words and is critical for spelling irregular familiar words; while the computing plausible spellings of unfamil- iar words (like proper names) and spelling of regular words may depend almost entirely on the sublexical phonological method of spelling. Either of these spelling mechanisms can be disrupted independently, indicating that the neural networks that support these cognitive processes are distinct.72

A common spelling impairment a er stroke is a de cit in hold- ing the string of graphemes in working memory (‘the graphemic bu er’) while the word is spelled. is spelling impairment equally a ects regular and irregular words, and familiar and unfamiliar words, but a ects longer words more than short words. It results in deletions, insertions, transpositions, and substitutions of graph- emes.73 Agraphia can be part of an aphasia syndrome, thus termed

aphasic ‘agraphia’ where spelling and grammatical errors are de n- ing features. Pure agraphia has also been reported.63

‘Constructional agraphia’ has been described, with disturbances in the perception of spatial relations resulting in wrongly arranged words or letters, either haphazardly, or diagonally, or superim- posed. A right-to-le arrangement is also noted where only the right side of the page is used. In this case, researchers relate the writing disorder to le hemispatial neglect, a ecting responsive- ness to stimuli and space on the le side of the viewer. Right hemis- patial neglect can also occur but tends to a ect the right sides ( nal letters) of individual words, irrespective of the location with respect to the viewer. ‘Apraxic agraphia’ is reported a er frontal and pari- etal lesions, due to impaired motor planning required to form the proper shapes of letters and words.

Pure word deafness

Pure word deafness refers to an inability to recognize spoken words in the absence of a peripheral de cit in auditory acuity or more general auditory discrimination impairment. In his 1884 memoir, Lichtheim mentioned the patient who produced no paraphasias or paragraphias and had no dyslexia, but had a repetition impairment and di culty communicating using any means other than writing. When asked to write to dictation, though, the patient complained of an inability to hear. Pure word deafness, also known as ‘auditory verbal agnosia’, can occur a er lesions in the le superior tempo- ral gyrus and the superior temporal sulcus, both anterior. Bilateral temporal lesions can cause pure word deafness or a more general auditory discrimination de cit referred to as cortical deafness.74

Causes of aphasia

Any acute or transient insult or progressive pathologic process that a ects the language network can cause aphasia. e most common lesion is ischaemic stroke,75 and only ischaemic stroke typically causes the vascular syndromes described above. Haemorrhagic stroke, central nervous system infections,76,77 tumours, and trau- matic brain injury78 are known aetiologies. Neurodegenerative diseases79 and demyelinating diseases are reported also.80,81 Transient ischaemic attacks, complicated migraines, and seizures cause transient aphasia. Primary progressive aphasia refers to three syndromes: the non- uent, agrammatic variant is most commonly caused by a tauopathy such as frontotemporal degeneration-tau (FTLD-t), progressive supranuclear palsy, or corticobasal degen- eration; the semantic variant is usually caused by frontotemporal degeneration-ubiquitin (FTLD-u); the logopenic variant is most commonly caused by Alzheimer’s disease pathology.82 Primary progressive aphasia is considered in detail in chapter 34.

Disorders of speech

Speech output is a highly organized task that requires coordination of respiratory musculature, larynx, pharynx, palate, tongue, and lips, via control by extrapyramidal structures, cerebellum, basal ganglia, and the corticobulbar tracts. Motor speech disorders are the result of an insult at any level of this system or multiple levels. Muscle weakness, paralysis, spasticity, and poor coordination are all reported ndings.83 A way to categorize this type of movement disorder is into the phenotypical presentation, as various dysar- thrias or apraxia of speech.

e dysarthrias

Darley and colleagues classi ed the dysarthrias based on their e ects on rate, range, tone, and timing of movement into the fol- lowing categories: accid, spastic, mixed spastic and accid, ataxic, hypokinetic, hyperkinetic, and unilateral upper motor neuron dysarthrias.83,84

It was reported by the European Brain Council that about 20– 30 per cent of people who have a stroke experience muscular dis- turbances impairing speech output.85 More than 100 muscles are responsible for a proper articulation and phonation, important for the strength, speed, range, accuracy, steadiness, and tone of the speech.86 In clinical practice, assessment of speech should be based on objective criteria about auditory–perceptual character- istics, repetition rate, oral mechanisms, and intelligibility testing. e last can be examined using the Assessment of Intelligibility in Dysarthric Speakers, for example.87

Flaccid dysarthria

Any impairment at the level of the cranial or spinal nerves innervat- ing any of the muscles assisting speech output results in weakness of the corresponding muscles a ecting several aspects of speech.84 Lesions involving the motor nuclei in the medulla and lower pons can cause this disorder. Disorders of the neuromuscular junction can also cause accid dysarthria.

Because the insult involves a nal common pathway, sole a ected muscles can be observed. Although the presentation depends on the nerves a ected, common features may be observed like hyper- nasality due to reduced velar movement and subsequent nasal emission.86 Audible inspiration and hypophonia due to paralysis of unilateral or bilateral vocal folds in abducted position follows involvement of the vagal nerve. Pronunciation of lingual sounds becomes di cult following insults to the hypoglossal nerve.

Wallenberg’s lateral medullary syndrome is the most common aetiology and occurs with a constellation of neurological symp- toms (dizziness, nystagmus, crossed sensory loss, etc.), in addition to accid dysarthria.

Besides vascular causes, dysarthria has been described in mus- cular disorders, such as adult-onset myotonic dystrophy. Slowing down of relaxation of the muscles of the facial, jaw, and neck mus- culature a er rest or activity are responsible for the dysarthria that is characterized by monotony, hypernasality, hoarseness, shorter stretches of speech, slow speech rate, and reduced intelligibility.88 Warming-up phenomenon can be used for improving speech out- put.89 Myasthenia gravis is the most common cause of accid dysar- thria at the level of the neuromuscular junction. A bilateral insult to the vagal nerve, usually infectious in origin, can cause a nasal speech due to bilateral palatal paralysis. Bilateral insults to cranial nerve VII as seen in Guillain–Barre syndrome, Lyme disease, or sarcoidosis cause problems with consonant output, such as ‘p’ and ‘b’.

Ataxic dysarthria

Ataxic dysarthria follows an insult to cerebellar structures, mainly the superior cerebellar peduncle or brachium conjunctivum.90 Loss of motor organization and coordination of speech-responsible mus- cles is the key feature. e classic presentation is a ‘drunken quality’ of speech. e characteristic scanning speech is slurred, monoto- nous, with poor pitch control, and with unnatural separation of

the syllables of words. Tremor of the laryngeal and respiratory muscles is common.91 Breath may seem not enough for complet- ing the utterance; a pause followed by explosive output is common. Intermittent hypo- and hypernasality is observed, suggesting an improper timing of the velar and articulatory gestures for conso- nants.92 However, there is also abnormal variability in duration and intensity of vowel prolongation.

Common aetiologies of ataxic dysarthria include multiple scle- rosis, spinocerebellar ataxia syndromes, paraneoplastic cerebellar degeneration, as well as stroke or tumour in the cerebellum.

Unilateral upper motor neuron dysarthria

ere are several neurological disorders of speech that are due, in part, to unilateral damage to the pyramidal tracts.93–95 Speech is mildly imprecise; phonation is harsh and low-pitched. is speech disturbance follows an insult to the upper motor neuron(s) that transmits the signal via cranial or spinal nerves to the articulation muscles.

Darley86 and Melo96 described this entity as impairment in artic- ulation precision with ‘incomplete pronunciation’. Added to this, Ropper97 reported slowed speaking rates and monotonous voice as common features.

Pure dysarthria is generally observed with face and tongue weak- ness and is the result of 1 per cent of lacunar strokes involving the corona radiate or the internal capsule.98,99 Genu of the internal capsule or hemispheric strokes that include the mouth area of the motor strip in the precentral gyrus are the most common lesion sites causing this type of dysarthria.

Spastic dysarthria

Damage to bilateral corticobulbar tracts by vascular, demyelinat- ing, or motor neuron disease result in pseudobulbar palsy, the symptoms of which include ‘spastic’ dysarthria and pseudobulbar lability (laughter and crying).84 De ning features are imprecision, monotony, hypernasality, ‘strangled’ breathy voice, pitch breaks, excess stress, and slow rate.83

Aetiologies include bilateral strokes, midbrain or upper pon- tine strokes, central pontine myelinolysis, bilateral in ammatory or infectious encephalitis, and progressive supranuclear palsy. Amyotrophic lateral sclerosis causes a mixed upper and lower motor neuron dysarthria, but the spastic component is o en prominent.

Apraxia of speech

Apraxia of speech (AOS) is a motor speech disorder that can occur in the absence of aphasia or dysarthria. is disorder of speech has been the subject of continuous debate regarding its characteris- tics, corresponding anatomical lesions, and mechanism of de cits. It o en occurs in the context of Broca’s aphasia84 but can occur in isolation.100,101 While aphasic patients have a problem selecting the proper phonemes, apraxic individuals have a di culty in the motor execution of this same phoneme.102 ey tend to have characteristi- cally abnormal prosody103 but are aware of their de cits, in contrast to the patients with conduction aphasia.101 In contrast to dysarthria, which results in consistent and predictable errors, apraxia of speech results in inconsistent and non-predictable utterances.84,86,88

Brie y, though no single symptom has been solely attributed to AOS, Wertz103 described ve features of the disorder: (1) e ortful

CHAPTER 12 acquired disorders of language and speech 129

130 SECTION 2 cognitive dysfunction

trial and error with groping, (2) self correction of errors, (3) abnor- mal rhythm, stress, and intonation, (4) inconsistent articulation errors on repeated speech productions of the same utterance, and (5) di culty initiating utterances.

De ning AOS in terms of anatomical lesions has been controver- sial. Broca’s area has been found to be associated with AOS in acute and chronic stroke,20,104 although other chronic lesion studies have found that failure to recover from AOS is associated with lesions in le temporoparital cortex,101 the anterior superior insula,105 and the basal ganglia.84,106,106

AOS is usually caused by stroke, due to a clot in the superior division of the le middle cerebral artery. However, any lesion that a ects the le inferior frontal cortex, such as tumour, abscess, or focal atrophy can cause AOS. AOS is one of the two possible key features (along with agrammatic speech) of non- uent agrammatic variant of primary progressive aphasia.82

Treatment of aphasia

Recovery of language function following vascular impairments has been the subject of extensive controversy. Knowing that this recovery still occurs with the persistence of the lesion,108 the various factors predicting outcome remain controversial. ough transformation in aphasia types in the acute phase, mainly from non- uent to uent, not the opposite, and from severe to a milder form, is noted in 30–60per cent of aphasics,109 the severity of the


training appliance to compensate for hypernasality,132 and environ- mental listener training are used modalities. Computerized so – ware to increase single function ability has also been implemented.


1. Lenneberg EH. Biological Foundations of Language. Oxford: Wiley, 1967.

2. Ludlow CL and Lou G. Observations on human laryngeal muscle control. In: N Fletcher and P Davis (eds). Controlling Complexity and Chaos: 9th vocal fold Physiology Symposium. San Diego, CA: Singular Press, 1996.

3. Borden GJ and Harris KS. Speech Science Primer: Physiology, Acoustics, and Perception of Speech, 2nd edn. Baltimore, MD: Williams and Wilkins, 1984.

4. Kertesz A. e Western Aphasia Battery. Philadelphia, PA: Gruyne & Stratton, 1982.

5. Poeppel D and Hickok G. Towards a new functional anatomy of lan- guage. Cognition. 2004 May–Jun;92(1–2):1–12.

6. Saur D, Kreher BW, Schnell S, et al. Ventral and dorsal pathways for language. Proc Natl Acad Sci USA. 2008 Nov 18; 105(46):18035–40.

7. Knecht S, Dräger B, Deppe M, et al. Handedness and hemispheric language dominance in healthy humans. Brain. 2000;Dec;123:Pt 12:2512–18.

8. Broca P. Perte de la parole. Bulletins de la Societé Anthropologique de Paris. 1861;2:235–8.

9. Bouillaud J. Recherches cliniques propres à démontrer que la perte de la parole correspond à la lésion des lobules antérieures du cerveau. Archives Générales de Médecine. 1825;8:25–45.

10. Wernicke C. Der aphasische symptomen complex. Breslau: Cohn and Weigert, 1874.

11. Lichtheim L. On aphasia. Brain. 1885;7:433–84.
12. Mohr J. Broca’s area and Broca’s aphasia. In: H Whitaker (ed.). Studies

in Neurolinguistics, Vol 1. New York, NY: Academic Press, 1976,

pp. 201–35.
13. Mohr J, Pessin M, Finkelstein S, et al. Broca’s aphasia pathologic and

clinical. Neurology. 1978 Apr;28(4):311–24.
14. Goldstein K. Language and Language Disturbances: Aphasic Symptom

Complexes and their Signi cance for Medicine and eory of Language.

New York, NY: Grune & Stratton, 1948.
15. Kornyey E. Aphasie transcorticale et echolalie: Le probleme de

l’initiative de la parole. Cogn. Neuropsychol. 1975;(3):291–308.
16. Rubens A. Aphasia with infarction in the territory of the anterior cer-

ebral artery. Cortex. 1975 Sep;11(3):39–50.
17. Sweet EW, Panis W, and Levine DN. Crossed Wernicke’s aphasia.

Neurology. 1984 Apr;34(4):475–9.
18. Grossi D, Trojano L, and Soricelli A. Mixed transcortical aphasia: clini-

cal features and neuroanatomical correlates. A possible role of the right

hemisphere. Eur Neurol. 1991;31(4):204–11.
19. Turkeltaub PE, Messing S, Norise C, et al. Are networks for residual

language function and recovery consistent across aphasic patients?

Neurology. 2011 May 17;76 (20):1726–34.
20. Alexander M, Hiltbrubber B, and Fischer R. Distributed anatomy of

transcortical sensory aphasia. Arch Neurol. 1989 Aug;46(8):885–92. 21. Maeshima S, Uematsu Y, and Terada T. Transcortical mixed aphasia

with le frontoparietal lesions. Neuroradiology. 1996 May;38 Suppl

22. Nagaratnam N, Grice D, and Kalouche H. Optic ataxia following unilat-

eral stroke. J Neurol Sci. 1998 Mar 5;155(2):204–7.
23. Bougousslavsy J, Regli F, and Assal G (1985) Isolation of speech area

from focal brain ischemia. Stroke. 1985;16(3):441–3.
24. Bogousslavsky J, Regli F, and Assal G. Acute transcortical mixed

aphasia, a carotid occlusion syndrome with pial and watershed infarcts.

Brain. 1988 Jun;111 (3):631–41.
25. Geschwind N, Quadfasel FA, and Sagarra JM. Isolation of the speech

initial presentation predicts the nal outcome.
spontaneous recovery in the rst few months has been related to the lesion size and location,112 age, and premorbid intelligence.113 Moreover, systems or multivariate databases of combined clinical and functional imaging data have been introduced to provide indi- vidual outcome prediction post vascular aphasia.114,115 It has been reported that all but severely aphasic patients improve by 70 per cent of their maximum potential by 90 days, as long as those who are aphasic receive at least some speech and language therapy.116 However, controversy still exists concerning the e cacy of speci c treatment modalities and the correlation between the intensity of the treatment and outcome.117

Nevertheless, there is strong evidence that recovery takes place by a number of di erent mechanisms, and can be augmented by speech and language therapy, as well as non-invasive brain stimula- tion techniques, such as transcranial magnetic stimulation (TMS), and transcranial direct current stimulation (tDCS).118–125

Pharmacotherapy with stimulants,126 cholinesterase inhibitors, and dopamine agonists127 has also been suggested for therapy augmentation. More clinical trials are needed for further proof of e cacy.

Treatment of dysarthria

Management strategies for patients with acquired dysarthria vary

according to the severity and type of dysarthria. However, the over-

all cornerstone of therapy is enhancing orofacial muscle strength

and mobility. Intelligibilty improvement with these techniques has

been reported in single case or small group studies.128,129 Post-

stroke dysarthria is best managed by targeting respiratory, phona-

tory, articulatory, and resonatory systems for a more intelligible

utterance,131 Behavioural compensation through reduction of rate

of speech, provision of prosthetic devices, example palatal li , or

e extent of

area. Neuropsychologia. 1968;6(4):327–40.

26. Rapcsak S, Krupp L, Rubens AB, et al. Mixed transcortical aphasia with- out anatomic isolation of the speech area. Stroke. 1990 Jun;21(6):953–6.

27. Kertesz A. Aphasia and Associated Disorders. New York, NY: Grune & Stratton, 1979.

28. Kertesz A. Aphasia. In: JA Frederiks (ed.). Handbook of Clinical Neurology, Vol 45: Clinical Neuropsychology. Amsterdam: Elsevier, 1985, pp. 287–332.

29. Kohn S. Conduction Aphasia. Mahwah, NJ: Erlbaum, 1992.

30. Benson D and Ardila A. Conduction aphasia: a syndrome of language
network disruption. In: H Kirshner (ed.). Handbook of Speech and
Language Disorders. 1994. New York, NY: Mercel Dekker, pp. 149–64.

31. Benson D and Ardila A. Aphasia: A Clinical Perspective. New York,
NY: Oxford University Press, 1996.

32. Bartha L and Benke T. Acute conduction aphasia: an analysis of
20 cases. Brain Lang. 2003 Apr;85(1):93–108

33. Tanabe H, Sawada T, and Inoue N. Conduction aphasia and arcuate
fasciculus. Acta Neurol Scand. 1987 Dec;76(6):422–7.

34. Geldmacher D, Quigg M, and Elias W. MR tractography depicting
damage to the arcuate fasciculus in a patient with conduction aphasia.
Neurology. 2007 Jul 17;69(3):321.

35. Yamada K, Nagakane Y, and Mizuno T. MR tractography depicting
damage to the sarcuate fasciculus in a patient with conduction aphasia.
Neurology. 2007 Mar 6;68(10):789.

36. Kumar R, Masih A, and Pard J. Global aphasia due to thalamic hemor-
rhage: A case report and review of the literature. Arch Phys Med Rehabil.
1996 Dec;77(12):1312–5.

37. Blumenfeld H. Neuroanatomy through Clinical Cases, 2nd edn.
Sunderland, MA Sinauer Associates, 2010.

38. Hillis AE, Barker P, Beauchamp N, et al. Restoring blood pressure rep-
erfused Wernicke’s area and improved language, Neurology. 2001 Mar
13;56 (5):670–2.

39. Saur D, Lange R, Baumgaertner A, et al. Dynamics of language reor-
ganization a er stroke. Brain. 2006 Jun;129 (Pt 6):1371–84.

40. Damasio A, Damasio H, Rizzo M, et al. Aphasia with nonhemorrhagic
lesions in the basal ganglia and internal capsule. Arch Neurol. 1982

41. Naeser M, Alexander M, Helm-Estabrooks N, et al. Aphasia with
predominantly subcortical lesion sites. Description of three capsular/
putamenal aphasia syndromes. Arch Neurol. 1982 Jan;39(1):2–14.

42. Megens J, van Loon J, Go n J, et al. Subcortical aphasia from a tha-
lamic abscess. J Neurol Neurosur Ps. 1992;55:319–21.

43. Ferro JM and Kertesz A. Comparative classi cation of aphasic disor-
ders. J Clin Exp Neuropsychol. 1987 Aug;9(4):365–75.

44. Weiller C, Ringlestein EB, Reiche W, et al. e large striatocapsular infarct: A clinical and pathophysiological entity. Arch Neurol. 1990

45. Weiller C, Willmes K, Reiche W, et al. e case of aphasia or neglect
a er striatocapsular infarction. Brain. 1993 Dec;116 (Pt6):1509–25.

46. Mazzocchi F and Vignolo L. Localisation of lesions in apha-
sia: Clinical-CT scan correlations in stroke patients. Cortex. 1979

47. Mohr J, Walters W, and Duncan G. alamic hemorrhage and Aphasia.
Brain Lang. 1975 Jan;2(1):3–17.

48. Hillis AE, Wityk RJ, Barker PB, et al. Subcortical aphasia and neglect in
acute stroke: the role of cortical hypoperfusion. Brain. 2002 May;125(Pt

49. Skyhøj-Olsen T, Bruhn P, and Oberg RG. Cortical hypoperfu-
sion as a possible cause of ‘subcortical aphasia’. Brain. 1986

50. Nadeau SE and Crosson B. Subcortical Aphasia. Brain Lang. 1997

51. Démonet J. Subcortical aphasia(s): a controversial and promising topic.
Brain Lang. 1997 Jul;58(3):410–7.

52. Croquelois A, Wintermark M, Reichhart M, et al. Aphasia in hypera-
cute stroke: language follows brain penumbra dynamics. Ann Neurol. 2003 Sep;54(3):321–9.

53. Baron J, D’Antona R, Pantano P, et al. E ects of thalamic stroke on energy metabolism in the cerebral cortex. A Positron Tomography study in man. Brain. 1986 Dec;109 (Pt 6):1243–59.

54. Vallar G, Perani D, Cappa S, et al. Recovery from aphasia and neglect a er subcortical stroke: neuropsychological and cerebral perfusion study. J Neurol Neurosur Ps. 1988 Oct;51(10):1269–76.

55. Hillis AE, Kane A, Tu ash E, et al. Reperfusion of speci c brain regions by raising blood pressure restores selective language functions in suba- cute stroke. Brain Lang. 2001;79(3):495–510.

56. Hillis AE, Ulatowski JA, Barker PB, et al. A pilot randomized trial of induced blood pressure elevation: e ects on function and focal perfu- sion in acute and subacute stroke. Cerebrovasc Dis. 2003;16(3):236–46.

57. Hillis AE, Wityk RJ, Beauchamp NJ, et al. Perfusion-weighted MRI as a marker of response to treatment in acute and subacute stroke. Neuroradiology. 2004 Jan;46(1):31–9.

58. Perani D, Vallar G, Cappa S, et al. Aphasia and neglect a er subcorti- cal stroke. A clinical/cerebral perfusion correlation study. Brain. 1987 Oct;110(Pt 5):1211–29.

59. Metter E, Wasterlain C, Kuhl D, et al. FDG positron emission computed tomography in a study of aphasia. Ann Neuro. 1981 Aug;10(2):173–83.

60. Metter E. Neuroanatomy and physiology of aphasia: evidence from positron emission tomography. Aphasiology. 1987;1:3–33.

61. Wallesch C and Papagno C. Subcortical aphasia. In: F Rose, R Whurr, and M Wyke (eds). Aphasia. London: Whurr, 1988, pp. 256–87.

62. Dehaene S and Cohen L. e unique role of the visual word form area in reading. Trends Cogn. Sci. 2011 Jun;15(6):254–62.

63. Hillis AE. Neural correlates of the cognitive processes underlying reading: Evidence from Magnetic Resonance Perfusion Imaging. In:
P Cornelissen, P Hansen, M Kringelbach, and K Pugh (eds). e Neural Basis of Reading. Oxford: Oxford University Press, 2010, pp. 264–80.

64. Bub D and Kertesz A. Deep agraphia. Brain Lang. 1982 Sep;17(1):146–65.

65. Dejerine J. Contribution a I’etude anatomo-pathologique et clinique des di erentes varietes de cecites verbale. Memoires de la Societe Biologique. 1892;4:61–90.

66. Geschwind N. Disconnection syndromes in animals and man. Brain. 1965;88:237–94.

67. Iwata M. Kanji versus Kana. Neuropsychological correlates of the Japanese writing system. Trends Neurosci. 1982;7:290–3.

68. Caplan LR and Hedley-Whyte T. Cuing and memory dysfunction in alexia without agraphia. A case report. Brain. 1974 Jun;97(2):251–62.

69. Cohen D, Salanga V, Hully W, et al R. Alexia without agraphia. Neurology. 1976 May;26(5):455–9.

70. Luscher C and Horber FF. Transitory alexia without agraphia in HIV positive patient su ering from toxoplasma encephalitis: A case report. Eur Neurol. 1992;32(1):26.

71. Verma A, Singh N, and Misra S. Transitory alexia without
agraphia: A disconnection syndrome due to neurocysticercosis. Neurol India. 2004 Sep;52(3):378–9.

72. Purcell JJ, Turkeltaub PE, Eden GF, et al. Examining the central and peripheral processes of written word production through meta-analysis. Front Psychol. 2011 Oct 11;2:239.

73. Cloutman LL, Newhart M, Davis CL, et al. Neuroanatomical corre- lates of oral reading in acute le hemispheric stroke. Brain Lang. 2011 Jan;116(1):14–21.

74. Kertesz A. Aphasia in clinical practice. Can Fam Physician. 1983 Jan;29:128–32.

75. Goodglass H. Understanding Aphasia. San Diego, CA: Academic Press, 1993.

76. Otero E, Cordova S, Diaz F, et al. Acquired epileptic aphasia (the Landau–Kle ner syndrome) due to neurocysticercosis. Epilepsia. 1989 Sep-Oct;30(5):569–72.

77. Senda J, Ito M, Atsuta N, et al. Paradoxical brain embolism induced by Mycoplasma pneumoniae infection with deep venous thrombus. Intern Med. 2010;49(18):2003–5.

CHAPTER 12 acquired disorders of language and speech 131

132 SECTION 2 cognitive dysfunction

78. Reeves RR and Panguluri RL. Neuropsychiatric complications of traumatic brain injury. J Psychosoc Nurs Ment Health Serv. 2011 Mar;49(3):42–50.

79. Rohrer J, Rossor M, and Warren J. Alzheimer’s pathology in primary progressive aphasia. Neurobiol Aging. 2012 Apr;33(4):744–52.

80. Larner AJ and Lecky BR. Acute aphasia in MS revisited. Int MS J. 2007 Sep;14(3):76–7.

81. Sta N, Lucchinetti C, and Keegan B. Multiple sclerosis with predominant, severe cognitive impairment. Arch Neurol. 2009 Sep;66(9):1139–43.

82. Gorno-Tempini ML, Hillis AE, et al. Classi cation of primary progres- sive aphasia and its variants. Neurology. 2011 Mar 15;76(11):1006–14.

83. Darley F, Aronson A, and Brown J. Di erential Diagnostic Patterns of
Dysarthria. J Speech Hear Res. 1969;12(2):246–69 and 462–96.

84. Du y J. Motor Speech Disorders. St. Louis, MO: Mosby, 1995.

85. Warlow C, Dennis M, and van Gijn J. Stroke: A Practical Guide to
Management, 2nd edn. Oxford: Blackwell Scienti c, 2000.

86. Darley F, Aronson A, and Brown J. Motor Speech Disorders.
Philadelphia, PA: W.B. Saunders, 1975.

87. Yorkston K, Beukelman D, and Bell K. Clinical Management of
Dysarthric Speakers. San Diego, CA: College-Hill Press, 1988.

88. de Swart BJ, van Engelen BG, van de Kerkhof JP, et al Myotonia and
accid dysarthria in patients with adult onset myotonic dystrophy.
J Neurol Neurosur Ps. 2004 Oct;75(10):1480–2.

89. de Swart B, van Engelen B, and Maassen B. Warming up improves
speech production in patients with adult onset myotonic dystrophy.
J Commun Disord. 2007 May–Jun;40(3):185–95.

90. Lechtenberg R and Gilman S. Speech disorders in cerebellar disease.
Ann Neurol. 1978 Apr;3(4):285–90.

91. Ackermann H and Ziegler W. Articulatory de cits in Parkinsonian
dysarthria: An acoustic analysis. J Neurol Neurosur Ps. 1991

92. Auzou P, Ozsancak C, Jan M, et al. Evaluation of motor speech func-
tion in the diagnosis of various forms of dysarthria. Rev Neurol (Paris).
2000 Jan;156(1):47–52.

93. Darley F, Brown J, and Goldstein N. Dysarthria in multiple sclerosis.
J Speech Hear Res. 1972 Jun;15(2):229–45.

94. Fisher M. Lacunar strokes and infarcts: A review. Neurology.

95. Hartman DE and Abbs JH. Dysarthrias of movement disorders. Adv

96. Melo T, Bocousslavsky J, Melle G, et al. Pure motor stroke: A reap-
praisal. Neurology. 1992 Apr;42(4) 789–95.

97. Ropper A. Severe dysarthria with right hemisphere stroke. Neurology.
1987 Jun;37(6):1061–3.

98. Ozaki I, Baba M, Narita S, et al. Pure dysarthria due to anterior
internal capsule and/or corona radiata infarction: a report of ve cases.
J Neurol Neurosur Ps. 1986 Dec;49(12):1435–7.

99. Urban P, Wicht S, Hopf H, et al Isolated dysarthria due to extracer-
ebellar lacunar stroke: a central monoparesis of the tongue. J Neurol
Neurosur Ps. 1999 Apr;66(4):495–501.

100. Square-Storer P, Roy E, and Hogg S. e dissociation of aphasia from
apraxia of speech, ideomotor limb and buccofacial apraxia. In: GR Hammond (ed.). Cerebral Control of Speech and Limb Movements. Advances in Psychology. Amsterdam: North-Holland, 1990, pp. 451–76.

101. Square P, Roy A, and Martin R. Apraxia of speech: Another form of praxis disruption. In: LJG Rothi and KM Heilman (eds). Apraxia: e Neuropsychology of Action. East Sussex: Psychology Press, 1997,
pp. 173–206.

102. McNeil M, Pratt S, and Fossett T. e di erential diagnosis of apraxia of speech. In: B Maassen. Speech Motor Control in Normal and Disordered Speech. New York, NY: Oxford University Press, 2004.

103. Wertz R, LaPointe L, and Rosenbek J. Apraxia of Speech: e Disorder and its Management. New York, NY: Grune & Stratton, 1984.

104. Hillis A, Work M, Barker P, et al. Re-examining the brain regions crucial for orchestrating speech articulation. Brain. 2004 Jul;127(Pt 7):1479–87.

105. Dronkers N. A new brain region for coordinating speech articulation. Nature. 1996 Nov 14;384(6605):159–61.

106. Square P, Martin R, Bose A. Nature and treatment of neuromotor speech disorders in aphasia. In: R Chapey. Language Intervention Strategies in Aphasia and Related Neurogenic Communication Disorders, 4th edn. Philadelphia, PA: Lippincott, Williams & Wilkins, 2001.

107. Peach R and Tonkovich J. Phonemic characteristics of apraxia of speech resulting from subcortical hemorrhage. J Commun Disord. 2004 Jan-Feb;37(1) 77–90.

108. Holland AL, Fromm DS, DeRuyter F, et al. Treatment e cacy: aphasia. J Speech Hear Res. 1996;Oct;39(5):S27–36.

109. Pashek GV and Holland AL. Evolution of aphasia in the rst year post- onset. Cortex. 1988;Sep;24(3):411–23.

110. Kertesz A and McCabe P. Recovery patterns and prognosis in aphasia. Brain. 1977 Mar;100(1):1–18.

111. Pedersen PM, Vinter K, and Olsen TS. Aphasia a er stroke: type, severity and prognosis. e Copenhagen aphasia study. Cerebrovasc Dis. 2004;17(1):35–43.

112. Plowman E, Hentz B, and Ellis C. Post-stroke aphasia prognosis: a review of patient-related and stroke-related factors. J Eval Clin Pract. 2012;Jun 18(3):689–94.

113. Lazar RM and Antoniello D. Variability in recovery from aphasia. Curr Neurol Neurosci Rep. 2008 Nov;8(6):497–502.

114. Price CJ, Seghier ML, and Le AP. Predicting language outcome and recovery a er stroke: the PLORAS system. Nat Rev Neurol. 2010 Apr;6(4):202–10.

115. Saur D, Ronneberger O, Kümmerer D, et al. Early functional magnetic resonance imaging activations predict language outcome a er stroke. Brain. 2010 Apr;133(Pt 4):1252–64.

116. Lazar RM, Minzer B, Antoniello D, et al. Improvement in aphasia scores a er stroke is well predicted by initial severity. Stroke. 2010 Jul;41(7):1485–8.

117. Bhogal SK, Teasell R, and Speechley M. Intensity of aphasia therapy, impact on recovery. Stroke. 2003 Apr;34(4):987–93.

118. Marsh EB and Hillis AE. Recovery from aphasia following brain injury: the role of reorganization. Prog Brain Res. 2006;157:143–56.

119. Sarasso S, Santhanam P, Määtta S, et al. Non- uent aphasia and neural reorganization a er speech therapy: insights from human sleep elec- trophysiology and functional magnetic resonance imaging. Arch Ital Biol. 2010 Sep;148(3):271–78.

120. Monti A, Cogiamanian F, Marceglia S, et al. Improved naming a er transcranial direct current stimulation in aphasia. J Neurol Neurosur Ps. 2008 Apr;79(4) 451–53.

121. Baker JM, Rorden C, and Fridriksson J. Using transcranial direct- current stimulation to treat stroke participants with aphasia. Stroke. 2010 Jun;41:1229–36.

122. Kang EK, Kim YK, Sohn HM, et al. Improved picture naming in aphasia patients treated with cathodal tDCS to inhibit the right Broca’s homologue area. Restorative Neurol Neurosci. 2011;29 (3):141–52.

123. Fridriksson J, Richardson JD, Baker JM, et al. Transcranial direct current stimulation improves naming reaction time in uent aphasia: A double-blind, sham-controlled study. Stroke. 2011 Mar;42:819–21.

124. Martin PI, Naeser MA, eoret H, et al. Transcranial magnetic stimu- lation as a complementary treatment for aphasia. Semin Speech Lang. 2004; 25:181–91.

125. Naeser M, Martin PI, Nicholas M, et al. Improved naming a er TMS treatments in a chronic, global aphasia patient case report. Neurocase. 2005 Jun;11(3):182–93.

126. Walker-Batson D, Curtis S, Natarajan R, et al. A double-blind, placebo-controlled study of the use of amphetamine in the treatment of aphasia. Stroke. 2001 Sep;32(9):2093–8.

127. Klein RB and Albert ML. Can drug therapies improve language func- tions of individuals with aphasia? A review of the evidence. Semin Speech Lang. 2004 May;25(2):193–204.

128. Robertson S. e e cacy of oro-facial and articulation exercises in dysarthria following stroke. Int J Lang Commun Disord. 2001;36 Suppl:292–7.

129. Ray J. Orofacial myofunctional therapy in dysarthria: a study on speech intelligibility. Int J Orofacial Myology. 2002 Nov;28:39–48.

130. Freed DB. Motor Speech Disorders. San Diego, CA: Singular ompson Learning, 2000.

131. Yorkston KM, Beukelman D, Strand EA, et al. Management of Motor Speech Disorders in Children and Adults. 2nd edn. Austin, TX: Pro-Ed, 1999.

132. Tudor C and Selley WG. A palatal training appliance and a visual aid for use in the treatment of hypernasal speech. A preliminary report. Br J Disord Commun. 1974 Oct;9(2):117–22.

CHAPTER 12 acquired disorders of language and speech 133


Memory disorders

Lara Harris, Kate Humphreys,
Ellen M. Migo, and Michael D. Kopelman

eories of memory

Shortly a er learning, we are temporarily able to access informa- tion over a period of seconds. A er this, we can either recall this information in order to complete a task (short-term memory, STM), or the information may become consolidated into a longer- lasting memory (long-term memory, LTM). Memory takes vari- ous forms which can be de ned separately, and di erent forms of memory are associated with di erent patterns of brain damage. Distinguishing types of memory is therefore important to develop theories of memory and also to understand the kinds of problems that di erent patients are likely to have.

LTM may be divided (Fig. 13.1) into explicit, declarative mem- ory, which involves conscious recollection of facts and events, and implicit, non-declarative memory, where information is encoded without conscious memory of the learning event. Within explicit memory, there are episodic and semantic memory components. Episodic memory refers to memory for autobiographical events, o en associated with contextual information (e.g. time and place), whereas semantic memory is de ned as memory for factual infor- mation (e.g. meanings of words), which can be recalled without contextual information.

Episodic memories can be assessed through tests of recall and recognition. A recall memory test requires recollection of a target item or items perceived earlier. A recognition memory test involves identi cation of whether or not a given stimulus (or item) has been perceived before, either in a Yes/No format (‘Yes–No recognition’) or by selecting the item from one or more alternatives (‘forced- choice recognition’). Both episodic and semantic memory have retrograde (memory for past events) and anterograde (memory for new events) components.

In contrast to explicit memory, implicit memory is where prior events support performance without conscious awareness of learn- ing. Examples include priming, where subconscious awareness of previous information a ects performance on future trials, and pro- cedural memory, which supports acquisition of skills.

Traditionally, the role of the hippocampus was thought to be con- ned to LTM processes, grounded by early reports of dissociations between preserved STM and chronically impaired LTM in patients with hippocampal damage (e.g. patient HM).9 However, more recent ndings suggest the hippocampi are also involved in STM processes). In this section, we outline the main ndings from neu- ropsychology, cognitive psychology, and neuroscience in the study of di erent types of memory, with particular reference to the role of the hippocampus.

Short-term and working memory

Within cognitive neuropsychology, STM is de ned as the tempo- rary storage of information over a period of around 20–30 seconds. e term ‘working memory’ refers to the storage and manipula- tion of information in order to complete a complex task.10 e con- cept of working memory assumes that a limited capacity system temporarily maintains and stores information, and provides an interface between perception, LTM and action. Models of short- term memory can be divided into multi-store and unitary theories. Multi-component theories view STM and LTM as separate systems with distinct representations, whereas unitary models suggest that both STM and LTM use the same representations, di ering only in terms of the level of activation of these representations and some of the processes that act upon them.10

e Baddeley and Hitch8 model (Fig. 13.2), which has been the most highly in uential account of working memory, comprises three functionally independent bu ers: the phonological loop (responsible for information that can be rehearsed verbally), a visuospatial sketchpad (to maintain visual information), and an episodic bu er (for binding information from the other systems). Within this model, auditory information enters the phonological store directly and is then transferred to an output bu er, where the information may be either recalled or recycled through rehearsal. Remembering a list of words is easier when they form a meaningful sentence (e.g. ‘chunking’).15 Within the Baddeley and Hitch model, this is because information from LTM supports the integration of words into sentences through the episodic bu er. According to their model, a supervisory system (or central executive) controls, coordinates, and regulates these systems, and is responsible for task shi ing, retrieval strategies, selective attention, and inhibition.

ere is support for neurologically and functionally distinct pro- cesses in STM and LTM. Patients with medial temporal lobe (MTL) damage present with preserved STM but impaired LTM,12–16 while some patients, for example with parietal damage, show a pro le of preserved STM despite disorders in LTM (e.g. patient KF).15

Support for the Baddeley and Hitch model8 comes from neuropsy- chological double-dissociations in memory-impaired patients who show that visual and verbal STM can be independently impaired, following right and le hemisphere damage respectively.16 Further support has come from dual-task experiments with healthy par- ticipants, where concurrent verbal tasks interfere with verbal STM and visual tasks with visual STM17 (see section on classi cation of disorders of memory, this chapter, for a discussion of patients showing damage to component subsystems in STM). Evidence


cognitive dysfunction

Explicit/Declarative memory

Implicit/Non-declarative memory

memory Priming

Long Term Memory


Semantic memory

Anterograde Retrograde

Distinction between recall and recognition

Episodic memory


from neuroimaging strongly suggests that verbal and visual STM processes may be neurologically distinct. Verbal STM is thought to be subserved by the le inferior frontal and parietal cortex, whereas spatial STM is made possible by the right posterior dor- sal frontal and right parietal cortices and object/visual STM by the le inferior frontal and le parietal/le inferior temporal cortices.18–22

Perhaps the most in uential unitary model of STM was described by Atkinson and Shi rin.21 Essentially, they proposed that STM consists of activated long-term representations, an idea that has been recently further developed.22–27 Within their model, informa- tion is rst submitted to sensory memory and is then transferred to a short-term store where information is fed into and out of long- term memory. Given this, STM consists of temporary activations of representations that may be associated with long-term memories, or information that was recently perceived. Crucially, representa- tions that are more strongly activated (modulated by recency and frequency of occurrence) are more accessible. Oberauer26 has sug- gested that four pieces (chunks) of information are available for access, but only one chunk of information can be the focus of atten- tion at any one time.

Although the neural substrates of STM and LTM were tradi- tionally assumed to be separate, there is some evidence that STM and LTM may share some neural processes. Patients with damage

to the MTL frequently perform well on standard STM tasks, but some amnesic patients have also shown impairment where STM tasks require the representation of novel materials,28–32 and novel associations among stimuli, and between stimuli and context.31,32 is nding has received strong support from neuroimaging.33,34 e data suggest that MTL, and the hippocampus in particular, are employed in the encoding and retrieval of associative information during STM as well as in LTM. ese ndings challenge the simple STM/LTM dissociation that has been reported in classical lesion studies.

Long-term memory

Explicit/declarative memory

Explicit memory can be subdivided into episodic memory, de ned as memory for a person’s life events, and semantic memory, the memory for facts, concepts, and word meaning.35 Crucially, epi- sodic memory is described as relational, involving the representa- tion of various associations between time, space, and the self, which is consistent with ndings of hippocampal involvement in the short term, during associative memory tasks. Broadly, declarative mem- ory is subserved by MTL structures: the hippocampal region (the dentate gyrus, the subicular complex, and the hippocampus itself; see chapter 4), midline diencephalic structures,36 entorhinal cor- tex, perirhinal cortex, and parahippocampal cortex,37–41 and the thalami, mammillary bodies, the mammillo-thalamic tract, retros- plenium, and the fornix. ere may also be dorsolateral prefrontal cortex involvement.42

e hippocampus appears to have a speci c role in the binding of information in memory. In a detailed case study of a patient with selective damage to the hippocampus (YR), Mayes and colleagues reported that associative memory for items of the same type (e.g. words) were preserved, while associative memory for di erent types of information (i.e. pictures and professions, faces and voices) was clearly impaired.43 e authors suggest that di erent types of information processed in the neocortical regions is committed to the hippocampus for binding.44,45 Further evidence supporting a specialized role of the hippocampus in associative memory has been found elsewhere (e.g. references 46, 47, see 48 for a review). It should be noted, though, that specialization of the hippocampus for relational memory has not always been found.49–51

Anterograde Retrograde

Fig. 13.1 An overview of long term memory (LTM).
Adapted from Neurobiology of Learning and Memory. 82(3), Squire LR, Memory systems of the brain: A brief history and current perspective, pp. 171–7, Copyright (2004), with permission from Elsevier.


Visuospatial Sketchpad

Visual Semantics

Central Executive

Episodic Buffer

Episodic Long Term Memory

Phonological Loop



Fig. 13.2 e revised model of working memory, incorporating links with long- term memory (LTM) by way of both the subsystems and the episodic bu er. Adapted from Trends in Cognitive Sciences. 4(11), Baddeley A, e episodic bu er: a new component of working memory? pp. 417–23, Copyright (2000), with permission from Elsevier.

Retrograde amnesia

Traditionally, it has been believed that in retrograde amnesia (RA), there is relative sparing of early memories, as is postulated by Ribot.52 e two leading theories of remote declarative memory are consolidation theories53–55 and multiple trace theory (MTT).56–58 Consolidation theory suggests that encoded experiences are ini- tially stored in the hippocampus and cortical regions (perirhinal cortex, parahippocampal cortex), and with repeated learning, this information is transferred to the neocortex for permanent storage (consolidated). MTT suggests instead that experiences form mem- ory traces and older memories are associated with a greater number of memory traces acquired over time.

e perspectives di er in terms of the neural mechanisms assumed to subserve semantic memory and episodic memory; in particular, the e ects of hippocampal or MTL damage on remote memory (retrograde amnesia). Consolidation theories state that hippocampal or MTL damage leads to an impairment in retrieval of remote episodic (event-based) and remote semantic (knowledge or fact-based) information, both with a temporal gradient (i.e. relative sparing of early memories compared to more recent ones). MTT, on the other hand, states that hippocampal or MTL damage leads to an extensive loss of remote episodic memories across all time periods, while remote semantic memories are spared.

Both theories agree that damage extending beyond the MTLs will a ect remote episodic and semantic memories, but the MTT states that damage to the MTLs is su cient to cause an extensive remote episodic memory loss (examples of cases showing disorders in LTM are described in section on classi cation of disorders of memory, this chapter). However, there is still considerable contro- versy over these issues.59,04

Topographical memory

Topographical memory involves relating information about land- marks and space from semantic and episodic memory for the purposes of navigation. In topographical amnesia, buildings and landmarks can frequently be recognized and recalled, but the mem- ory for associations between them and how they relate to space is defective.61–64

Neuroimaging and neuropsychological evidence suggests that while the parahippocampus is implicated in relating visual and spatial information into a topographical representation, the hip- pocampus is involved in their consolidation. In an important study, Maguire and colleagues65 took structural magnetic reso- nance imaging (MRI) scans of the brains of professional London taxi drivers, who undertake two to three years of training to learn the various spatial relations between destinations in the city. e authors reported that the taxi drivers had signi cantly larger pos- terior hippocampi, relative to a control group, concluding that the posterior hippocampus stores a map of spatial representations to enable navigation.

Topographical memory appears to be underpinned by a network including the medial parietal lobe, the posterior cingulate gyrus, occipitotemporal areas, the parahippocampal gyrus, and the right hippocampus.65 is is consistent with neuropsychological reports of hippocampal patients who show impaired topographical memory in the context of better preserved memory for visual information.66 On functional imaging, there is hippocampal activation during studies of navigation in virtual environments in PET64,65 and activa- tion of the right hippocampus during route- nding on fMRI.67,68

ere is some suggestion that the role of the hippocampus in relating spatial representations may not be con ned to LTM pro- cesses, as hippocampal damage impedes the memory for topo- graphical information even over short delays.69

Implicit/non-declarative memory

While explicit memory processes are mediated by the MTL and diencephalic regions, the implicit (non-declarative) memory sys- tem is traditionally understood to be independent of the MTL, though the neural regions implicated in tests of implicit mem- ory vary widely with the type of stimuli presented. Dissociations between implicit and explicit memory performance in amnesic patients6 are consistent with theories positing separate neural sys- tems for explicit and implicit memory.

More recent work has suggested that there may be some overlap between the neural mechanisms involved in implicit and explicit memory, which may indicate a unitary system. In particular, there is some evidence that MTL may be implicated in implicit memory where retrieval is of relational information rather than individual items. ere is accumulating evidence from neuroim- aging studies showing MTL activation during associative memory tasks (for reviews, see references 70, 71). Hippocampal activity during implicit relational memory encoding has been demon- strated in healthy participants,47 and implicit relational memory e ects were absent in hippocampal patients tested under the same conditions.46

Procedural memory

Procedural memory refers to the acquisition and retention of perceptuomotor skills. ese memories are accessed and applied without the need for recalling information relating to the event where the skill was acquired. Procedural memory is less well understood than explicit memory, but it is likely to involve a net- work comprising frontal, basal ganglia, parietal, and cerebellar regions.36,70,73 Unlike explicit memory, learning in the procedural memory system is gradual, and the automaticity with which pro- cedural memory is applied is only achieved a er repeated expo- sure and practice.

Skill acquisition has been tested experimentally using mirror- reading and pursuit rotor tasks. Mirror-reading tasks involve read- ing mirror-transformed words, and pursuit rotor tasks involve following a moving dot around a circle with a wand. Performance on these tasks should improve with practice. One study74 com- pared the performance of patients with Huntington’s disease with Korsoko ’s syndrome patients and controls on mirror-reading and pursuit rotor tasks. Both Korsako ’s and control participants showed the expected pattern (increased speed of mirror-reversed words with increased exposure), whereas the performance of the Huntington’s group was stable over incremental trials. Such lack of improvement with practice would be compatible with a special role of brain regions particularly a ected in Huntington’s in implicit memory (e.g. the basal ganglia).

Classi cation of disorders of memory

ere are various types of memory disorders, each associated with di erent clinical characteristics and neuropsychological dissocia- tions. In this section, we describe the most common memory disor- ders using vignettes of important neuropsychology cases from the literature.

CHAPTER 13 memory disorders 137

138 SECTION 2 cognitive dysfunction Short-term memory

Much of the data on STM comes from memory span tasks, where lists of words, pictures, or numbers are presented and the partici- pant is required to recall them in the order they were presented. Memory span is determined by the longest list of items reliably recalled in the correct order and is considerably reduced in patients with short-term memory disorders, relative to control norms.

Several STM-impaired patients have been described. Patients with phonological STM de cits are characterized by a marked impairment for verbally presented STM despite preserved visual STM. ese patients are una ected by phonological similarity or word length of the to-be-recalled items—e ects commonly observed under STM conditions.20,75–77 e rst phonological STM patient to be described was patient KF15,77 who, despite hav- ing a normal ability to articulate words and comprehend language, could recall sequences of only two auditorily presented items.15,77 Strikingly though, KF performed within the normal range under conditions of visual presentation.

e authors attributed these results to avoidance of employing a defective phonological loop during STM tasks.4,78 A similar patient (see Box 13.1) with a pure de cit for phonological information showed the same pattern of impaired auditory span, but with nor- mal language comprehension with sentences comprised of simple structures (patient PV).4 ese dissociations strongly suggested selective impairment of an auditory short-term system, putatively localized in the le parietal or superior temporal regions15,79 in a model with functionally separate short-term stores. Some other studies have also reported de cits of spatial span following lesions of the right parietal region.80,81

As will be discussed below, MTL patients with impaired long-


Anterograde amnesia is characterized by the failure to create new memories or acquire new information following the onset of a dis- ease or brain injury. In contrast, retrograde amnesia refers to the loss of memories which occurred before the onset of a disease or head trauma. A highly in uential case of anterograde amnesia fol- lowing bilateral MTL lesions is patient H.M. (Box 13.2).

e association between anterograde amnesia and the MTL described in these original observations was subsequently repli- cated in several studies of amnesic patients with MTL damage (e.g. patient SS82 and patient RB83; see also Box 13.3), and in experimen- tal animals with tailored lesions to the MTL.84 is work has sought to investigate the speci c structures within the MTL involved in anterograde and retrograde amnesia.

Anterograde amnesia has been associated with bilateral loss of the pyramidal cells in the CA1 hippocampal area,83 and damage to the anterior thalamus.85–88 In herpes simplex encephalitis, the severity of anterograde amnesia is strongly modulated by the extent of pathology in the medial limbic regions, with bilateral damage typically predictive of very severe amnesia.89–91

In contrast, some studies have found that retrograde amne- sia is associated with damage to the right temporal and frontal areas.41,92–94 In a detailed case study, Levine and colleagues attrib- uted retrograde amnesia in a traumatic brain injury patient to a focal right frontal lesion, and right frontotemporal disconnection.95 ough some authors have described cases of disproportionate, ‘isolated’, or ‘focal’ retrograde amnesia,87,96,97 many of these cases have in fact shown evidence of coexisting impairments in antero- grade memory98–102 (see reference 101 for a review).

Box 13.2 Vignette: Patient HM

Patient HM1,2 underwent a bilateral medial temporal lobe resec- tion in 1953 at the age of 27, which included the hippocampus and most of the amygdaloid complex and entorhinal cortex, in order to control frequent and debilitating epileptic seizures. Surgery was partially successful in modifying his epilepsy but resulted in severe anterograde amnesia.

He failed to acquire new event-related, autobiographical memories (i.e. episodic memory, e.g. appointments, people he had just met) and memories for facts (i.e. semantic memory). HM famously reported that ‘every day is alone in itself’.1 In contrast, wider cognition, including perceptual abilities, short- term memory, procedural memory, and language skills were well-preserved.

e case of HM strongly in uenced memory research, empha- sizing the role of the medial temporal lobe structures in explicit, declarative memory, and demonstrating that the neural mecha- nisms responsible for memory can be dissociated from struc- tures involved in other aspects of cognition.

term memory and preserved STM have also been described. ese ndings indicate that STM processes are broadly independ- ent of MTL structures. Moreover, there is some evidence that while phonological (verbal) STM stores might be localized to posterior le hemisphere regions, visusospatial STM stores are in posterior right hemisphere areas.

Anterograde and retrograde amnesia

Box 13.1 Vignette: Patient PV

Patient PV7 was a right-handed woman with 11 years of edu- cation, who su ered a large, le hemisphere CVA at the age of 23. Acutely, she had a right hemiparesis which cleared within a month, and some signs of aphasia, including phonemic parapha- sias and word- nding di culties, and sentence repetition was particularly impaired, though wider cognition was preserved.

Two years a er her stroke, most of her language problems had resolved, though striking de cits in sentence repetition (for sentences containing more than eight syllables) and in compre- hending complex language (e.g. using the Token test and Raven’s progressive matrices) persisted. ese di culties were observed in the context of good repetition and comprehension of single words and short sentences suggesting that PV’s problems were mnemonic in nature.

Her auditory span was severely restricted (to lists of two or three items) but she performed within the normal range with visual presentation. Her sentence repetition impairment was restricted to sentences of two to three words. Sentence com- prehension was better and she experienced problems only with long, complex sentences. e absence of detrimental e ects of phonological similarity and increased word length indicates sub- components in STM, and suggests that a defective phonological loop11 is the locus of PV’s impairments in span, sentence repeti- tion, and comprehension.

e partial dissociation of anterograde and retrograde amne- sia has received support from studies of Korsoko ’s syndrome patients, where the extent of retrograde amnesia is not well cor- related with the severity of anterograde amnesia.102–105

Selective de cits in episodic memory?

Patients with impaired episodic memory show particular di cul- ties in remembering events with a speci c spatial or temporal con- text in both anterograde and autobiographical memory. ere are reports of patients who show dissociations between episodic and semantic memory (Box 13.4).

In a study of retrograde amnesia, Bright and colleagues106 com- pared episodic and semantic memory performance in medial tem- poral, medial plus lateral temporal, and frontal lesion patients. MTL lesions were associated with impaired retrieval of recent epi- sodic memories whereas patients with medial plus lateral temporal damage showed impaired recall of both recent and remote episodic memories (i.e. a at temporal gradient).

Episodic memory disorder occurs in herpes simplex (HSV) encephalitis107 and a similar pattern—though o en to a lesser

extent—has been reported in limbic encephalitis.108 In terms of neuroimaging ndings, HSV encephalitis causes hyper-intense signal alteration on T2-weighted MRI scans and loss of volume in the MTL which is consistent with an association between episodic memory and the MTL.89,109,110

Selective de cits in semantic memory?

In the early stages, semantic dementia (SD) patients show frequent word- nding di culties, and may demonstrate impaired reading of low-frequency, irregularly spelled words (surface dyslexia). In the later stages of the disease, speech becomes increasingly empty of meaning, though it remains uent and grammatically sound (Box 13.5). Many semantic dementia patients have atrophy of the temporal pole, with relative preservation of MTL structures (see reference 111 for a review).

Under neuropsychological examination, these patients show impairments on tests of semantic knowledge (e.g. pyramids and palm trees).112 Crucially, and as is consistent with preserved MTL regions on imaging, episodic memory in these patients is o en rela- tively spared,113–115 In a study comparing the memory performance of an MTL amnesic patient with a patient with semantic demen- tia, Westmacott and colleagues116 showed that, unlike the amnesic patient, the semantic dementia patient EL had preserved episodic memory, at least on cueing, and a similar nding was made in patient IH (Box 13.5) by Moss and colleagues.3 Further, EL’s memory for semantic facts was signi cantly modulated by autobiographical sig- ni cance, whereas this was not true of the amnesic patient KC, indi- cating that episodic memory may contribute to semantic memory in cases of SD. ere is also evidence from a longitudinal study sug- gesting intact autobiographical memory in semantic dementia until the very late stages of the illness (patient AM).117

Semantic memory is also commonly a ected in both Alzheimer’s disease118 and HSV encephalitis,7,119 manifesting in surface dys- lexia and di culties on wider lexical semantic memory tasks. is impairment has been attributed to le inferolateral temporal lobe or temporal pole damage.120

CHAPTER 13 memory disorders 139

Box 13.3 Vignette: Patient DJ

Patient DJ10 su ered unilateral le temporal lobe damage due to herpes encephalitis in 1990, when he was aged 36. Initially, DJ was unable to remember events and could not read, speak, or comprehend spoken language. Recall of earlier memories was better preserved.

One year post-onset, his language abilities improved (though surface dyslexia persisted). Strikingly, he was still very unable to acquire new memories, though memory for remote news and autobiographical events was only moderately impaired. He made frequent confabulation errors when required to recall auditorily presented stories, both in immediate and delayed (20–30 min- utes) recall conditions (logical memory, WMS–R).

Consistent with his le temporal lobe pathology, DJ’s recogni- tion memory was poor, though his memory for faces was bet- ter preserved than for words (using the Recognition Memory Test). Seven years post-onset, DJ was still severely amnesic and anomic, and showed on testing a pattern of poor verbal memory and preserved visual memory (WMS–R), though memory for recent episodic and semantic memory was much improved and he was able to name highly familiar items.

Box 13.5 Vignette: Patient IH

Patient IH6 was diagnosed with semantic dementia aged 62. An MRI scan revealed marked atrophy of the le temporal lobe but crucially with better preservation of the le hippocampus and MTL, and minor atrophy in the right temporal lobe and neocortex.

He showed di culties in word- nding, reading, naming, and language comprehension, despite good non-verbal reasoning, visual spatial processing, and day-to-day memory and orienta- tion. is pattern of neuropsychological performance is charac- teristic of semantic dementia, though he was sometimes able to spontaneously recall events from his late teens.

IH showed a reversed temporal gradient (relative preserva- tion of recent memories) in autobiographical memory using the Autobiographical Memory Interview, but not when recall- ing news events (semantic memory). However, IH’s memory for early, remote events could be signi cantly improved with detailed cueing. e neuropsychological pro le of IH suggests that lexical–semantic disturbances were the basis of his impaired retrieval from autobiographical memory, rather than de ciencies in autobiographical memory storage.

Box 13.4 Vignette—Patient KC

Patient KC3–5 is an amnesic patient with complete destruction of the le hippocampus, parahippocampal gyrus, entorhinal and perirhinal cortex following a road tra c accident.

He subsequently developed anterograde amnesia and a tem- porally graded retrograde amnesia for episodic information: he could not acquire new semantic or autobiographical memories, and could only reliably recall old semantic (fact-based) memo- ries from his life prior to the accident. Notably, he could remem- ber detailed factual information from his education but could not recall emotional details, such as those relating to his brother’s death. KC was also unable to imagine himself in the future (auto- noetic consciousness).


cognitive dysfunction

Box 13.6 Vignette: Patient Jon

Jon8 is a developmental case of early onset amnesia. He was delivered prematurely and su ered two long-lasting convulsions at the age of four. Jon began to show evidence of memory prob- lems a year-and-a-half later.

At the age of 19, Jon was assessed by Vargha-Khadem and col- leagues.8 On imaging, Jon showed abnormally small hippocampi bilaterally. Impressively, at this time he had an IQ of 120, could read successfully, and showed relatively preserved memory for factual information (semantic memory), even for information learned a er his hippocampal damage. However, Jon was unable to nd his way around familiar routes, was not well oriented in time, and could not acquire information about daily events (epi- sodic memories).

Consistently, during assessment, he showed a striking impair- ment on the Rivermead Behavioural Memory Test, which includes tasks such as remembering a route, an appointment, and a message to be relayed. Despite his preserved ability to perceive and recognize objects, Jon’s topographical memory was mark- edly impaired, as was his context-dependent episodic memory.

Box 13.7 Vignette: Patient LH

Patient LH9 was aged 18 when he was involved in a road tra c accident. He su ered a traumatic brain injury and underwent an extensive right temporal lobectomy and insertion of a shunt for hydrocephalus. MRI and SPECT conducted when he was aged 41 revealed damage to the right parietal and occipital lobes and a le hemisphere white matter lesion (extending from the inferior temporal gyrus to just below the occipital horn), but the dience- phalic regions medial temporal lobe structures were spared.

LH’s main complaint was an inability to recognize faces. He also showed other impairments in visuoperceptual skills. He showed an absent priming e ect in perceptual identi cation of words and pseudowords and absent word completion priming in the context of normal (explicit) recognition memory.

Topographical memory

Turriziani and colleagues66 reported a patient with signi cant bilat- eral hippocampal atrophy and moderate cortical atrophy follow- ing cerebral hypoxia. Crucially, there was a chronic impairment in memory for spatial information that was signi cantly improved with visual cues, but a relatively well-preserved ability to learn ver- bal and visual information (including topographical information), which was only mildly impaired. e authors concluded that there was a (largely) preserved ability to form topographical represen- tations (modulated by the preserved parahippocampus), but an impaired ability to consolidate them into LTM (owing to bilateral hippocampal damage). A developmental syndrome has also been described (Box 13.6).

e association between hippocampal damage and topographi- cal memory has been observed even at very short delays. In a neu- ropsychological study of four focal hippocampal patients, Hartley and colleagues69 found that two patients were impaired in both topographical perception and memory, but that two showed a selective impairment for topographical memory (i.e. despite pre- served ability to perceive and process topographical representa- tions), even at very brief (two-second) delays. is nding suggests the speci c role of the hippocampus in topographical memory con- solidation, and during specialized STM tasks tapping visualspatial information.

Implicit memory

A double dissociation between explicit and implicit memory in two neuropsychological cases, LH and HM, has been reported.6 While HM was profoundly amnesic with severely impaired explicit mem- ory and preserved performance on implicit memory tasks (percep- tual identi cation, word completion, priming), LH demonstrated the reverse dissociation (Box 13.7).

Keane and colleagues6 explained the di erence in these patients’ implicit memory performance in terms of occipital circuits that were intact in HM and damaged in LH. Ostergaard has contested the idea that there is complete preservation of implicit memory

in medial temporal amnesics, suggesting that implicit memory is o en not preserved when studies are properly controlled with respect to baseline.121

Procedural memory is usually preserved in amnesia,82,121–124 but can be impaired in Parkinson’s and Huntington’s disease.74,125

Recall and recognition memory

In both episodic and semantic memory, there are distinctions between recall and recognition tests. ese tests ask participants to remember studied items in di erent ways. Recall tests are con- sidered to be more di cult than recognition tests, requiring more e ort, and patients o en perform rather worse on them than in recognition tests. Performance on recall and recognition tests is usually interpreted in terms of the contributions of recollection and familiarity.126,127 Recollection is where participants retrieve information beyond the represented stimulus, such as the context in which it was presented. Familiarity is simply the feeling that a stimulus has been encountered before.

Patients with apparently similar lesions of the hippocampi can show very di erent memory performance patterns.128 A meta- analysis by Aggleton and Shaw129 looked for associations between recognition performance and pathology in amnesic patients. ey found that patients with more focal brain damage, particularly to the hippocampus, mamilliary bodies, and fornix, were more likely to show preserved recognition, despite profound impairments on recall tests. However, their meta-analysis was confounded by oor e ects in some of their patients, and not all studies show dispropor- tionate impairment on recall memory in hippocampal patients.49 e reasons behind this inconsistency are not yet resolved.

Disproportionate recall over recognition de cits have also been reported in ageing130 and a number of disorders, such as schizo- phrenia131 and autism.132 Damage to frontal brain regions has been shown to impair free recall performance more than cued recall, which in turn is more impaired than recognition, though recogni- tion is commonly also a ected in these patients.133

Testing memory

A wealth of standardized neuropsychological assessments of mem- ory is available to the clinician to assist diagnosis. Some of the most well-known include the Wechsler Memory Scale,134 the California Verbal Learning Test II,135 and the Rey Complex Figure.136 Most of these concentrate on episodic memory. However, specialist

tests also exist for autobiographical memory (e.g. autobiographi- cal memory interview),137 prospective memory (e.g. Cambridge Prospective Memory Test),138 and semantic memory (e.g. pyramids and palm trees).112 Comprehensive critical reviews can be found in standard texts.139,140 e reader is also referred to chapter 11. In this section, we outline practical considerations when testing for di erent types of memory disorder.

Diagnostic assessments

It is important to rst establish the clinical history from both the patient and an informant relating to a memory complaint such as the time and nature of its onset and other related disease or psychiatric complaint, and then to assess whether there is objective evidence of a memory disorder on formal testing; that is, whether performance falls by at least 1.5 to 2 standard deviations based on estimated pre- morbid IQ (see chapter 11). Standardized tests of memory that give scores that can be compared directly against optimal IQ (i.e. that give age-scaled standardized scores) should be employed. Memory for both visual and verbal material should be tested as these can be impaired relatively independently,141 and it is necessary to test free recall, ideally a er a delay as well as immediately.

Recognition memory or cued recall should be assessed if perfor- mance on free recall is poor, as it may be that the information is being encoded but cannot be retrieved without a cue. Suitable test batter- ies for evaluating episodic memory include the Wechsler Memory Scale,134 the doors and people test,140 and the BIRT (Brain Injury Rehabilitation Trust) Memory and Information Processing Battery (BMIPB),143 and the Recognition Memory Test 2007.144 Performance on the Wechsler Adult Intelligence Scale145 digit span subtest can be used as a measure of phonological STM and working memory either alone, or in combination with the arithmetic subtest with which it comprises the Wechsler Working Memory Index. Visuospatial STM and working memory can be evaluated using the symbol span subtest from the WMS–IV or the Corsi Block Tapping Test.146

If objective evidence of memory impairment is found, a second question is whether the pattern of impairment is more consistent with neurological or psychogenic causes (e.g. depression). In gen- eral, patients who are simply depressed will tend to make a large number of ‘don’t know’ responses, to be reluctant to guess, and to show a pattern of generally poor performance. For these reasons, it is sometimes helpful to administer symptom validity tests such as the test of memory malingering,147 the word memory test,148 and the Camden Pictorial Memory Test.149 Poor or below-chance per- formance on these tasks is strongly indicative of motivational fac- tors rather than neurological disorder.

If the ndings are more indicative of a neurological complaint, the question is whether the pattern of memory test scores has any lateralizing or localizing value or is consistent with a particular di erential diagnosis. In general, di culties remembering verbal material are associated with le hemisphere pathology while there is a less strong association between visual memory di culties and pathology in the right hemisphere.150

Another important consideration in a diagnostic assessment is whether the memory di culties are progressive or static in nature. is is particularly important in distinguishing between a cogni- tive impairment a er a stable lesion and a dementia. Obviously this point can only be addressed by serial assessments. Memory batter- ies with parallel forms that increase slightly in di culty, to counter- act practice e ects, are available (e.g. the BMIPB).143

CHAPTER 13 memory disorders 141 Planning and monitoring rehabilitation

Results from memory assessments can inform memory rehabilita- tion programmes, which can be tailored to maximize the use of the individual’s strengths and compensate for their areas of weakness. Findings from traditional standardized memory tests can be useful; for example, knowing that an individual scores at the 75th percen- tile on tests of verbal memory and only at the 5th percentile on tests of visual memory means that teaching verbal encoding strategies for visual material is likely to be of bene t. Furthermore, many cli- nicians nd it more helpful to use so-called ecologically valid tests of memory to inform rehabilitation. ese tests are designed to map on to real-life abilities in a much more direct way and aim to provide a measure of disability rather than impairment. Commonly used ecologically valid memory tests include the Rivermead Behavioural Memory Test151 and the Cambridge Prospective Memory Test.138

Interpreting memory test scores in context

It is usually relatively meaningless to obtain memory test scores in isolation. First, poor performance on memory tests may be sec- ondary to di culties with other cognitive and perceptual domains such as processing speed, executive functions, language or visual cognition152 rather than due to a primary ‘memory de cit’. us, we would recommend at least screening these areas if di culties are found on memory tests. Another reason to test more widely than just memory is that patients o en report ‘memory problems’ when they mean that they experience word- nding di culties or other cognitive problems.139 ird, performance on memory tests must be considered relative to the individual’s likely optimum level of functioning (see chapter 11); performance in the average range may constitute a strength for someone with an intellectual disabil- ity but a relative weakness for someone previously likely to have functioned in the superior range.

As well as the quantitative scores provided by memory tests, it is necessary to gather qualitative information regarding how the individual approached the task and the types of errors they made in order to aid interpretation of the results. For example, confabula- tion, intrusions, or perseverative responses, or an inability to initi- ate responses without frequent prompting and encouragement, can indicate fronto-executive dysfunction.

In addition to cognitive tests, it is desirable to administer a mood screen such as the Hospital Anxiety and Depression Scale153 or the Beck Depression Inventory II154 since depression and anxiety can a ect performance on memory tests.155 It is also good prac- tice to administer a questionnaire asking about subjective memory di culties, such as the Prospective and Retrospective Memory Questionnaire.156


Memory can be divided into various subtypes, and, while there are well-established ndings (e.g. MTL involvement in episodic mem- ory), there is still considerable controversy in some areas of the literature regarding the functional description and neural organi- zation of memory processes. ere is accumulating evidence attest- ing to the importance of hippocampi in representing novel items and associations both in the long- and (to some extent) the short- term, and in memory consolidation. Detailed neuropsychological case descriptions have contributed signi cantly to the evolution of

142 SECTION 2 cognitive dysfunction

memory theories. Standardized neuropsychological assessments are available that allow targeted evaluation of di erent types of memory (e.g. episodic and semantic), memory for di erent modal- ities of information (e.g. verbal and visual), and the underlying neurobiological process (e.g. static or progressive). However, when assessing memory-impaired patients, it is important to interpret evidence in the context of premorbid IQ and any wider cognitive or psychological disorders that may be causing impaired perfor- mance. Understanding memory disorders is of crucial importance for the clinician for making diagnoses and for planning rehabili- tation. Moreover, neuropsychological descriptions of memory- impaired patients remain critically important for informing and evaluating memory theory.


1. Milner B, Corkin S, and Teuber HL. Further analysis of the hip- pocampal amnesic syndrome: 14-year follow-up study of H.M. Neuropsychologia. 1968;6(3):215–34.

2. Scoville WB and Milner B. Loss of recent memory a er bilateral hippocampal lesions. 1957. J Neuropsych Clin N. 1957;12(1):103–13.

3. Moss HE, Kopelman MD, Cappelletti M, et al. Lost for words or loss of memories? Autobiographical memory in semantic dementia. Cognitive Neuropsych. 2003;20(8):703–32.

4. Vallar G and Baddeley AD. Fractionation of working
memory: Neuropsychological evidence for a phonological short- term store. Journal of Verbal Learning and Verbal Behavior. 1984;23(2):151–61.

5. Vargha-Khadem F, Gadian DG, Watkins KE,et al. Di erential E ects of Early Hippocampal Pathology on Episodic and Semantic Memory. Science. 1997;277(5324):376–80.

6. Keane MM, Gabrieli JDE, Mapstone HC, et al. Double dissociation of memory capacities a er bilateral occipital-lobe or medial temporal-lobe lesions. Brain. 1995;118(5):1129–48.

7. Stanhope N and Kopelman MD. Art and memory: A 7-year follow-up of herpes encephalitis in a professional artist. Neurocase. 2000;6(2):99–110.

8. Baddeley A and Hitch GJ. Working memory. In: GA Bower (ed.). Recent Advances in Learning and Motivation. New York, NY: Academic Press, 1974, pp. 47–90.

9. Squire LR. e Legacy of Patient H.M. for Neuroscience. Neuron. 2009;61(1):6–9.

10. Baddeley A. Working memory: Looking back and looking forward. Nat Rev Neurosci. 2003;4(10):829–39.

11. Baddeley A. e episodic bu er: A new component of working memory? Trends Cogn Sci. 2000;4(11):417–23.

12. Squire LR. Memory and the hippocampus: A synthesis from ndings with rats, monkeys, and humans. Psychol Rev. 1992;99(2):195–231.

13. Scoville WB and Milner B. Loss of recent memory a er bilateral hip- pocampal lesions. J Neurol Neurosur Ps. 1957;20:11–21.

14. Baddeley AD and Warrington EK. Amnesia and the distinction between long- and short-term memory. Journal of Verbal Learning and Verbal Behavior. 1970;9(2):176–89.

15. Shallice T and Warrington EK. e dissociation between short term retention of meaningful sounds and verbal material. Neuropsychologia. 1974;12(4):553–5.

16. Wang PP and Bellugi U. Evidence from two genetic syndromes for a dissociation between verbal and visual-spatial short-term memory. J Clin Exp Neuropsyc. 1994;16(2):317–22.

17. Baddeley AD. Working Memory. Oxford: Oxford University Press, 1986.

18. Awh E, Jonides J, Smith EE, et al. Dissociation of Storage and Rehearsal
in Verbal Working Memory: Evidence from Positron Emission
Tomography. Psychol Sci. 1996;7(1):25–31.

19. Jonides J, Smith EE, Koeppe RA, et al. Spatial working memory in

20. Warrington EK, Logue V, and Pratt RTC. e anatomical localisa- tion of selective impairment of auditory verbal short-term memory. Neuropsychologia. 1971;9(4):377–87.

21. Atkinson RC and Shi rin RM. Human Memory: A Proposed System and its Control Processes. In: WS Kenneth and JS Taylor (eds). Psychology of Learning and Motivation. New York, NY: Academic Press, 1968, pp. 89–195.

22. Anderson JR, Bothell D, Byrne MD, et al. An Integrated eory of the Mind. Psychological Review. 2004;111(4):1036–60.

23. Cowan N. Attention and Memory: An Integrated Framework. Oxford: Oxford University Press, 1995.

24. Cowan N. e magical number 4 in short-term memory: A reconsid- eration of mental storage capacity. Behav Brain Sci. 2001;24(1):87–114; discussion 85.

25. McElree B. Working memory and focal attention. J Exp Psychol Learn. 2001;27(3):817–35.

26. Oberauer K. Access to information in working memory: Exploring the focus of attention. J Exp Psychol Learn. 2002;28(3):411–21.
27. Verhaeghen P, Cerella J, and Basak C. A Working Memory

Workout: How to Expand the Focus of Serial Attention From One to Four Items in 10 Hours or Less. J Exp Psychol Learn Mem Cogn. 2004; 6:1322–37. doi:10.1037/0278-7393.30.6.1322.

28. Bu alo EA, Reber PJ, and Squire LR. e human perirhinal cortex and recognition memory. Hippocampus. 1998;8(4):330–9.

29. Holdstock JS, Shaw C, and Aggleton JP. e performance of amnesic subjects on tests of delayed matching-to-sample and delayed matching- to-position. Neuropsychologia. 1995;33(12):1583–96.

30. Olson I, Page K, Moore KS, et al. Working memory for con- junctions relies on the medial temporal lobe. J Neurosci. 2006;26(17):4596–601.

31. Hannula DE, Tranel D, and Cohen NJ. e long and the short of It: Relational memory impairments in amnesia, even at short lags. J Neurosci. 2006;26(32):8352–9.

32. Olson IR, Page K, Moore KS, et al. Working memory for conjunctions relies on the medial temporal lobe. J Neurosci. 2006;26(17):4596–601.

33. Miyashita Y and Chang HS. Neuronal correlate of pictorial short-term memory in the primate temporal cortex. Nature. 1988;331(6151):68–70.

34. Ranganath C and D’Esposito M. Medial temporal lobe activity associated with active maintenance of novel information. Neuron. 2001;31(5):865–73.

35. Tulving E. Episodic and semantic memory. In: E Tulving, W Donaldson (eds). Organization of Memory. New York, NY: Academic Press, 1972, pp. 381–402.

36. Squire LR and Zola SM. Structure and function of declara- tive and nondeclarative memory systems. Proc Natl Acad Sci USA.1996;93(24):13515–22.

37. Squire LR. Memory systems of the brain: A brief history and current perspective. Neurobiol Learn Mem. 2004;82(3):171–7.

38. Squire LR and Knowlton BJ. e Medial Temporal Lobe, the Hippocampus, and the Memory Systems of the Brain. In: MS Gazzaniga (ed.). Memory. Cambridge, MA: MIT Press, 2000, pp. 825–37.

39. Suzuki WA and Eichenbaum H. e neurophysiology of memory. Annals of the New York Academy of Sciences. 2000;911(1):175–91.

40. Kopelman MD, Stanhope N, and Kingsley D. Temporal and spatial context memory in patients with focal frontal, temporal lobe, and diencephalic lesions. Neuropsychologia. 1997;35(12):1533–45.

41. Kopelman MD, Stanhope N, and Kingsley D. Retrograde amne- sia in patients with diencephalic,temporal lobe or frontal lesions. Neuropsychologia. 1999;37(8):939–58.

42. Prabhakaran V, Narayanan K, Zhao Z, et al. Integration of diverse information in working memory within the frontal lobe. Nat Neurosci. 2000;3(1):85–90.

43. Mayes AR, Holdstock JS, Isaac CL, et al. Associative recognition in a patient with selective hippocampal lesions and relatively normal item recognition. Hippocampus. 2004;14(6):763–84.

44. Mayes AR, Montaldi D, and Migo EM. Associative memory and the medial temporal lobes. Trends Cogn Sci. 2007;11(3):126–35.

humans as revealed by PET. Nature. 1993;363(6430):623–5.

45. Montaldi D and Mayes AR. e role of recollection and familiar- ity in the functional di erentiation of the medial temporal lobes. Hippocampus. 2010;20(11):1291–314.

46. Hannula DE, Ryan JD, Tranel D, et al. Rapid Onset Relational Memory E ects Are Evident in Eye Movement Behavior, but Not in Hippocampal Amnesia. J Cognitive Neurosci. 2007;19(10):1690–705.

47. Hannula DE and Ranganath C. e Eyes Have It: Hippocampal Activity Predicts Expression of Memory in Eye Movements. Neuron. 2009;63(5):592–9.

48. Eichenbaum H. Hippocampus: Cognitive Processes and Neural Representations that Underlie Declarative Memory. Neuron. 2004;44(1):109–20.

49. Kopelman MD, Bright P, Buckman J, et al. Recall and recognition memory in amnesia: Patients with hippocampal, medial temporal, tem- poral lobe or frontal pathology. Neuropsychologia. 2007;45(6):1232–46.

50. Stark CE and Squire LR. Hippocampal damage equally impairs memory for single items and memory for conjunctions. Hippocampus. 2003;13(2):281–92.

51. Stark CEL, Bayley PJ, and Squire LR. Recognition memory for single items and for associations is similarly impaired following damage to the hippocampal region. Learn Memory. 2002;9(5):238.

52. Ribot TA. e Diseases of Memory. New York, NY: Appleton & Co., 1882.

53. Alvarez P and Squire LR. Memory Consolidation and the Medial
Temporal Lobe: A Simple Network Model. Proc Natl Acad Sci USA.

54. Squire LR. Lost forever or temporarily misplaced? e long
debate about the nature of memory impairment. Learn Memory.

55. Squire LR, Stark CE, and Clark RE. e medial temporal lobe. Annu
Rev Neurosci. 2004;27:279–306.

56. Moscovitch M, Nadel L, Winocur G, et al. e cognitive neuroscience
of remote episodic, semantic and spatial memory. Curr Opin Neurobiol.

57. Nadel L and Moscovitch M. Memory consolidation, retrograde amnesia
and the hippocampal complex. Curr Opin Neurobiol. 1997;7(2):217–27.

58. Winocur G and Moscovitch M. Memory Transformation and Systems Consolidation. Journal of the International Neuropsychological Society.

59. Kopelman MD and Bright P. On remembering and forgetting our
autobiographical pasts: Retrograde amnesia and Andrew Mayes’s contribution to neuropsychological method. Neuropsychologia. 2012;50(13):2961–72.

60. Kopelman MD and Stanhope N. Anterograde and retrograde amnesia following frontal lobe, temporal lobe, or diencephalic lesions In: LR Squire and D Schacter (eds). Neuropsychology of Memory, 3rd edn. New York, NY: Guilford Press, 2002, pp. 47–60.

61. Bottini G, Cappa S, Geminiani G, et al. Topographic disorientation—A case report. Neuropsychologia. 1990;28(3):309–12.

62. De Renzi E, Faglioni P, and Villa P. Topographical amnesia. J Neurol Neurosur Ps. 1977;40(5):498–505.

63. Habib M and Sirigu A. Pure Topographical Disorientation: A De nition and Anatomical Basis. Cortex. 1987;23(1):73–85.

64. Maguire EA, Burke T, Phillips J, et al. Topographical disorientation following unilateral temporal lobe lesions in humans. Neuropsychologia. 1996;34(10):993–1001.

65. Maguire EA, Frackowiak RSJ, and Frith CD. Recalling Routes around London: Activation of the Right Hippocampus in Taxi Drivers.
J Neurosci.1997;17(18):7103–10.

66. Turriziani P, Carlesimo GA, Perri R, et al. Loss of spatial learning in a patient with topographical disorientation in new environments.
J Neurol Neurosur Ps. . 2003;74(1):61–9.

67. Gron G, Wunderlich AP, Spitzer M, et al. Brain activation during human navigation: Gender-di erent neural networks as substrate of performance. Nat Neurosci. 2000;3(4):404–8.

68. Hartley T, Maguire EA, Spiers HJ, et al. e Well-Worn Route and the Path Less Traveled: Distinct Neural Bases of Route Following and Way nding in Humans. Neuron. 2003;37(5):877–88.

69. Hartley T, Bird CM, Chan D, et al. e hippocampus is required for short-term topographical memory in humans. Hippocampus. 2007;17(1):34–48.

70. Cohen NJ, Ryan J, Hunt C, et al. Hippocampal system and declarative (relational) memory: Summarizing the data from functional neuroim- aging studies. Hippocampus. 1999;9(1):83–98.

71. Davachi L. Item, context and relational episodic encoding in humans. Curr Opin Neurobiol. 2006;16(6):693–700.

72. Rizzolatti G, Fogassi L, and Gallese V. Cortical mechanisms sub- serving object grasping and action recognition: A new view on the cortical motor functions. In: MS Gazzaniga (ed.). e New Cognitive Neurosciences. Cambridge, MA: MIT Press, 2000, pp. 539–52.

73. Schacter D and Tulving E. Memory Systems. Cambridge, MA: MIT Press, 1994.

74. Martone M, Butters N, Payne M, et al. DIssociations between skill learning and verbal recognition in amnesia and dementia. Arch Neurol– Chicago. 1984;41(9):965–70.

75. Basso A, Spinnler H, Vallar G, et al. Le hemisphere damage and selec- tive impairment of auditory verbal short-term memory. A case study. Neuropsychologia. 1982;20(3):263–74.

76. Sa ran EM and Marin OSM. Immediate memory for word lists and sentences in a patient with de cient auditory short-term memory. Brain Lang. 1975;2(0):420–33.

77. Warrington EK and Shallice T. e Selective Impairment Of Auditory Verbal Short-Term Memory. Brain. 1969;92(4):885–96.

78. Vallar G and Shallice T. Neuropsychological Impairments of Short-Term Memory. Cambridge: Cambridge University Press, 1990.

79. Vallar G and Papagno C. Neuropsychological impairments of verbal short-term memory. In: A Baddeley, MD Kopelman, and BA Wilson (eds). Handbook of Memory Disorders, 2nd edn. Chichester: Wiley, 2002, pp. 249–70.

80. De Renzi E. Disorders of Space Explanation and Cognition. Chichester: John Wiley, 1982.

81. Hanley RJ, Pearson NA, and Young AW. Impaired Memory For New Visual Forms. Brain. 1990;113(4):1131–48.

82. Cermak LS and O’Connor M. e anterograde and retrograde retrieval ability of a patient with amnesia due to encephalitis. Neuropsychologia. 1983;21(3):213–34.

83. Zola-Morgan S, Squire LR, and Amaral DG. Human amnesia and the medial temporal region: Enduring memory impairment fol- lowing a bilateral lesion limited to eld CA1 of the hippocampus. JNeurosci.1986;6(10):2950–67.

84. Winocur G, McDonald RM, and Moscovitch M. Anterograde and ret- rograde amnesia in rats with large hippocampal lesions. Hippocampus. 2001;11(1):18–26.

85. Gra -Radford NR, Tranel D, et al. Diencephalic Amnesia. Brain. 1990;113(1):1–25.

86. Guinan EM, Lowy C, Stanhope N, et al. Cognitive e ects of pituitary tumours and their treatments: Two case studies and an investigation of 90 patients. J Neurol Neurosur Ps. 1998;65(6):870–6.

87. Kapur N, Scholey K, Moore E, et al. Long-Term Retention De cits in Two Cases of Disproportionate Retrograde Amnesia. J Cognitive Neurosci. 1996;8(5):416–34.

88. Parkin AJ and Hunkin NM. Impaired Temporal Context Memory on Anterograde But Not Retrograde Tests in the Absence of Frontal Pathology. Cortex. 1993;29(2):267–80.

89. Colchester A, Kingsley D, Lasserson D, et al. Structural MRI volu- metric analysis in patients with organic amnesia, 1: Methods and comparative ndings across diagnostic groups. J Neurol Neurosur Ps. 2001;71(1):13–22.

90. Kapur N, Barker S, Burrows EH, et al. Herpes simplex encephali- tis: Long term magnetic resonance imaging and neuropsychological pro le. J Neurol Neurosur Ps. 1994;57(11):1334–42.

91. Kopelman MD, Lasserson D, Kingsley D, et al. Structural MRI volumetric analysis in patients with organic amnesia, 2: Correlations with anterograde memory and executive tests in 40 patients. J Neurol Neurosur Ps. 2001;71(1):23–8.

CHAPTER 13 memory disorders 143

144 SECTION 2 cognitive dysfunction

92. Fink GR, Markowitsch HJ, Reinkemeier M, et al. Cerebral
Representation of One’s Own Past: Neural Networks Involved in
Autobiographical Memory. J Neurosci. 1996;16(13):4275–82.

93. Kopelman MD, Lasserson D, Kingsley DR, et al. Retrograde amne-
sia and the volume of critical brain structures. Hippocampus.

94. Verfaellie M, Kose P, and Alexander MP. Acquisition of novel
semantic information in amnesia: E ects of lesion location.
Neuropsychologia. 2000;38(4):484–92.

95. Levine B, Black SE, Cabeza R, et al. Episodic memory and the self in a
case of isolated retrograde amnesia. Brain. 1998;121(10):1951–73.

96. Hodges JR and McCarthy RA. Loss of remote memory: A cog-
nitive neuropsychological perspective. Curr Opin Neurobiol.

97. Kapur N. Focal Retrograde Amnesia in Neurological
Disease: A Critical Review. Cortex. 1993;29(2):217–34.

98. Brown JW and Chobor KL. Severe retrograde amnesia. Aphasiology.

99. Markowitsch HJ, Calabrese P, Haupts M, et al. Searching for the
anatomical basis of retrograde amnesia. J Clin Exp Neuropsyc.

100. O’Connor M, Butters N, Miliotis P, et al. e dissociation of antero-
grade and retrograde amnesia in a patient with herpes encephalitis.
J Clin Exp Neuropsyc. 1992;14(2):159–78.

101. Kopelman, MD. Focal Retrograde Amnesia and the Attribution of
Causality: An Exceptionally Critical Review. Abingdon: Taylor &
Francis, 2000.

102. Kopelman MD. Remote and autobiographical memory, temporal con-
text memory and frontal atrophy in Korsako and Alzheimer patients.
Neuropsychologia. 1989;27(4):437–60.

103. Mayes AR, Downes JJ, McDonald C, et al. Two tests for assessing
remote public knowledge: A tool for assessing retrograde amnesia.

104. Parkin AJ. Recent advances in the neuropsychology of memory.
In: J Weinman and J Hunter (eds). Memory: Neurochemical and
Abnormal Perspectives. London: Harwood Academic, 1991, pp. 141–62.

105. Shimamura AP. Priming e ects in amnesia: Evidence for a dissociable
memory function. Q J Exp Psychol–A. 1986;38(4-A):619–44.

106. Bright P, Buckman J, Fradera A, et al. Retrograde amnesia in patients
with hippocampal, medial temporal, temporal lobe, or frontal pathol-
ogy. Learn Memory. 2006;13(5):545–57.

107. Reed LJ, Lasserson D, Marsden P, et al. Correlations of regional
cerebral metabolism with memory performance and executive function in patients with herpes encephalitis or frontal lobe lesions. Neuropsychology. 2005;19(5):555–65.

108. Vincent A, Buckley C, Schott JM, et al. Potassium channel antibody‐ associated encephalopathy: A potentially immunotherapy‐responsive form of limbic encephalitis. Brain. 2004;127(3):701–12.

109. Holmes EJ, Butters N, Jacobson S, et al. An examination of the e ects of mammillary-body lesions on reversal learning sets in monkeys. Physiol Psychol. 1983;11(3):159–65.

110. Murray EA, Davidson M, Ga an D, et al. E ects of fornix transection and cingulate cortical ablation on spatial memory in rhesus monkeys. Exp Brain Res. 1989;74(1):173–86.

111. Hodges JR and Patterson K. Semantic dementia: A unique clinico- pathological syndrome. Lancet Neurol. 2007;6(11):1004–14.

112. Howard D and Patterson K. e Pyramids and Palm Trees Test. Bury St. Edmunds: ames Valley Test Company, 1992.

113. Hodges Jr, Patterson K, Oxbury S, et al. Semantic
Dementia: Progressive Fluent Aphasia with Temporal Lobe Atrophy. Brain. 1992;115(6):1783–806.

114. Murre JMJ, Graham KS, and Hodges JR. Semantic demen-
tia: Relevance to connectionist models of long-term memory. Brain. 2001;124(4):647–75.

115. Snowden JS, Goulding PJ, and Neary D. Semantic dementia: A form of circumscribed cerebral atrophy. Behav Neurol. 1989;2(3):167–82.

116. Westmacott R, Leach L, Freedman M, et al. Di erent Patterns of
Autobiographical Memory Loss in Semantic Dementia and Medial

Temporal Lobe Amnesia: A Challenge to Consolidation eory.

Neurocase. 2001;7(1):37–55.
117. Maguire EA, Kumaran D, Hassabis D, et al. Autobiographical memory

in semantic dementia: A longitudinal fMRI study. Neuropsychologia.

118. Hodges JR, Salmon DP, and Butters N. Semantic memory impair-

ment in Alzheimer’s disease: Failure of access or degraded knowledge?

Neuropsychologia. 1992;30(4):301–14.
119. Hokkanen L, Salonen O, and Launes J. AMnesia in acute herpetic and

nonherpetic encephalitis. Arch Neurol–Chicago. 1996;53(10):972–8. 120. Binney RJ, Embleton KV, Je eries E, et al. e Ventral and Inferolateral

Aspects of the Anterior Temporal Lobe Are Crucial in Semantic Memory: Evidence from a Novel Direct Comparison of Distortion- Corrected fMRI, rTMS, and Semantic Dementia. Cerebral Cortex. 2010;20(11):2728–38.

121. Ostergaard AL. Priming de cits in amnesia: Now you see them, now you don’t. Journal of the International Neuropsychological Society. 1999;5:175–90.

122. Corkin S, Amaral DG, Gonzalez RG, et al. H.M.’s medial tem- poral lobe lesion: Findings from magnetic resonance imaging. J Neurosci.1997;17(10):3964–79.

123. Moscovitch M. Multiple dissociations of function in amnesia. In: LS Cermak (ed.). Human Memory and Amnesia. Hillsdale, NJ: Lawrence Erlbaum, 1982, pp. 337–70.

124. Wilson BA and Wearing D. Prisoner of consciousness: A state of just awakening following herpes simplex encephalitis. In: R Campbell and MA Conway (eds). Broken Memories. Oxford: Blackwell, 1985, pp. 14–30.

125. Reber PJ and Squire LR. Intact learning of arti cial grammars and intact category learning by patients with Parkinson’s disease. Behav Neurosci. 1999;113(2):235–42.

126. Migo EM, Mayes AR, and Montaldi D. Measuring recollection and familiarity: Improving the remember/know procedure. Conscious Cogn. 2012;21(3):1435–55.

127. Yonelinas AP. e Nature of Recollection and Familiarity: A Review of 30 Years of Research. J Mem Lang. 2002;46(3):441–517.

128. Holdstock JS, Parslow DM, Morris RG, et al. Two case studies illustrat- ing how relatively selective hippocampal lesions in humans can have quite di erent e ects on memory. Hippocampus. 2008;18(7):679–91.

129. Aggleton JP and Shaw C. Amnesia and recognition memory: A re-analysis of psychometric data. Neuropsychologia. 1996;34(1):51–62.

130. Craik FIM and McDowd JM. Age Di erences in Recall and Recognition. J Exp Psychol Learn. 1987;13(3):474–9.

131. Aleman A, Hijman R, de Haan EH, et al. Memory impair- ment in schizophrenia: A meta-analysis. Am J Psychiat. 1999;156(9):1358–66.

132. Bennetto L, Pennington BF, and Rogers SJ. Intact and Impaired Memory Functions in Autism. Child Development. 1996;67(4):1816–35.

133. Wheeler MA, Stuss DT, and Tulving E. Frontal lobe damage pro- duces episodic memory impairment. Journal of the International Neuropsychological Society. 1995;1(06):525–36.

134. Wechsler, D. (2009). Wechsler Memory Scale—Fourth Edition (WMS–IV) technical and interpretive manual. San Antonio, TX: Pearson, 2009.

135. Delis DC, Kramer JH, Kaplan E, et al. e California Verbal Learning Test II. San Antonio, TX: Psychological Corporation, 2000.

136. Oserrieth PA. e test of copying a complex gure: A contribution to the study of perception and memory. Archives de Psychologie. 1944;30:286–356.

137. Kopelman MD, Wilson B, and Baddeley A. Autobiographical Memory Interview. Oxford: Pearson Assessments, 1990.

138. Shiel A, Wilson BA, Emslie H, et al. Prospective Memory Test. Cambridge: Pearson, 2005.

139. Lezak MD, Howieson DB, Bigler ED, et al. Neuropsychological Assessment, 5th edn. Oxford: Oxford University Press, 2012.

140. Strauss E, Sherman EMS, and Spreen O. A Compendium of Neuropsychological Tests. Oxord: Oxford University Press, 2006.

141. Saling MM. Verbal memory in mesial temporal lobe epilepsy: Beyond material speci city. Brain. 2009;132(3):570–82.

142. Baddeley AD, Emslie H, and Nimmo-Smith I. Doors and People. London: Pearson Assessment, 2006.

143. Oddy M, Coughlan A, and Crawford J. BIRT Memory & Information Processing Battery. Horsham: Brain Injury Research Trust, 2007.

144. Warrington E. Recognition Memory Test Manual. Windsor: Nfer-Nelson, 1984.

145. Wechsler D. Wechsler Adult Intelligence Scale, 4th edn. San Antonio, TX: Pearson, 2008.

146. Corsi PM. Human Memory and the Medial Temporal Region of the Brain. PhD thesis, McGill University, 1972.

147. Tombaugh TN. Test of Memory Malingering. Toronto: Multi-Health Systems, 1996.

148. Green P. Green’s Word Memory Test for Microso Windows: User’s Manual. Edmonton, Canada: Green’s Publishing Inc., 2003.

149. Warrington EK. Camden Pictorial Recognition Memory Test. Windsor: Infernelson, 1996.

150. McConley R, Martin R, Palmer CA, et al. Rey Osterrieth complex gure test spatial and gural scoring: Relations to seizure focus and

hippocampal pathology in patients with temporal lobe epilepsy.

Epilepsy & Behavior. 2008;13(1):174–7.
151. Wilson BA, Green eld E, Clare L, et al. Rivermead Behavioural

Memory Test. London: Pearson, 2008.
152. Davidson PSR, Troyer AK, and Moscovitch M. Frontal lobe con-

tributions to recognition and recall: Linking basic research with clinical evaluation and remediation. Journal of the International Neuropsychological Society. 2006;12(02):210–23.

153. Zigmond AS and Snaith RP. e Hospital Anxiety and Depression Scale. Acta Psychiat Scand. 1983;67(6):361–70.

154. Beck AT, Steer RA, Ball R, et al. Comparison of Beck Depression Inventories-IA and-II in Psychiatric Outpatients. J Pers Assess. 1996;67(3):588–97.

155. Kizilbash AH, Vanderploeg RD, and Curtiss G. e e ects of depres- sion and anxiety on memory performance. Arch Clin Neuropsych. 2002;17(1):57–67.

156. Smith G, Del Sala S, Logie RH, et al. Prospective and retrospect- ive memory in normal ageing and dementia: A questionnaire study. Memory. 2000;8(5):311–21.

CHAPTER 13 memory disorders 145



Vision and visual processing de cits
Anna Katharina Schaadt and Georg Kerkho


e following short recommendations may be helpful, primarily for patients with non-progressive disorders (cf reference 2):

Bilateral postchiasmatic lesion: Use magni cation so ware (for PCs) or screen-reading machines for permanent enlargement of printed text, pictures, and letters.

Visual exploration de cit: Improve visual search by providing the patient with a systematic (horizontally or vertically) saccadic search strategy. Acuity will improve when visual search is more systematic, quicker, and when omissions are reduced.

Nystagmus: Reduce nystagmus with orthoptic (prisms) or pharma- cological means.12

Spasmodic xation (Bálint–Holmes syndrome): Test acuity with sin- gle letter charts, as acuity for single letters should be normal as long as the patient can xate the single target. Furthermore, improving simultaneous perception by repetitive treatment enlarges the use- ful eld of view13 and improves visual activities of daily living.

Dynamic visual acuity: Treat smooth pursuit eye movements in the horizontal domain (le , right) for di erent velocities. e rec- ognition of moving objects is important for vocational tasks14 and mobility in the environment. It improves in parallel with the increase of the smooth pursuit gain (relation of target velocity to eye–movement velocity).

Spatial contrast sensitivity (CS)


Spatial CS denotes the ability to discriminate between striped pat- terns (gratings) of di ering luminance (contrast) and stripe width (spatial frequency). It is o en impaired in acute vascular posterior brain lesions (80 per cent).15 In the majority of patients, recovery is rapid, although permanent de cits persist in about 20 per cent. An example for the assessment of CS is illustrated in Fig. 14.1b. CS also diminishes in AD.16,17


CS can be trained e ectively in normal subjects but this has rarely been tried in brain-damaged patients. In those 20 per cent with permanent de cits, the use of additional, indirect lighting is help- ful because it improves contrast. Light- ltering lenses may increase contrast sensitivity.18

Visual disorders are frequent function losses a er brain damage and occur in about 20–50 per cent of the patients with cerebrovascular disorders1 and some 50 per cent of patients with traumatic brain injury (TBI).2 In stroke patients > 65 years the incidence rises to 40– 60 per cent.3 In Alzheimer’s disease (AD), visual impairments (low- level and high-level) occur in some 40 per cent of patients.4 ey are core features of posterior cortical atrophy (PCA). Consequently, routine screening of the various types of visual de cits is necessary both for diagnosis and rehabilitation planning. Patients with intact awareness can easily be questioned with a simple questionnaire (see Table 14.1), responses to which prove clinically useful in 95 per cent of cases.5,6

Visual acuity impairments

Visual acuity refers to the spatial resolution of the visual process- ing system7 and is usually tested using high-contrast acuity plates (Fig. 14.1a). It is important to appreciate that impairments of visual acuity and spatial contrast sensitivity (see below) will o en lead to di culties for patients in performing higher-level neuropsycho- logical tests, thus it is essential to test basic visual function before interpreting de cits on cognitive visual tests.8

Concerning de cits of visual acuity, primary and secondary causes have to be distinguished in patients with brain damage before initiating treatment.

Primary causes

Bilateral postchiasmatic lesions9 which may cause partial up to total loss of visual acuity in both eyes which cannot be corrected by lenses. is is o en associated with bilateral homonymous visual eld defects.10

Secondary causes

Disturbed visual exploration, xation di culties due to Bálint– Holmes syndrome, impaired contrast sensitivity, eccentric xation due to cerebral hypoxia, or nystagmus. Impairments in acuity for moving targets (dynamic acuity) are caused by de cient smooth pursuit eye movements,11 due to cerebellar or parietal lesions.

Recovery is frequent in patients with secondary, but rare in those with primary causes of disturbed visual acuity. As impaired acu- ity a ects all subsequent visual activities as well as neuropsycho- logical testing, treatment of the secondary causes should be started immediately.

148 SECTION 2 cognitive dysfunction
Table 14.1 Schema for the anamnesis of visual disorders after acquired brain lesions. Indent the questions in the table into the following

phrase: ‘Did you experience … since your brain lesion?’


Purpose of Question, Underlying Disorder

1. any changes in vision?

◆ Awareness of de cits? Information about case history

2. diplopia?transiently/permanently?

◆ Type of gaze palsy? If transient: fusional disorder?

3. reading problems? syllables/words missing, change of line, reduced reading span?

◆ Hemianopic alexia? Di erential diagnosis of neglect dyslexia, aphasic alexia, or pure alexia

4. problems in estimating depth on a staircase? reaching with your unimpaired hand for a cup, hand, door handle?

◆ Depth perception? Optic ataxia?

5. bumping into obstacles? failure to notice persons? at which side?

◆ Visual exploration de cits in homonymous visual eld disorders?

6. blinding after exposure to bright light?

◆ Foveal photopic adaptation?

7. dark vision? that you need more light for reading?

◆ Foveal scotopic adaptation?

8. blurredvision?transiently/permanently?

◆ Contrast sensitivity? Acuity? Fusion?

9. that colours look darker, paler, less saturated?

◆ Colour hue discrimination? Impaired contrast sensitivity?

10. that faces look darker, paler, unfamiliar?

◆ Face discrimination/recognition disorders?

11. problems in recognizing objects?

◆ Object discrimination/recognition disorders?

12. problems in nding your way in familiar/unfamiliar environments?

◆ Topographic orientation de cits?

13. visual hallucinations (stars, dots, lines, fog, faces, objects) or illusions (distorted objects, faces)?

◆ Simple or complex visual hallucinations, illusions? Awareness about illusory character?

Adapted from Neurorehabilitation & Neural Repair. Neumann G, Schaadt A-K, Reinhart S, and Kerkho G, Clinical and psychometric evaluations of the Cerebral Vision Screening Questionnaire in 461 non-aphasic individuals post-stroke, Copyright (2016), with permission from SAGE Publications.

Disorders of foveal photopic or scotopic


Foveal photopic adaptation means the continuous adapting to a brighter illumination than the current one, scotopic adaptation the adaptation to a darker illumination than the present one. Both pro- cesses are dissociable and impaired in some 20 per cent of patients with posterior cerebral artery infarctions or cerebral hypoxia.19 A question- naire for the assessment of the most frequent subjective complaints


in these patients can be found at: . e case report in Box 14.1 illustrates the subjective visual impairments associated with a foveal photopic adaptation de cit. Concerning recov- ery, there is no evidence (even a er years) that such de cits recover.19


Photopic adapation

Avoid direct lighting, use a dimmer to adjust light individually; avoid ickering neon lights; use sunglasses outside buildings; avoid


Fig. 14.1 Examples for assessing visual acuity (a) and spatial contrast sensitivity (b). For assessing visual acuity, size but not spatial contrast of the symbols diminishes; for assessing spatial contrast, sensitivity size of the characters is constant whereas spatial contrast diminishes.

Box 14.1 Foveal photopic adaptation

Case study

Since his stroke (right posterior cerebral artery infarction with associated le homonymous hemianopia), this patient has been unable to stay longer than 10 minutes in bright environments without feeling highly uncomfortable and getting severe head- ache. e adaptation de cit is subjectively more disturbing to him than the visual eld loss. At work, for example, he would always darken the room he is sitting in. When colleagues come to his o ce, they would always complain about the darkness and turn on the lights. In the examiner’s o ce, the patient considered the luminance as comfortable when the room was nearly fully darkened (50 lux).

continuously adapting sunglasses (Varilux) because they are too slow in readapting inside a building. Driving at night (‘blinding’) is not advisable. If there is photophobia, light- ltering lenses can also reduce this sensation.18

Scotopic adaptation

Increase indirect lighting by additional light bulbs; use also port- able dimmer to adjust lighting individually.

Disorders of convergent fusion

and stereopsis

CHAPTER 14 vision and visual processing deficits 149 1 minute

5 minutes

10 minutes

Fig. 14.2 Schematic illustration of the development of diplopic images in patients with fusion disorders as a function of time. Black and gray traces refer to the optic image of the left/right eye. Note blurring and nally diplopia after sustained binocular vision.

Visual discomfort

Looking at homogeneous, regular patterns like lines, written text, agstones, or stripes of a certain spatial frequency (three to four cycles per degree visual angle)27 may elicit unpleasant sensations (termed ‘visual discomfort’; see Fig. 14.3a, b), blurred vision, and headaches in some healthy people, but much more so in patients with cerebral visual disorders. Visual discomfort in brain-lesioned patients may reduce sustained visual activities considerably and lead to asthenopic symptoms. ere is no evidence so far that such symptoms recover naturally.


In reading, visual discomfort can be eliminated by using a simple mask that covers all lines except the one that is currently read (see Fig. 14.3c).

Homonymous visual eld disorders

Visual eld disorders (VFDs) are present in 20–50 per cent of all neurological patients with stroke1 and may also be present in patients with PCA. Visual eld sparing is < 5° for the a ected vis- ual hemi eld in 70 per cent of stroke cases with VFDs who receive speci c neurovisual treatment in neurorehabilitation centres.7,10 In acute neurology settings, visual eld sparing on the blind side may be more variable. Fig. 14.4 demonstrates the most frequent types of VFD, although in patients with PCA such classical patterns are not usually present, or may vary, sometimes leading to the errone- ous conclusion that the patient is psychogenic. Patients may present three types of associated de cits: visual exploration de cits, reading disorders, and visuospatial de cits.

Visual exploration de cit

Time-consuming, ine cient visual search due to loss of overview and unsystematic search strategies; numerous, small-amplitude staircase-saccades in the blind hemi eld; omissions of targets in the blind eld.28–31

Stereopsis refers to the perception of spatial depth based on binocu- lar integration. Convergent fusion is a prerequisite of stereopsis and means the fusion of the le and right eye’s image into one combined (fused) picture of the world.20 Fusion and stereopsis (local, global) are reduced in patients with vascular occipital, parietal, or temporal brain lesions,21 and impair manual activities in near space (reach- ing and grasping, technical work, depth perception), which is also relevant for vocational rehabilitation. Astereopsis is also caused by TBI.22 Fusion is impaired in some 20 per cent of patients with pos- terior vascular lesions and about one-third of TBI patients.2 ose patients have severe reading problems a er some 10 minutes (see Fig. 14.2). ey rapidly develop diplopia and are impaired in all near-work activities.

e percentage of patients showing recovery is unknown in aste- reopsis. In TBI patients with fusional disorders, three-quarters have persistent impairments for years a er their injury.23


Fusion and stereopsis can be trained together using simple orth- optic or binocular devices.24–26 First, determine from the history whether there are asthenopic symptoms (sensation of eye pres- sure, fatigue in reading or with PC work), blurred vision, problems in near-work activities, and how long the patient can read before blurred vision or diplopia emerges. Improvement of fusion and stereopsis can occur with repetitive display of dichoptic images with increasing disparity angle; 8–20 sessions advisable.24–26 e out- come is favourable in 80 per cent of patients, with improvements in reading duration, stereopsis, and fusional range; relief from asthe- nopia; and better function in vocational life. However, this therapy is contra-indicated in patients with premorbid de cits in binocular integration or those with permanent diplopia of exophoria > 15°.


cognitive dysfunction

Fig. 14.3 Illustration of the visual discomfort phenomenon with stripes (a), text (b), as well as its removal with a cover template (c).
Reproduced from Habermann C and Kolster F, Ergotherapie im Arbeitsfeld Neurologie, Copyright (2008), with permission from ieme Medical Publishers.

Hemianopic reading disorder

For reading, the central visual eld (+/–5° around the fovea) is crucial because only here visual acuity and form recognition are su cient for letter recognition (‘perceptual reading window’). Slow reading with errors is evident in patients with eld sparing < 5°, as well as those with paracentral scotomas and quadrantanopia; however, reading of short, single words is normal (no aphasia or alexia).32–34 Fig. 14.5 illustrates the impairment in reading depend- ing on the type of VFD (see also chapter 18).

Visuospatial de cits

e patient’s feeling of the subjective visual straight ahead in space or his subjective midline in bisecting horizontal lines and objects is shi ed towards the blind eld (horizontally in le /right VFDs, vertically in altitudinal VFDs, oblique in quadrantic VFDs) in 90 per cent of the patients.35–38 is spatial shi is also evident in pointing29 and in daily life (walking through doorways, sitting in front of a table). Line bisection can be used for the di erential diag- nosis of hemianopia versus visual neglect (see chapter 15). While the subjective midline in homonymous hemianopia is shi ed towards the blind eld (contralesional), it is ipsilesionally displaced away from the neglected side, in patients with visual neglect (see Fig. 14.6).36,40,41 e line bisection error is not due to eccentric xa- tion42 and attentional cueing does not change it.43 A recent study identi ed lesions in Brodmann area 18 (lingual gyrus) as crucial.44 Patients with homonymous quadrantanopia show a related, oblique shi of their subjective visual straight ahead towards the scotoma (see Fig. 14.6b).37

Field recovery is present in the rst two to three months post- lesion in up to 40 per cent of the patients with a stable aetiology such as stroke.45 A er six months post-lesion, spontaneous recov- ery is extremely unlikely.45,46


Field recovery is very limited, and therefore restorative eld train- ing is appropriate only in a very small group of patients, detailed below. For the majority of VFD patients (95 per cent) compensa- tory visual eld treatment of the associated disorders in reading and visual scanning is advocated as the standard treatment for patients with VFDs (see Table 14.2). While restorative visual eld training induces only very small or no visual eld increases (~1°) and improves visual search or reading only minimally,47 hemian- opic reading training and visual exploration training induce sig- ni cant, lasting, and functionally relevant improvements in these treated domains. us, these treatments improve ‘visual’ activi- ties of daily living and increase functional independence of the patient.2,7,10,34,48 Cross-modal (visual-auditory) training has also








Fig. 14.4 Most frequent types of homonymous visual eld defects: (a) left hemianopia, (b) left superior quadrantanopia, (c) left inferior quadrantanopia, (d) left paracentral scotoma, (e) tunnel vision, (f) left hemiamblyopia (loss of colour and form vision along with relatively intact light perception).
Reproduced from Habermann C and Kolster F, Ergotherapie im Arbeitsfeld Neurologie, Copyright (2008), with permission from ieme Medical Publishers.


(b) Table 14.2 Summary of restorative (visual eld training) and compensatory approaches (hemianopic reading and visual exploration

training) in patients with postchiasmatic scotomata


0° 15°

CHAPTER 14 vision and visual processing deficits 151





Restorative visual eld training:

. (1)  Anamnesis: visual perimetry, tachistoscopic tests: identi cation of amblyopic transition zones which are most likely candidates for eld recovery

. (2)  Type of treatment: improvement of saccadic localization at eld border or in amblyopic transition zone; discourage head movements to target; recognition of colour, form, orientation, or luminance of the target; amount of treatment: 30–500 sessions (hours)

. (3)  Transfer: very small improvements in reading and subjective awareness of visual problems; minimal improvement in visual search

. (4)  Outcome and follow-up: small or no visual eld increase; partial eld recovery in exceptional patients with incomplete lesions

Hemianopic reading training:

(1) Anamnesis: problems with change of line, types of errors (omissions, substitutions, problems with long words or numbers), maximum reading duration, asthenopic disorders (eye strain)

(2) Typeoftreatment:improvementofoculomotorreadingstrategies(i.e. optokinetic reading therapy) substituting the lost parafoveal visual eld; tachistoscopic reading of single words, moving window technique, oating words, search for words in a text, scanning reading technique, reading

of numbers with embedded zeros: variation of physical and linguistic parameters: word length and frequency, position on screen (left, centre, right), number of words, presentation time, complexity of text, variation of instruction (read versus scan text), verbal working memory training

. (3)  Transfer: reading of newspaper, book, own manuscripts; text editing on a PC, increase of maximal reading duration

. (4)  Outcome and follow-up: increase in reading speed; reduction in reading errors; small eld recovery in one-third of patients; improvements in reading eye movements

Visual exploration training:

(1) Anamnesis: limited overview, bumping into persons and obstacles, defective orientation in visual space, i.e. crowded situations, tra c

(2) Typeoftreatment:increasingamplitudeofsaccadiceyemovements towards scotoma: variation of size, increase of velocity of saccade, reduction of saccadic reaction time, reduction of head movements; systematic, spatially organized visual search on wide- eld displays: organized search strategy (horizontal or vertical); start search in blind eld; visual displays requiring serial and parallel search

(3) Transfer:orientationinclinic,ownurbandistrict,newenvironments, management of visual activities of daily living: nd objects on table or in room, nd therapist ́s room, nd objects in supermarket, cross street, use public tra c, nd way home

(4) Outcome and follow-up: reduction of omissions and search time; improved eye- movements; signi cant improvements in functional visual tasks (e.g. nd objects on table); subjective improvements in patient’s functional independence in daily life

(c) (d)



Fig. 14.5 Importance of the central visual eld for reading (‘perceptual reading window’). In healthy people with Western reading habits, the reading window is larger in the right paramacular hemi eld so that right hemianopia (b) or a right paracentral scotoma (d) a ect a bigger part of the reading window. In contrast, left hemianopia only a ects a smaller part of the reading window (c), resulting in less marked reading impairment.

Reproduced from Habermann C and Kolster F, Ergotherapie im Arbeitsfeld Neurologie, Copyright (2008), with permission from ieme Medical Publishers.

been used for improvement of reading and scanning in hemiano- pia.49,50 Visual and auditory targets are presented time-locked in locations of the visual eld, and the patient has to saccade to them. is training induces similar improvements as conventional visual scanning training but requires additional technical facilities.

Left hemianopia

Left hemi-neglect (b)

Objective midline




0° 5°

5° 1




Left upper quadrantanopia Left lower quadrantanopia Right upper quadrantanopia Right lower quadrantanopia Control subjects


Fig. 14.6 Illustration of the horizontal line bisection error: (a) In left hemianopia, the subjective midpoint is shifted towards the blind hemi eld, in left hemi- neglect it is biased towards the ipsilesional hemi eld. (b) Oblique shifts of the subjective visual straight ahead direction towards the scotoma in di erent types of homonymous quarantanopia, without visual neglect.

Compensatory versus restorative visual eld training

In recent years, restorative visual eld training has been revived a er publication of advantageous results following new training proce- dures.51 However, numerous replication studies have failed to nd sig- ni cant visual eld enlargements30,52–54 or found only minimal visual eld increases as described above. In our view, restorative eld training is only promising when lesions are incomplete and a high degree of

15° 2


Adapted from Neuropsychologia. 48(11), Kuhn C, Heywood C, Kerkho G. Oblique spatial
shifts of subjective visual straight ahead orientation in quadrantic visual eld defects,
pp. 3205–10, Copyright (2010), with permission from Elsevier. residual visual capacities (light, motion, form, or colour perception) is

152 SECTION 2 cognitive dysfunction

preserved in speci c regions of the scotoma.2,48 Moreover, compensa- tory eld training leads to a much quicker reduction of visual impair- ments and needs fewer treatment sessions. Recently, home-based treatments of visual search and reading have been successfully tested in VFDs.30,55,56 ese approaches are cost-e ective, but require regular advice by the therapist (i.e. by telephone or visit).

Ine ective or disadvantageous therapies

Most hemianopic patients get confused when using prisms to sub- stitute the visual eld loss. However, small prisms tted to a spec- tacle can be useful in some cases.57 Compensatory head shi s towards the scotoma (either spontaneously adopted by the patient or to instruction) are of no use in the rehabilitation of VFDs because they lead to visual exploration de cits in the ipsilesional visual eld, strain of the neck muscles, and delay treatment progress in visual scanning training.58 Training of ‘blindsight’ (the ability of rare cases of cortical blindness which respond to stimuli in their visual eld, e.g. by pointing to them, even if they are not able to consciously per- ceive them) is probably not useful for the majority of the patients59 because it does not lead to improved functioning in daily life.

Anton’s syndrome

Unawareness of visual eld defects is not an unfrequent phenom- enon, with up to one-third of the patients showing a denial of their impairment (Anton’s syndrome).7,60,61 One the other hand, there has been the reverse condition reported in which patients with spared vision a er visual eld loss deny any visual sensation in the intact parts of their visual eld.62 Insu cient awareness is negatively associated with development and use of compensatory strategies and rehabilitation outcome.63 Consequently, detailed assessment and education of the patient are inevitable to assure compliance and the conditions for a good outcome.

Positive visual phenomena (visual


Whereas the previously described disorders refer to function losses (i.e. negative visual phenomena), visual hallucinations are positive

(a) (b)

(d) (e)

symptoms in the absence of an external stimulus.64 Simple formed visual hallucinations (light dots, bars, lines, stars, fog, coloured sensations, etc.)65 are frequently reported by patients—although only when questioned systematically—with posterior, vascular lesions, most o en a er occipital lesions. More complex visual hallucinations and illusions are rare in structural lesions and most o en associated with temporal lobe lesions; see Fig. 14.7).66,67,68 Recovery is rapid and complete in 95 per cent of the patients with stroke aetiology, so that at six weeks post-lesion the occurrence is quite rare.66,67 Positive visual phenomena have also been described in AD,69 and well-formed visual hallucinations, typically non- threatening and of silent animals or people, are core diagnostic fea- tures of dementia with Lewy bodies (DLB),128 and very common in Parkinson’s disease with dementia. Visual hallucinations are not uncommon in prion diseases, and in particular those patients presenting with visual impairment—the so-called Heidenhain variant.70


As hallucinations and illusions are irritating but—in the case of structural lesions—mostly transient phenomena, informing and reassuring the patient is important.

Complex visual scenes have a higher reality character than sim- ple hallucinations and are therefore more frightening to the patient. ese patients may be reluctant to talk about their experience for fear of being misdiagnosed as a psychogenic. Note that psychiatric patients much more o en have auditory than visual hallucinations, while the opposite holds true for patients with organic visual hal- lucinations a er posterior brain lesions. Further, brain-damaged patients very rarely report ‘hearing voices’. e complex well formed halluciantions of DLB and Parkinson’s disease with dementia may respond very well to treatment with cholinesterase inhibitors.

Persistent visual hallucinations

Check if there is an epileptic focus (EEG), the possibility of a new infarction developing, or a psychiatric disease. Lasting visual hallu- cinations that interfere with visual recognition have been reported in Parkinson’s disease.71,72



Fig. 14.7 Examples for positive visual phenomena (visual hallucinations); (a) and (b): simple visual hallucinations, (c): coloured visual hallucinations, (d), (e), (f) complex visual hallucinations.
Reproduced from Habermann C and Kolster F, Ergotherapie im Arbeitsfeld Neurologie, Copyright (2008), with permission from ieme Medical Publishers.

Colour perception de cits

Colour perception can be impaired within a scotoma a er a postchi- asmatic VFD or within central vision caused by bilateral postchias- matic lesions of various aetiologies.73–75 e de cit is most apparent in central vision and may manifest as a subtle impairment in hue dis- crimination. Such disorders are o en found a er unilateral occipi- totemporal lesions of vascular origin as well as a er mild cerebral hypoxia or in Alzheimer’s disease.76,77 Total achromatopsia is much more rarely found, usually associated with bilateral occipitotemporal or di use lesions (see case study in Box 14.2).78 Recovery of colour and form vision within a scotoma is o en observed in patients with partial visual eld recovery.79 As a rule, the progression of visual recovery (if there is one) in VFDs is as follows: light detection → light localization → brightness discrimination → form discrimination → colour perception. In those patients with colour vision de cits in cen- tral vision no recovery has been reported over six years in one study.80


Defective colour vision in visual eld regions

In patients with residual colour perception in a scotoma and incom- plete lesions, there is some evidence that improvement of colour discrimination can be trained by displaying coloured targets at the eld border and having the patient saccade to them and discrimi- nate the colour.

Defective colour perception in central vision

Forced discrimination of di erently coloured forms is partially e ective in cerebral anoxia, however with limited transfer to

non-trained colours.80 O en, patients can learn to base their col- our judgments on other cues such as the brightness or saturation despite permanently impaired hue discrimination.

Visual form, object, and face perception

de cits (visual agnosias)

e inability to recognize visual stimuli despite su ciently intact elementary visual functions (e.g. visual acuity, spatial contrast sen- sitivity) as well as una ected language processing and intact recog- nition in other modalities is de ned as visual agnosia.7 Depending on the severity and speci ty of the visual recognition de cit, several types of agnosia can be distinguished.

Visual object agnosia refers to impairments in recognizing com- plex objects or pictures. Traditionally, a distinction has been made between apperceptive agnosia and associative agnosia. e former indicates a de cit in perception which leads to impaired object discrimination; the latter implies loss of semantic knowledge or understanding what the object is, despite patients seemingly having intact perceptual abilities. us while apperceptive agnosic patients have di culty in copying objects or matching objects from di erent views (see Fig. 14.8a), patients with pure associative agnosia may copy and perform perceptual match tasks well but still not be able to say what an object is for—sometimes referred to as ‘perception stripped of meaning’,81,82 a core feature of the semantic dementia subtype of frontotemporal dementia. Such behaviour needs to be distinguished from anomia where patients may not be able to name an object but nevertheless can describe what it is or how it might be used. Hence, patients with associative agnosia cannot even match objects by semantic properties as illustrated in Fig. 14.8c. Visual form agnosia refers to a severe type of apperceptive visual object agnosia, characterized by an inability to discriminate even simple forms like rectangles or squares (see Fig. 14.8b). Prosopagnosia corresponds to a selective de cit in recognizing faces.7

Visual agnosias are commonly described as rare conditions (less than 3 per cent of all neurological patients),7,59,83 previously con- sidered to occur most frequently a er bilateral occipitotemporal lesions of vascular, traumatic, or anoxic origin.81 However, recent evidence indicates that visual agnostic de cits might be more frequent than previously assumed when every patient with pos- terior brain lesions is quantitatively tested (e.g. Martinaud and col- leagues84 reporting a frequency of 65 per cent following posterior cerebral artery infarction). Moreover, with greater recognition of neurodegenerative conditions it is becoming evident that these too may lead to visual agnosia. Impairments in object processing have also been reported for neurodegenerative diseases like AD asso- ciated with or without PCA,85–88 DLB,85 corticobasal syndrome (CBS),89 or Huntington’s disease (HD) (e.g. recognition of overlap- ping gures).90

Standardized diagnostic is available with the Birmingham Object Recognition Battery (BORB),91 or the Visual Object and Space Perception Battery (VOSP).92

Detailed case reports about recovery are rare. Partial recovery concerning object or face recognition of real-life objects has been occasionally noted, while recognition of photographs of objects or faces rarely improves. Recovery is particularly unlikely in anoxic brain damage, probably due to the widespread di use lesions and the additional cognitive impairment impeding the acquisition of compensatory strategies.93 Partial recovery is more likely in

CHAPTER 14 vision and visual processing deficits 153

Box 14.2 Cerebral achromatopsia

Case study

A 66-year-old man was washing his red car in a green meadow. Suddenly, he began to feel sick and noticed that his just-cleaned car appeared dirty, rusty brown, while the surrounding meadow looked more grey than green. e patient later reported that it seemed to him as if someone had switched o the colour TV into black-and-white mode. Furthermore, he described that although he had initially been able to recognize his car and house; later on he was not able anymore to see things in his upper eld of vision. As illustrated below, the patient showed severe impairments in a colour-matching task. In contrast, discrimination of grey shades (not shown) as well as colour imagery were unimpaired. His symp- toms were due to bilateral basal, temporo-occipital infarctions, associated with bilateral damage of lingual and fusiform gyri.

Examiner’s arrangement of colours Patient’s attempt to match colours

Original Patient’s copy

154 SECTION 2 cognitive dysfunction (a) Sample

(b) Sample


Fig. 14.8 Illustration of matching tasks in which agnostic patients depending on type of agnosia typically show de cits. (a) View-matching task: e patient has to match the sample to the target picture that is presented in a di erent view. Patients with apperceptive agnosia fail in such tasks as they are not able to form
a coherent visual perception of an object. (b) Form-matching task (Efron shapes). Form agnostic patients typically have de cits in comparing and matching simple forms. (c) Function-match task: e subject has to match those two pictures that share a common function. De cits in this task are characteristic for associative agnostic patients.

traumatic or vascular lesions and in those few cases with unilat- eral right sided lesions showing face agnosia.81 A case of transient postoperative prosopagnosia that spontaneously recovered a er six to seven days has been described,94 demonstrating that recovery is in principle possible, but this may depend on lesion size.


Visual form recognition can be improved in some cases by repeti- tive discrimination training for simple geometric forms equated for total luminance. Verbal or computerized feedback is essential with progressive increase in the similarity of the stimuli to be discrimi- nated. Treatment can be accomplished either with self-constructed paper-made stimuli, or using computerized devices (e.g. Efron shapes) which give detailed quantitative feedback and allow vari- ations of colours, sizes, and forms (cf. Kerkho & Marquardt).95 Controlled treatment studies are rare for complex object- and face-recognition de cits. Improvements have been reported using errorless-learning paradigms focusing on speci c search for key features of objects or faces.7,59 In general, the use of context infor- mation (knowledge about objects and faces and the relevant social situation) and non-visual cues is advisable and may be helpful for some patients.7

Visuospatial disorders

Visuospatial disorders are frequent impairments following stroke a ecting extrastriate cortical and subcortical brain areas (30–50 per cent a er le , 50–70 per cent a er right hemisphere stroke).96 Moreover, poor visuospatial skills are o en observed in conditions such as AD, PCA, DLB, and CBS.85,97,98 Since intact visuospatial abilities are relevant for many activities of daily living (e.g. dress- ing, transfers, reading the clock), they are important predictors for rehabilitation outcome, particularly a er right-hemisphere brain

damage.99 Four categories of visuospatial disorders have been pro- posed that are compatible with the neuroanatomical conception of a dorsal and ventral visual pathway proposed by Ungerleider and Mishkin (see also individual chapters 3, 4, and 5).100

Perceptive visuospatial disorders

is group of impairments occurs a er distinct lesions of (especially right-sided) parieto-occipital brain areas. More posterior lesions of these brain regions lead to de cits in estimation or discrimination of length, distance, or form. In contrast, more anterior (parieto- temporal) lesions are related to di culties in estimating position or orientation as well as perceiving the subjective visual vertical/ horizontal in the frontal and saggital plane; see Fig. 14.9a).101,102

Transformational visuospatial disorders

Some visuospatial tasks require spatial operations (rotation, mir- roring, scale transformation). De cits in perspective change or mental rotation tasks are related to parietal and parietooccipital lesions of both hemispheres; see Fig. 14.9b).102

Constructive visuospatial disorders

ese de cits refer to a heterogenous group of functional de cits, manifest as impairments in the ability of patients to manually con- struct or copy a gure comprising simpler elements (e.g. draw- ing or copying a geometric gure in two or three dimensions, see Fig. 14.10a & b). ‘Constructional apraxia’ is the term o en given to these de cits (not to be confused with limb apraxia). Despite their clinical and daily relevance as well as frequent co-occurrence with perceptive visuospatial, dysexecutive, and working memory de cits as well as neglect,103 the core mechanisms of constructive visuospatial symptoms are still unknown.102 Some authors have provided evidence for defective spatial remapping of locations across eye movements when information in retinal coordinates has to be transformed to locations in the external world.104

Topographic visuospatial disorders

Topographic visuospatial disorders refer to orientation de cits in the real as well as imagined three-dimensional space and are related




Subjective horizontal

Subjective vertical

Estimation of distance

Axis mirroring

Estimation of orientation

Estimation of form

Position mirroring

Fig. 14.9 (a) Examples for perceptual visuospatial tasks: subjective visual horizontal/vertical, estimation of orientation/distance/form. (b) Examples for cognitive visuospatial tasks: axis/position mirroring.

(a) Face


CHAPTER 14 vision and visual processing deficits 155 135° 45°


(b) Rey-Osterriethcomplexfigure

Original copy

Fig. 14.10 (a) Performance of two patients with a constructive visuospatial disorder when requested to draw a ower respectively a face from memory. (b) Copying performance of a patient with constructive visuospatial disorder in the Rey–Osterrieth complex gure test. Note also neglect of left-sided elements. (c) Illustration of visual line-orientation-estimation performance before (above) and after systematic training for two oblique orientations (45° and 135°; following).

to parahippocampal lesions or can occur as secondary de cits in neglect or Bálint–Holmes syndrome.102,105


Successful therapeutic approaches are feedback-based training of perceptual visuospatial abilities, visual background movement, constructive visuospatial training, reaction-chaining methods for topographic visuospatial disorders as well as ADL (activities of daily living) therapy.106 ese approaches including their therapeu- tic principles are summarized in Table 14.3. Concerning feedback- based training of visuospatial abilities, Funk and colleagues107 have reported rapid and long-lasting improvements in visual line-orien- tation discrimination a er systematic training along with transfer to other spatial domains such as visuoconstructive performance, clock reading, and horizontal writing (see Fig. 14.10c). In addi- tion, non-invasive galvanic vestibular stimulation has been shown to improve subjective visual vertical judgements in patients su er- ing from right-sided stroke.108 Treatments are, however, unlikely to help patients with progressive neurodegenerative disorders.

Visual motion perception de cits

with AD, and particularly the PCA variant. While processing of lin- ear moving patterns seems to be preserved, perception of optic ow is impaired in more than one-third of AD patients.112,113

Little is known about recovery. In those rare patients with bilat- eral lesions, no recovery has been reported,114 while those with uni- lateral lesions may show recovery. Even the motion-blind patient reported by Zihl and colleagues re-adapted to moving stimuli in daily life by certain compensatory techniques, despite her perma- nent motion de cit under laboratory conditions.114 Again, there are no realistic prospects for recovery in neurodegenerative cases.


Due to the rarity of severe impairments in visual motion process- ing and probably the multiplicity of cortical and subcortical areas involved in motion perception, treatment approaches have not been developed. However, the treatment of an associated ability (i.e. smooth pursuit eye movements when tracking a moving tar- get) is useful to improve visual scanning on computer screens and visual orientation in daily life.14 is can be accomplished by use of a large PC screen, where the patient follows a moving target in di erent directions with a stabilized head. In addition, training for situations in daily life where motion is important (crossing a street, using an escalator) may improve orientation and reduce the likeli- hood of accidents due to reduced motion perception.

Optic ataxia

Optic ataxia refers to a visuomotor disorder characterized by an impairment in visually guided reaching that is not attributable to other primary motor or visual disorders.115 At the bedside, this is assessed by asking the patient to xate on the examiner’s nose while the examiner’s nger is presented as a target for a reach in either the le or right visual hemi eld. Typically, healthy individuals can reach accurately even to a peripheral target while maintaining cen- tral xation, but patients with optic ataxia misreach under such conditions.

Complete loss of movement perception (akinetopsia)109 due to bilateral cerebral lesions is rather an unusual phenomenon.78 More incomplete impairments of visual motion perception may occur with a frequency of 13 per cent a er focal lesions of motion- sensitive regions, including area V5/MT in the occipito-parieto- temporal cortex, but permanent de cits are probably rare.110 However, many brain-damaged patients report subjectively prob- lems in estimating the velocity and position changes of moving vehicles in tra c situations as a pedestrian or when driving in a car. is may result either from impaired motion perception, possibly of impaired optic ow detection (radial patterns emerging when a subject moves),111 disturbed visuospatial perception, smooth pur- suit eye movements, or a combination of these factors. Moreover, de cits in motion perception have also been reported for patients

156 SECTION 2 cognitive dysfunction
Table 14.3 erapeutic approaches for visuospatial disorders

2. Optic ataxia: see earlier in the chapter
3. Visual neglect and visuospatial disorders such as impaired reten-

tion of distance, orientation, and position122

4. Oculomotor disorders: severe and impaired xation of gaze (sticky xation) as well as problems in generating saccades vol- untarily or on demand (oculomotor apraxia)7,123

Furthermore, patients show severe reading problems, while read- ing of short real words (four to six letters) is better than reading of non-words.124

Due to the bilateral or di use disseminated occipitoparietal lesions, recovery is limited in these severely and chronically disa- bled patients. It is estimated that some 30 per cent of patients with degenerative dementias might show aspects of Bálint–Holmes syn- drome,125,126 although rarely the complete syndrome, and this is much more common in PCA; the incidence in non-dementing, neurological disease is probably <0.5 per cent (Kerkho , unpub- lished results).


Research on e ective rehabilitation techniques is sparse (for review see references 13 and 127). It is likely that the disorder is o en over- looked or misdiagnosed. Eye blinking may eliminate confusing visual images or the patient’s subjective feeling of seeing the same object at multiple locations in space.2,7 Zihl59 noted some recovery of visual exploration and xation a er systematic training in three patients with Bálint–Holmes syndrome, but no recovery of the spa- tial disorder. Despite these occasional experiences e ective treat- ment strategies are poorly developed and evaluated.


1. Rowe F, Brand D, Jackson C, et al. Visual impairment following stroke: do stroke patients require vision assessment? Age Ageing. 2009;38(2):188–93.

2. Kerkho G. Neurovisual rehabilitation, recent developments and future directions. J Neurol Neurosur Ps. 2000;68:691–706.

3. Sucho IB, Kappor N, Ciu reda KJ, et al. e frequency of occur- rence, types, and characteristics of visual eld defects in acquired brain injury: A retrospective analysis. Optometry. 2008;79:259–65.

4. Mendez MF, Mendez MA, Martin R, et al. Complex visual disturbances in Alzheimer’s disease. Neurology. 1990;40(3): 439–43.

5. Kerkho G, Schaub J, and Zihl J. e anamnesis of cerebral visual disor- ders a er brain damage (German). Der Nervenarzt. 1990;61:711–18.
6. Neumann G, Schaadt A-K, Reinhart S, et al. Clinical and psychometric

evaluations of the Cerebral Vision Screening Questionnaire in 461 non- aphasic individuals post-stroke. Neurorehabilitation and Neural Repair. 30(3):187–98.

7. Zihl J. Rehabilitation of Visual Disorders a er Brain Injury, 2nd edn. New York, NY: Psychology Press, 2011.

8. Skeel RL, Schutte C, Van Voorst W, et al. e relationship between visual contrast sensitivity and neuropsychological performance in a healthy elderly sample. J Clin Exp Neuropsyc. 2–6;28(5):696–705.

9. Frisén L. e neurology of visual acuity. Brain. 1980;103:639–70. 10. Kerkho G. Restorative and compensatory therapy approaches in

cerebral blindness—a review. Restorative Neurology and Neuroscience.

11. Haarmeier T and ier P. Impaired analysis of moving objects due to

de cient smooth pursuit eye movements. Brain. 1999;122:1495–505. 12. Straube A and Kennard C. Ocular Motor Disorders. In: T Brandt, LR

Caplan, J Dichgans, et al. (eds). Neurological Disorders. Course and Treatment. San Diego, CA: Academic Press, 1996, pp. 101–11.

erapeutic approach

erapeutic principle

Feedback-based training of perceptual visuospatial abilities

Improvement of spatial perception by graded training with verbal or visual feedback; basic concept: recalibration of spatial perception

Visual background movement to improve perceptual visuospatial de cits

Improvement of attention for spatial expansion and orientation (subjective visual vertical/ horizontal) through repetitive stimulation; use of the attention-improving e ect of optokinetic stimulation

Constructive visuospatial training

Improvement of perceptual, cognitive, and constructive visuospatial abilities as well as planning performance by graded practice with constructive material (e.g. Tangram, block design training)

ADL therapy

Direct practice of problematic ‘spatial’ daily procedures (e.g. wheelchair navigation, getting dressed)

Reaction-chaining and memory strategies for learning routes in the environment

Parsing longer routes into shorter distances, practicing them by conditioning and later ‘chaining’ or linking them together; eventually additional use of mnestic strategies

Adapted from Der Nervenarzt. 78(4), Kerkho G, Oppenländer K, Finke K, et al.
erapy of cerebral visual perception disturbances (German), pp. 457–70, Copyright (2007), with permission from Springer.

Beside the severe impairment in reaching, many patients also demonstrate a problem in grasping peripherally presented visual objects. By contrast, reaching to the patient’s own body parts seems to be largely preserved,116 although reaching to auditory targets is also impaired.117 Furthermore, the accuracy of reaching can be improved by delaying the patient ́s movement initiation a er stimulus presentation.118,119 Optic ataxia is associated with lesions in the parieto-occipital junction and the superior parietal lobule120 and can occur both a er unilateral or bilateral brain damage and as a result of neurodegenerative diseases including AD. Due to the neuroanatomical overlap, optic ataxia can co-occur with neglect a er right parietal lesions (see chapter 5). For di erential diagno- sis, it is therefore important to note that neglect patients usually can reach and grasp accurately to visually presented objects in the neglected hemi eld if they notice them.116


Controlled treatment studies are rare. Since optic ataxia is less severe in the foveal than the a ected peripheral visual hemi eld,120 prior xation of the target before reaching or grasping usually improves reaching accuracy.

Bálint–Holmes syndrome, ocular motor apraxia

Bálint–Holmes syndrome designates a cluster of symptoms121 including:

1. Simultanagnosia: Impaired simultaneous perception of more than one object123

13. Perez FM, Tunkel RS, Lachmann EA, et al. Bálints-Syndrome arising from bilateral posterior cortical atrophy or infarction—rehabilitation strategies and their limitation. Disability and Rehabilitation. 1995;18:300–4.

14. Gur S and Ron S. Training in oculomotor tracking, occupational health aspects. Israel J Med Sci. 1992;28:622–8.

15. Bulens C, Meerwaldt JD, van der Wildt GJ, et al. Spatial contrast sen- sitivity in unilateral cerebral ischaemic lesions involving the posterior visual pathway. Brain. 1989;112:507–20.

16. Corkin S, Nissen MJ, Buonanno FS, et al. Spatial vision in Alzheimer’s disease. General ndings and a case report. Arch Neurol–Chicago. 1985;42:667–71.

17. Cronin-Golomb A, Corkin S, and Growdon JH. Visual dysfunc- tion predicts de cits in Alzheimer’s disease. Optometry Vision Sci. 1995;72(3):168–76.

18. Jackowski MM, Sturr JF, Taub HA, et al. Photophobia in patients with traumatic brain injury: uses of light- ltering lenses to enhance contrast sensitivity and reading rate. Neurorehabilitation. 1996;6:193–201.

19. Zihl J and Kerkho G. Foveal photopic and scotopic adaptation in patients with brain damage. Clin Vision Sci. 1990;2:185–95.

20. Rizzo M. Astereopsis. In: F Boller and J Grafman (eds). Handbook of Neuropsychology. Amsterdam: Elsevier, 1989, pp. 415–27.

21. Koh SB, Kim BJ, Lee J, et al. Stereopsis and colour vision impairment in patients with right extrastriate cerebral lesions. European Neurology. 2008;60:174–8.

22. Miller LJ, Mittenberg S, Carrey VM, et al. Astereosis caused by trau- matic brain injury. Arch Clin Neuropsy. 1999;14:537–43.

23. Hart CT. Disturbances of fusion following head injuries. Proceedings of the Royal Society of Medicine. 1969;62:704–6.

24. Schaadt A-K, Schmidt L, Kuhn C, et al. Perceptual re-learning of bin- ocular fusion a er hypoxic brain damage—four controlled single case treatment studies. Neuropsychology. 2014;28(3):382–87.

25. Schaadt A-K, Schmidt L, Reinhart S, et al. Perceptual relearning of binocular fusion and stereoacuity a er brain Injury. Neurorehabilitation and Neural Repair. 2014;28(5):462–71.

26. Schaadt A-K, Brandt SA, Kra A, et al. Holmes and Horrax (1919) revisited: Impaired binocular fusion as a cause of ‘ at vision’ a er right parietal brain damage—A case study. Neuropsychologia. 2015;69:31–8.

27. Wilkins A. What is visual discomfort? Trends Neurosci. 1986;9:343–6.

28. Zihl J. Visual scanning behavior in patients with homonymous hemia-
nopia. Neuropsychologia. 1995;33:287–303.

29. Pambakian A, Wooding D, Patel N, et al. Scanning the visual world: a
study of patients with homonymous hemianopia. J Neurol Neurosur Ps.

30. Pambakian AL, Mannan SK, Hodgson TL, et al. Saccadic visual search
training: a treatment for patients with homonymous hemianopia.
J Neurol Neurosur Ps. 2004;75:1443–8.

31. Machner B, Sprenger A, Sander T, et al. Visual Search Disorders in
Acute and Chronic Homonymous Hemianopia. Ann NY Acad Sci.

32. Zihl J. Eye movement patterns in hemianopic dyslexia. Brain.

33. Le A, Scott S, Crewes H, et al. Impaired reading in patients with right
hemianopia. Ann Neurol. 2000;47(2):171–8.

34. Spitzyna GA, Wise RJS, McDonald SA, et al. Optokinetic therapy
improves text reading in patients with hemianopic alexia. A controlled
trial. Neurology. 2007;68:1922–30.

35. Kerkho G. Displacement of the egocentric visual midline in altitudinal
postchiasmatic scotomata. Neuropsychologia. 1993;31:261–5.

36. Barton JJS and Black S. Line bisection in hemianopia. J Neurol Neurosur
Ps. 1998;64:660–62.

37. Kuhn C, Heywood C, and Kerkho G. Oblique spatial shi s of subjec-
tive visual straight ahead orientation in quadrantic visual eld defects.
Neuropsychologia. 2010;48:3205–10.

38. Kerkho G and Schenk T. Line bisection in homonymous visual eld
defects—recent ndings and future directions. Cortex. 2011;47:53–58.

39. Hesse C, Lane A, Aimola L, et al. Pathways involved in human con- scious vision contribute to obstacle-avoidance behaviour. European Journal of Neuroscience. 2012;36(3):2383–90.

40. Husain M. Hemispatial neglect. In: G Goldenberg and BV Miller (eds). Handbook of Clinical Neurology. Amsterdam: Elsevier, 2008, pp. 359–72.

41. Kerkho G and Bucher L. Line bisection as an early method to assess homonymous hemianopia. Cortex. 2008;44(2):200–5.

42. Kuhn C, Bublak P, Jobst S, et al. Contralesional spatial bias in chronic hemianopia: e role of (ec)centric xation, spatial cueing and visual search. Neuroscience. 2012;210:118–27.

43. Kuhn C, Bublak P, Grotemeyer KH, et al. Does spatial cueing a ect line bisection in chronic homonymous hemianopia? Neuropsychologia. 2012;50:1656–62.

44. Baier B, Mueller N, Fechir M, et al. Line bisection error and its ana- tomic correlate. Stroke. 2010;41(7):1561–3.

45. Zhang X, Kedar S, Lynn JJ, et al. Natural history of homonymous hemianopia. Neurology. 2006;66:901–5.

46. Zihl J and von Cramon D. Recovery of visual eld in patients with postgeniculate damage. In: K Poeck, HJ Freund, H Gänshirt (eds). Neurology. Heidelberg: Springer, 1986, pp. 188–94.

47. Mödden C, Behrens M, Damke I, et al. A randomized controlled trial comparing 2 interventions for visual eld loss with standard occupa- tional therapy during inpatient stroke rehabilitation. Neurorehabilitation and Neural Repair. 2012;26(5):463–9.

48. Bouwmeester L, Heutink J, and Lucas C. e e ect of visual training for patients with visual eld defects due to brain damage: a systematic review. J Neurol Neurosur Ps. 2007;78:555–64.

49. Bolognini N, Rasi F, Coccia M, et al. Visual search improve-
ment in hemianopic patients a er audio-visual stimulation. Brain. 2005;128:2830–42.

50. Keller I and Le n-Rank G. Improvement of visual search a er audio- visual exploration training in hemianopic patients. Neurorehabilitation and Neural Repair. 2010;24(7):666–73.

51. Kasten E, Wüst S, Behrens-Baumann W, et al. Computer-based training for the treatment of partial blindness. Nature Med. 1998;4:1083–7.

52. Nelles G, Esser J, Eckstein A, et al. Compensatory visual eld train- ing for patients with hemianopia a er stroke. Neuroscience Letters. 2001;306:189–92.

53. Reinhard J, Schreiber A, Schiefer U, et al. Does visual restitution training change absolute homonymous visual eld defects? A fundus controlled study. B J Ophthalmol. 2005;89:30–35.

54. Roth TT, Sokolov AN, Messias AA, et al. Comparing explorative saccade and icker training in hemianopia: A randomized controlled study. Neurology. 2009;72(4):324–31.

55. Lane AR, Smith DT, Ellison A, et al. Visual Exploration Training Is No Better than Attention Training for Treating Hemianopia. Brain. 2010;133(6):1717–28.

56. Aimola L, Lasne AR, Smith DT, et al. (submitted). E cacy and feasibil- ity of a home-based computer training for individuals with homony- mous visual eld defects. Neurorehabilitation and Neural Repair. 2014; 28(3):207–18.

57. Bowers A, Keeney K, and Peli E. Community-based trial of a peripheral prism visual eld expansion device for hemianopia. Arch Ophthalmol– Chic. 2008;126(5):657–64.

58. Kerkho G, Münssinger U, Haaf E, et al. Rehabilitation of homonym- ous scotomata in patients with postgeniculate damage of the visual system: saccadic compensation training. Restorative Neurology And Neuroscience. 1992;4(4):245–54.

59. Zihl J and Kennard C. Disorders of higher visual functions. In: T Brandt, LR Caplan, J Dichgans, et al. (eds). Neurological Disorders. Course and Treatment. San Diego, CA: Academic Press, 1996, pp. 201–12.

60. Anton G. Ueber die Selbstwahrnehmung der Herderkrankungen des Gehirns durch den Kranken bei Rindenblindheit und Rindentaubheit. Archiv für Psychiatrie und Nervenkrankheiten. 1899;32:86–127.

61. Zihl J. Zerebrale Sehstörungen. In H -O. Karnath, W Hartje, and W Ziegler (eds). Kognitive Neurologie. Stuttgart: ieme, 2006, pp. 1–18.

CHAPTER 14 vision and visual processing deficits 157

158 SECTION 2 cognitive dysfunction

62. Hartmann J, Wolz W, Roeltgen D, et al. Denial of visual perception. Brain Cognition. 1991;16(1):29–40.

63. Kortte K, Wegener ST, and Chwalisz K. Anosognosia and denial: eir relationship to coping and depression in acquired brain injury. Rehabilitation Psychology. 2004;48(3):131–6.

64. Zihl J. Visuelle Reizerscheinungen. In H -O Karnath and P ier (eds). Neuropsychologie. Heidelberg: Springer, 2006, pp. 84–7.

65. Lance JW. Simple formed hallucinations con ned to the area of a spe- ci c visual eld defect. Brain. 1976;99:719–34.

66. Kölmel HW. Coloured patterns in hemianopic elds. Brain. 1984;107:155–67.

67. Kölmel HW. Complex visual hallucinations in the hemianopic eld. J Neurol Neurosur Ps. 1985;47:29–38.

68. Baier B, de Haan B, Mueller N, et al. Anatomical correlate of positive spontaneous visual phenomena: a voxelwise lesion study. Neurology. 2010;74(3):218–22.

69. Holroyd S, Shepherd ML, and Downs J. Occipital atrophy is associated with visual hallucinations in Alzheimer’s disease. J Neuropsych Clin N. 2000;12(1):25–8.

70. Kropp S, Schulz-Schae er W, Finkenstaedt M, et al. e Heidenhain variant of Creutzfeldt–Jakob disease. Arch Neurol. 1999;56(1), 55–61.

71. Goetz C, Leurgans S, Pappert E, et al. Prospective longitudinal assessment of hallucinations in Parkinson’s disease. Neurology. 2001;57(11):2078–82.

72. Meppelink A, de Jong B, Renken R, et al. Impaired visual processing preceding image recognition in Parkinson’s disease patients with visual hallucinations. Brain.2009;132:2980–93.

73. Meadows JC. Disturbed perception of colours associated with localized cerebral lesions. Brain. 1974;97:615–32.

74. Zeki S. A century of cerebral achromatopsia. Brain. 1990;113:1721–77.

75. Bouvier SE and Engel SA. Behavioral de cits and cortical damage loci
in cerebral achromatopsia. Cerebral Cortex 2006;16(2):183–91.

76. Vingrys A and Garner L. e e ect of a moderate level of hypoxia on
human color vision. Documenta Ophthalmologica. 1987;2:171–85.

77. Cronin-Golomb A, Sugiura R, Corkin S, et al. Incomplete achromatop-
sia in Alzheimer’s disease. Neurobiol Aging. 1993;14(5):471–7.

78. Rizzo M and Barton JJS. Central disorders if visual function. In: NR
Miller, NJ Newman, V Biousse, and JB Kerrison (eds). Walsh and Hoyt’s Clinical Neuro-Ophthalmology: e Essentials. Philadelphia, PA: Lippincott Williams and Wilkins, 2008, pp. 263–84.

79. Zihl J and von Cramon D. Visual eld recovery from scotoma in patients with postgeniculate damage. Brain. 1985;108:335–65.

80. Merrill MK and Kewman DG. Training of colour and form iden- ti cation in cortical blindness, a case study. Arch Phys Med Rehab. 1986;67:479–83.

81. Farah M. Visual Agnosia. Cambridge, MA: MIT Press, 1990.

82. Riddoch MJ and Humphreys GW. Object recognition. In B. Rapp (ed.). e Handbook of Cognitive Neuropsychology. New York, NY: Psychology
Press, 2001, pp. 45–74.

83. Zihl J and Nelles G. Rehabilitation von zerebralen Sehstörungen. In: G
Nelles (ed.). Neurologische Rehabilitation. Stuttgart: ieme, 2004, pp.

84. Martinaud O, Pouliquen D, Gérardin E, et al. Visual agnosia and pos-
terior cerebral artery infarcts: An anatomical-clinical study. PLoS One.

85. Mosimann UP, Mather GG, Wesnes KA, et al. Visual perception in
Parkinson disease dementia and dementia with Lewy bodies. Neurology.

86. Done D and Hajilou B. Loss of high-level perceptual knowledge of
object structure in DAT. Neuropsychologia. 2005;43(1):60–8.

87. Caterini FF, Sala S, Spinnler HH, et al. Object recognition and object
orientation in Alzheimer’s disease. Neuropsychology. 2002;16(2):146–55.

88. Adlington RL, Laws KR, and Gale TM. Visual processing in Alzheimer’s
disease: Surface detail and colour fail to aid object identi cation.
Neuropsychologia. 2009;47(12):2574–83.

89. Mori E, Shimomura T, Fujimori M, et al. Visuoperceptual impairment

90. Finke K, Schneider WX, Redel P, et al. e capacity of attention and simultaneous perception of objects: A group study of Huntington’s disease patients. Neuropsychologia. 2007:45(14):3272–84.

91. Riddoch MJ and Humphreys GW. Birmingham Object Recognition Battery. Hove: Lawrence Erlbaum Associates, 1993.

92. Warrington EK and James M. e visual object and space perception battery. Bury St Edmunds: ames Valley Test Company, 1991.
93. Sparr SA, Jay M, Drislane FW, et al. A historic case of visual agnosia

revisited a er 40 years. Brain. 1991;114:789–800.
94. Mesad S, La R, and Devinsky O. Transient postoperative prosopag-

nosia. Epilepsy and Behavior 2003;4(5):567–70.
95. Kerkho G and Marquardt C. Standardised analysis of visuospatial

perception a er brain damage. Neuropsychological Rehabilitation.

96. Jesshope HJ, Clark MS, and Smith DS. e Rivermead Perceptual

Assessment Battery: its application to stroke patients and relationship

with function. Clinical Rehabilitation. 1991;5:115–22.
97. Tang-Wai D, Josephs K, Boeve B, et al. Pathologically con rmed

corticobasal degeneration presenting with visuospatial dysfunction.

98. Graham N, Bak T, and Hodges J. Corticobasal degeneration as a cogni-

tive disorder. Movement Disorders. 2003;18(11):1224–32.
99. Kaplan J and Hier DB. Visuospatial de cits a er right hemisphere

stroke. Am J Occup er. 1982;36(5):314–21.
100. Ungerleider LG and Mishkin M. Two cortical visual systems.

In: D Ingle and MA Goodale (eds). Analysis of Visual Behavior.

Cambridge, MA: e MIT Press, 1982, pp. 549–85.
101. Utz KS, Keller II, Artinger FF, et al. Multimodal and multispatial

de cits of verticality perception in hemispatial neglect. Neuroscience.

102. Kerkho G. Störungen der visuellen Raumorientierung. In:

H -O Karnath and P ier (eds). Kognitive Neurowissenscha en.

Berlin: Springer, 2012, pp. 241–9.
103. Marshall RS, Lazar RM, Binder JR, et al. Intrahemispheric localization

of drawing dysfunction. Neuropsychologia. 1994;32(4):493–501. 104. Russell C, Deidda C, Malhotra P, et al A de cit of spatial remap-

ping in constructional apraxia a er right-hemisphere stroke. Brain.

105. Aguirre GK and D’Esposito M. Topographical disorientation: A syn-

thesis and taxonomy. Brain. 199;122(9):1613–28.
106. Kerkho G, Oppenländer K, Finke K, et al. erapy of cere-

bral visual perception disturbances (German). Der Nervenarzt.

107. Funk J, Finke K, Reinhart S, et al. (in press). E ects of feedback-

based visual line-orientation discrimination training for visuo- spatial disorders a er stroke. Neurorehabilitation and Neural Repair. 2013;27(2):142–52.

108. Oppenländer K, Utz KS, Reinhart S, et al. Subliminal galvanic- vestibular stimulation recalibrates the distorted visual and tactile sub- jective vertical in right-sided stroke. Neuropsychologia. doi:10.1016/j. neuropsychologia.2015. 03.004.

109. Zeki S. Cerebral akinetopsia (visual motion blindness). A review. Brain. 1991;114:811–24.

110. Schenk T and Zihl J. Visual motion perception a er brain dam- age, I. De cits in global motion perception. Neuropsychologia. 1997;35:1289–97.

111. Gibson JJ. e Perception of the Visual World. Boston: Houghton Mi in, 1950.

112. Tetewsky S and Du y CJ. Visual loss and getting lost in Alzheimer’s disease. Neurology. 1999;52:958–65.

113. O’Brien H, Tetewsky S, Avery L, et al. Visual mechanisms of spatial disorientation in Alzheimer’s disease. Cerebral Cortex. 2001;11(11):1083–92.

114. Zihl J, von Cramon D, Mai N, and Schmid C. Disturbance of movement vision a er bilateral posterior brain damage. Further evidence and follow up observations. Brain. 1991;114:2235–51.

in dementia with Lewy bodies. Arch Neurol. 2000;57(4):489–93.

115. Perenin M and Vighetto A. Optic ataxia: a speci c disruption in visuo- motor mechanisms. I. Di erent aspects of the de cit in reaching for objects. Brain. 1988;111:643–74.

116. Goldenberg G. e neuropsychological assessment and treat- ment of disorders of voluntary movement. In JM Gurd, U Kischka, and JC Marshall (eds). e Handbook of Clinical Neuropsychology. Oxford: Oxford University Press, 2010, pp. 387–400.

117. Phan M, Schendel K, Recanzone G, et al. Auditory and vis-
ual spatial localization de cits following bilateral parietal lobe lesions in a patient with Balint’s syndrome. J Cognitive Neurosci. 2000;12(4):583–600.

118. Milner A, Dijkerman H, McIntosh R, et al. Delayed reaching and grasping in patients with optic ataxia. Progress in Brain Research. 2003;142:225–42.

119. Rossetti YY, Revol PP, McIntosh RR, et al. Visually guided reach- ing: Bilateral posterior parietal lesions cause a switch from
fast visuomotor to slow cognitive control. Neuropsychologia. 2005;43(2):162–77.

120. Karnath H and Perenin M. Cortical control of visually guided reaching: Evidence from patients with optic ataxia. Cerebral Cortex. 2005;15(10):1561–9.

121. Rafal RD. Bálint syndrome. In: TE Feinberg and MJ Farah (eds). Behavioral Neurology and Neuropsychology. Boston: McGraw-Hill, 1997, pp. 337–56.

122. Moreaud O. Bálint syndrome. Arch Neurol. 2003;60(9):1329–31.
123. Zee DS and Newman-Toker D. Supranuclear and internuclear ocular motility disorders. In: NR Miller, NJ Newman, V Biousse, et al. (eds).

Walsh and Hoyt’s Clinical Neuro-Ophthalmology: e Essentials.

Philadelphia, PA: Lippincott Williams & Wilkins, 2005, pp. 344–76. 124. Baylis GC, Driver J, Baylis LL, et al. Reading of letters and

words in a patient with Balint’s syndrome. Neuropsychologia.

1994;32(10): 1273–86.
125. Mendez M, Tomsak R, and Remler B. Disorders of the visual system in

Alzheimer’s disease. J Clin Neuro-Ophthal. 1990;10(1): 62–9.
126. Rizzo M. ‘Bálint’s syndrome’ and associated visuospatial disorders.

Baillière’s Clinical Neurology. 1993;2(2):415–37.
127. Kerkho G and Heldmann B. Balint syndrome and associated disor-

ders. Anamnesis—diagnosis—approaches to treatment (german). Der

Nervenarzt. 1999;70(10):859–69.
128. Uchiyama M, Nishio Y, Yokoi K, Hirayama K, Imamura T, Shimomura

T, and Mori E. Pareidolias: Complex visual illusions in dementia with Lewy bodies. Brain. 2012;135(8):2458–69.

CHAPTER 14 vision and visual processing deficits 159


Disorders of attentional processes
Paolo Bartolomeo and Ra aella Migliaccio


e term ‘attention’ refers to a heterogeneous set of cognitive pro- cesses which allow an organism to successfully cope with a con- tinuously changing external and internal environment, while maintaining its goals.1 is exibility calls for mechanisms that (a) allow for the processing of novel, unexpected events, that could be either advantageous or dangerous, in order to respond appropri- ately with either approaching or avoidance behaviour; (b) allow for the maintenance of nalized behaviour despite distracting events.2 To behave in a coherent and goal-driven way, we need to select stimuli appropriate to our goals while ignoring other less important objects. us, in a sense, objects in the world compete for recruiting our attention in order to be the focus of our subsequent behaviour, because of the obvious capacity limitations in our ability of deal- ing with multiple objects. Neural mechanisms of attention resolve this competition by taking into account both the agent’s goals and the salience of the sensorial stimuli.3 Neurological damage may impair these mechanisms and produce various sorts of attention disorders.4

e present chapter will focus on some of these disorders, such as the inability to process several visual objects at a time (simultagno- sia), the unawareness of an object when presented in competition to another one (extinction), or when occurring on one side of space (visual neglect). Other disorders may a ect the general ability to respond to external stimuli and to sustain attention over time,5 or to plan and coordinate di erent activities and inhibit inappropriate responses (monitoring/executive control).6,7

With ageing, people o en report a growing number of cogni- tive di culties. In some cases, elderly persons complain of ‘loss of e ciency’, for example, forgetting where objects are placed, having the impression of being unsafe when driving, experiencing trouble when in new places or navigating new routes. Neurological condi- tions, on the other hand, can lead to severe impairments in dif- ferent types of attention. ese problems o en occur in patients with acute vascular strokes (ischaemic or haemorrhagic), but they can also be observed in other neurological conditions, such as head trauma, brain tumours, or neurodegeneration. In several neurodegenerative conditions (e.g. corticobasal syndrome, CBS; Alzheimer’s disease, AD; parkinsonian syndromes such as demen- tia with Lewy bodies, DLB), attention de cits can appear as part of more complex cognitive impairment pro le. In others, such as in posterior cortical atrophy (PCA), they may constitute the cen- tral core of the syndrome.8 Because we know far more about visual

attention than any other sensory modality, in this chapter we focus on examples of visual inattention, although many of the conditions we discuss can also extend to other modalities.

Cortical networks for visuospatial attention

and visual recognition

ere is now considerable information on the functional anatomy, dynamics and pathological dysfunction of brain networks that sub- serve the spatial orienting of gaze and attention in the human brain. Important components of these networks include the dorsolateral prefrontal cortex (PFC) and the posterior parietal cortex (PPC). Physiological studies indicate that these two structures show inter- dependence of neural activity. In the rhesus monkey, analogous PPC and PFC areas show coordinated activity when the animal selects a visual stimulus as the goal of attention by, for example, moving their gaze to it.9

Functional MRI (fMRI) studies in healthy human participants (reviewed in reference 2 at p.1167) indicate the existence of fron- toparietal networks for spatial attention (Fig. 15.1, right panel). A dorsal attentional network (DAN), composed of the intrapari- etal sulcus/superior parietal lobule and the frontal eye eld/dor- solateral PFC, shows increased blood oxygenation level-dependent (BOLD) responses during the spatial orienting period. A more ven- tral attentional network (VAN), which includes the inferior pari- etal lobule (IPL) and the ventral PFC (inferior and middle frontal gyri) demonstrates increased BOLD responses when participants have to respond to targets presented at unexpected locations. us, the VAN is considered important for detecting salient, unexpected but behaviourally relevant events. Others have also argued for a role of the VAN in vigilance or sustaining attention over time.11 Importantly, the VAN is considered to be strongly lateralized to the right hemisphere,10 whereas the DAN appears to be more bilateral and symmetric (but see references 12 and 13 for possible asym- metries favouring the DAN in the right hemisphere).

Not surprisingly, PFC and PPC are directly and extensively inter- connected. In particular, studies in the monkey brain have identi- ed three distinct frontoparietal long-range pathways(see Fig 15.1, le panel).14,15 Recent evidence from advanced in vivo tractogra- phy techniques and postmortem dissections suggests that a similar architecture exists in the human brain (Fig. 15.1, middle panel).16 In humans, the most dorsal branch (SLF I) originates from BA (Brodmann’s area) 5 and 7 and projects to BA 8, 9, and 32. e mid- dle pathway (SLF II) originates in BA 39 and 40 within the IPL and

162 SECTION 2 cognitive dysfunction


Fig. 15.1 Fronto-parietal networks in the monkey (left, from reference 15) and in the human right hemisphere (middle, from reference 16). Right: attentional networks in the right hemisphere according to Corbetta and Shulman.104
Reproduced from Front Hum Neurosci. 6(110), Bartolomeo P, iebaut de Schotten M, and Chica AB, Brain networks of visuospatial attention and their disruption in visual neglect, Copyright (2012), with permission from Frontiers Media S.A, reproduced under the Creative Commons CC BY-NC 3.0 License.

reaches prefrontal BA 8 and 9. e most ventral pathway (SLF III) originates in BA 40 and terminates in BA 44, 45, and 47.

ese results are consistent with the fMRI evidence on atten- tional networks reviewed above. In particular, the SLF III connects the cortical nodes of the VAN, whereas the DAN is connected by the human homologue of SLF I. e SLF II connects the parietal component of the VAN to the prefrontal component of the DAN, thus allowing direct communication between ventral and dor- sal attentional networks. Importantly, in good agreement with asymmetries of BOLD response during fMRI—with larger right- hemisphere response for the VAN and more symmetrical activity for the DAN10—the SLF III (connecting the VAN) is anatomic- ally larger in the right hemisphere than in the le hemisphere, whereas the SLF I (connecting the DAN) is more symmetrically organized.16 e lateralization of the SLF II is instead strongly correlated to behavioural signs of right-hemisphere specializa- tion for visuospatial attention such as pseudo-neglect in line bisection (i.e. small le wards deviations of the subjective mid- line observed in healthy individuals),17–19 and asymmetries in the speed of detection of events presented in the right or in the le hemi eld.16

ese frontoparietal attentional systems are o en considered important for spatially-based visual abilities (but see reference 20 for nonspatial functions of the IPL). ey are to be distinguished from the dorsal and ventral visual streams which originate from the occipital cortex.21,22

De cits of high-level visual abilities

e occipitoparietal cortical visual stream—or ‘dorsal visual stream’—processes information about objects and their locations in a moment-to-moment manner, and mediates the visual con- trol of skilled actions. More ventral, occipitotemporal networks are instead critical for other visual abilities, such as visual recogni- tion21,22 (see chapter 14). ey appear to carry information about perceptual features, allowing the building of long-term representa- tions necessary to identify and recognize objects.

Damage to the occipitotemporal cortical visual stream impairs the perceptual recognition of visual items such as objects, faces, colours, and written words, whereas more dorsal, occipitopari- etal de cits concern the processing of spatial location (spatial

awareness and reaching movements) (see Box 15.1, cases 1 and 2). Anatomically, the ventral stream is composed of the occipitotem- poral cortices and the white matter bundles running between these regions, which include the inferior longitudinal fasciculus and por- tions of the inferior fronto-occipital fasciculus.23,24

Visuospatial de cits in neurodegenerative conditions o en develop and progress along these two main cortico-cortical axes. In particular, the distribution of neuropathology in neurodegen- eration seems to follow speci c trajectories for each syndrome, targeting speci c cerebral networks.25 For example, the pattern of network change in PCA is di erent to that in CBS, both of which can present with attention de cits, together with other features that might help distinguish between them. Within this framework, the anatomical de nition of ventral and dorsal variants can assist cli- nicians in localization, and allow them to de ne the distribution of pathology by bedside testing.26 Given these correspondences between disease, anatomically damaged patterns, and related cog- nitive impairment, the interpretation of neuropsychological tests of visuospatial cognition has important implications both for di er- ential diagnosis and to monitor disease progression (see Box 15.1 and Fig. 15.3).

Visual neglect

Vascular, traumatic, neoplastic, or degenerative damage to fron- toparietal networks in the right hemisphere is frequently associated with a disabling condition known as visual neglect.27–29 About half of the patients with a lesion in the right hemisphere su er from neglect for the contralesional, le side of space.30 ey are unaware of items to their le . Neglect patients may not eat from the le part of their dish, they o en bump their wheelchair into obstacles situ- ated on their le , and have a tendency to look to right-sided details in a visual scene, as if their attention were ‘magnetically’ attracted by these details.31 Many of them are also inattentive to auditory or somatosensory stimuli to the le . Neglect patients are usually unaware of their de cits (anosognosia), and o en obstinately deny being hemiplegic. Individuals with le brain damage may also show signs of contralesional, right-sided neglect, albeit more rarely and usually in a less severe form.32,33

Neglect is a substantial source of handicap and disability for patients, and entails a poor functional outcome. Diagnosis is important, because e ective rehabilitation strategies are becoming


available,34 and there are promising possibilities for pharmaco- logical treatments.35 Furthermore, in many cases the nature of neg- lect de cits (impaired active exploration of a part of space) renders the diagnosis di cult or impossible if signs of neglect are not sought.

Neglect is especially frequent a er focal vascular lesions of the right hemisphere, but signs of neglect have been described in AD.36–39 More recently, signs of visual neglect have also been described in PCA. Out of 24 PCA patients, signs of neglect on at least one paper-and-pencil test were present in 16 patients, and

14 also had visual extinction or hemianopia.40 In one patient with PCA and le -sided neglect as a presenting sign, MRI-based DTI tractography demonstrated damage to frontoparietal white matter bundles relatively selective to right-hemisphere pathways (refer- ence 41 p. 4752) (see patient 3, Box 15.2).

Diagnostic tests

Patients’ performance on paper-and-pencil tasks can easily dem- onstrate the presence and the extent of visual neglect. Here we

CHAPTER 15 disorders of attentional processes 163

Box 15.1 Ventral/dorsal PCA (posterior cortical atrophy) variants

On the basis of the schematic dichotomy between dorsal (occipito-parieto-frontal) and ventral (occipito-temporal and occipito-frontal) cortical visual networks, here we present three patients a ected by PCA, but showing a di erent pattern of white matter damage along these two main axes.26

Patient 1 was a 62-year-old woman who had been experiencing isolated di culties in reading and writing for about seven years. At the time of the study, she complained of episodes of topographical disorientation, and her neuropsychological pro le was dominated by a severe visual impairment. She was unable to copy the Rey complex gure. She was impaired in object and space perception and in face recognition tests. She performed poorly on reading words and pseudo-words. Despite her marked visual and gnosic di culties, she had excellent episodic memory for recent events, and no di culty in remembering appointments. She had a normal verbal working memory as measured by backwards digit span. Her speech was uent and syntactically well formed. She performed normally on tests of word uency tasks, as well as on tests of comprehension. Insight was preserved. e tractography study of this patient demonstrated white matter damage along all the components of the ventral cortical visual stream (namely, the inferior longitudinal and the fronto-occipital fasciculi) (Fig. 15.2a).

Patient 2 (Fig. 15.2b) was a 62-year-old lady. She had been experiencing episodes of misplacing of objects for the past two-and-a-half years, along with reading problems, prosopagnosia, le -right disorientation, and anomia. She was poorly oriented at the time of testing, with a severe visual agnosia. She also experienced de cits in working memory, visuospatial and verbal episodic memory. At the time of MRI, she had a severe optic ataxia, mild visuospatial neglect, and exhibited irritability and loss of interests. She had both dorsal and ventral dysfunction.26 In contrast, another PCA patient, with selectively impaired ‘ventral’ abilities (object recognition de cits, reading di culties, and impaired face recognition) had spared SLF (Fig. 15.2c).

(a) R








fractional anisotropy


Fig. 15.2 An illustrative reconstruction of the ventral (inferior longitudinal fasciculus, ILF and the inferior fronto-occipital fasciculus, IFOF) and dorsal (fronto-parietal superior longitudinal fasciculus, SLF, branches II and III) stream pathways. Long-range white matter tracts of patients are rendered as maps of fractional anisotropy (FA, index of microstructural white matter integrity) and displayed on the native T1-weighted MRI. FA values range from 0.40 (yellow) to 0.50 (dark red). e lower the value, the greater the damage. (a) PCA patient 1 had a long clinical history of isolated de cits in reading and writing, followed by an impairment in object and space perception and face recognition, and showed a bilateral ventral white matter damage. (b) PCA patient 2, with optic ataxia and signs of mild left neglect two-and-a-half years after disease onset, had a di usely damaged frontoparietal SLF (mean FA = 0.39). (c) Another PCA patient with preserved SLF (mean FA = 0.44).

See Box 15.1 for more clinical details.
Reproduced from Neurobiology of Aging. 33(11), Migliaccio R, Agosta F, Scola E, et al. Ventral and dorsal visual streams in posterior cortical atrophy: A DT MRI study, pp. 2572–84, Copyright (2012), with permission from Elsevier.

164 SECTION 2 cognitive dysfunction Pt #3

Pt. #4

Fig. 15.3 Performance on paper-and-pencil tests of PCA-AD patient 3 (see Box 15.2) and PCA-CBS patient 4. From left to right: clock-drawing test, copy of a drawing, line bisection. Note that patient 3, when copying the landscape, omitted the whole left part of the scene (scene-based pattern). Patient 4, on the other hand, tended to omit the left part of each element of the scene (object-based pattern); she also showed some spatial disorganization in placing the numbers during the clock drawing test.

Reproduced from Cortex. 48(10), Migliaccio R, Agosta F, Toba MN, et al. Brain networks in posterior cortical atrophy: a single case tractography study and literature review, pp. 1298–309, Copyright (2012), with permission from Elsevier.


brie y describe three visuomotor procedures simple enough as to be administered at the bedside (for other tests, see reference 4, p. 5198; reference 30, p. 1425; reference 42; reference 43, p. 4380). Care should be taken in the proper positioning of the test sheet; in the usual clinical conditions, the midline of the sheet should cor- respond to the trunk midline of the patient. Performance on these tasks is described by taking into account neglect for the le side of space, which is more common, severe, and durable than right- sided neglect in vascular patients.32 e relative frequency of le and right neglect in neurodegenerative conditions is currently unknown. In some studies right-sided neglect was observed with an unexpected, relatively high frequency in neurodegenerative dis- eases as compared to vascular patients (reference 40, p. 4310; see also reference 37, p. 515 for discussion of possible mechanisms), whereas other studies found the usual predominance of le -sided neglect to be present also in degenerative patients.44

Importantly, patients who perform normally on these paper-and- pencil tests may nevertheless show spatial or nonspatial de cits on more demanding tests of visuospatial attention, such as speeded response time tests. It is important to be aware of the possibility of these seemingly ‘subclinical’ de cits, which might well have clin- ical implications, for example in taking decisions about the patient’s ability to drive. In neurodegenerative conditions, such de cits of spatial attention have been described in patients with Alzheimer’s disease.45–47 Parkinson’s disease,48,49 Huntington’s disease,50,51 and progressive supranuclear palsy.52

Drawing tasks

When drawing gures, whether from memory or by copying them, neglect patients omit or distort the details on the le side (Fig. 15.3).52 When copying patterns composed of several elements

aligned horizontally, some patients neglect the whole le part of the model, while others copy all the items but leave un nished the le part of each (Fig. 15.3 and 15.4).53,54

ese distinct patterns of performance have been referred to, respectively, as scene- (or viewer-) based neglect and object-based neglect.55

Cancellation tasks

In cancellation tasks, patients are requested to search for and cross out items scattered on a paper sheet, such as lines,56 letters,57 or shapes.58,59 Patients with right hemisphere damage typically begin to scan the sheet from the right side, unlike normal participants or patients with le brain damage, who start from the le side.60 Patients with le neglect may omit a variable number of le -sided targets; some patients may continue to cancel the same right-sided items over and over again. Fig. 15.5 shows the performance on a shape cancellation test of a patient with PCA and mild signs of le neglect.

Line bisection

In line bisection tasks, patients have to mark the midpoint of a hori- zontal line; neglect patients deviate the subjective midpoint to the right of the true centre of the line (see Fig. 15.3).61 e amount of deviation depends on several factors. e longer the line, the more rightward the bisection point; for the shortest lines there may be a paradoxical le ward deviation (the ‘crossover e ect’).62 e loca- tion in space of the line with respect to the patient’s trunk midline also in uences performance; rightward deviation increases when lines are located in the le hemispace and decreases when they are in the right hemispace.61,63 Although patients’ performance on line bisection may dissociate from their performance on other tasks, such as cancellation tests,64 it remains a very useful test

particularly in situations, such as PCA, where simultagnosia may sometimes render di cult or impossible the completion of cancel- lation tests.65


Sensory extinction refers to the failure of brain-damaged patients to report the stimulus contralateral to their lesion when stimulated on both sides, despite being able to report a single stimulus pre- sented on either side. Extinction can occur in di erent sensory modalities: visual,66 somatosensory,67 acoustic,68 olfactory,69 and even cross-modally.70 Accounts of extinction typically emphasize either a sensory problem not severe enough to impair perception of single stimuli,71 or an attentional disorder favouring ipsilateral over contralateral stimuli,72 or both.73 Although visual extinction usu- ally occurs a er vascular strokes in the territory of medial cerebral artery, it has also been observed in neurodegenerative conditions such as PCA.40

Diagnostic tests

In clinical practice, the presence of extinction is traditionally inves- tigated using various sorts of double simultaneous stimulation. e confrontation method is a common test of visual extinction. e examiner asks the patient to xate the examiner’s nose and then brie y moves his/her ngers either in one hemi eld or in both hemi elds simultaneously. For example, six single unilateral stim- uli and six double simultaneous stimuli can be presented in pseu- dorandom order.40 In practice, patients can be considered to show visual extinction when they fail at least twice to report a contralat- eral stimulus during bilateral simultaneous presentation, while accurately detecting all unilateral stimuli.31 When the patient fails to report all stimuli on one side (whether single or double), homon- ymous hemianopia is a likely diagnosis which, however, requires con rmation with more detailed testing of the visual eld in each eye at the bedside or with formal visual perimetry. ree patients out of the 24 PCA patients examined by Andrade and colleagues40

CHAPTER 15 disorders of attentional processes 165

Fig. 15.4 Performance of a patient with probable AD on the copy of a landscape. Note the signs of left object-based neglect, similar to Patient 4 in Fig. 15.3.


Fig. 15.5 Performance of a PCA patient on the Bells test.58 e patient omitted three targets on the left side and one on the right side (red arrows). Note the false recognition on the left (green arrow) and the misreachings (blue arrows), perhaps depending on optic ataxia.

166 SECTION 2 cognitive dysfunction

missed all the le -sided stimuli, thus suggesting the presence of le homonymous hemianopia, which is a rare occurrence in neuro- degenerative diseases.74 Of the remaining patients, eight had le extinction and three showed mild right extinction.

Somatosensory extinction can be tested by asking the patient to close the eyes and report light touches given by the examiner on the patient’s limbs or face. To examine acoustic extinction, the exam- iner may lightly snap his/her ngers making a clicking sound near the patient’s ears.

In typical amnesic Alzheimer’s disease, general attentional de – cits can occur early along with memory de cits. Later in the course of the disease, neglect signs may appear.37,39 In some cases atten- tional de cits can precede the typical amnesic syndrome,75 espe- cially in the early-onset variant occurring before the age of 65.76 More speci cally, visuospatial attention de cits can have a central role in the impairment of higher-level cognitive processes concern- ing visual and spatial memory. As already mentioned, visuospa- tial neglect can represent the core symptom of clinical pro le of patients a ected by PCA (see Box 15.2, case 3). Even if less fre- quently, patients with CBS can also show signs of visuospatial neglect (see Box 15.3, case 4).44

Among the variety of tests used in clinical practice, line bisection might be more apt than target cancellation to demonstrate neg- lect in patients with neurodegenerative dementia, such as PCA,40 because performance on isolated horizontal lines is less prone to be in uenced by other concomitant de cits such as simultagnosia. In comparison with controls, PCA patients with signs of le -sided and right-sided neglect presented prominent hypoperfusion in right and le frontoparietal cortical networks, respectively.77 In another recent study, rightward bias (sign of le -sided neglect) in line bisec- tion test was strongly correlated with atrophy and hypoperfusion in a large-scale frontoparietal network in the right hemisphere, involving the parietotemporal cortex, the middle frontal gyrus, and in the postcentral region (Fig. 15.8).65

us, in these studies signs of neglect seemed to correlate with dysfunction in large-scale frontoparietal networks, beyond the sites

of parietal atrophy ((see reference 41, p. 4755 and p. 4752), consist- ent with evidence from patients with vascular lesions.28,78

Similar results on the task of line bisection were reported also in patients with classic AD.38 Obviously, in neurodegenerative patients, other aspects of the disease, such as simultagnosia and object recognition de cits, can interfere with patients’ performance on visual search tasks, such as target cancellation.


Simultagnosia is a rare neuropsychological condition character- ized by impaired spatial awareness of more than one object at time79 which can occur in patients with posterior brain damage of vascular or degenerative origin. Wolpert80 described simultagno- sia as an inability to interpret a complex visual scene (processing multiple items and the relations between them), despite preserva- tion of the ability to apprehend individual items. Simultagnosia can occur in isolation, or in association with other elements of Bálint’s syndrome (see below), that is, oculomotor apraxia and optic ataxia. Simultagnosia has been reported in patients with bilateral parietal and occipital damage.79 ere have also been some documented cases following either le or right unilateral parietal brain damage, but at least in some of these unilateral cases81,82 the lesions included damage to the corpus callosum. White matter tractography studies revealed associations with bilateral damage to major pathways within the visuospatial atten- tion network, including the superior longitudinal fasciculus, the inferior fronto-occipital fasciculus, and the inferior longitudinal fasciculus.83 us, simultagnosia typically occurs a er bilateral damage to parieto-occipital regions, o en associated with bilat- eral white matter disconnections.

Diagnostic tests

In clinical practice, simultanagnosia is assessed by the descrip- tion of complex visual scenes, such as the cookie the test.84 e tests consists of a complex image displaying a mother cleaning

Box 15.2 Patient 3: Unilateral spatial neglect and PCA-early onset AD variant (PCA-AD)

Patient 3 is a 58-year-old, right-handed medical doctor, who came to our observation a er about a year-and-a-half from disease onset, characterized by multiple minor car accidents against le -sided obstacles.

Clinical and neuropsychological examination revealed signs of severe le visual neglect (see Fig. 15.3), along with optic ataxia and ocular apraxia, as well as le ideomotor apraxia. ere was a moderate rightward deviation (19 per cent) on line bisection; her perfor- mance was pathological on the landscape drawing copy and on the clock-drawing test. She showed no auditory extinction, although she had some di culty to identify auditory stimuli presented on the le side. ere were rare le tactile extinctions on double stimulation. Mild memory impairment, especially with visuospatial material, and a very mild simultanagnosia were also present. Executive functions and calculation were relatively spared. Rare di culties in word nding and occasional phonologic paraphasias occurred.

Cerebrospinal uid analysis revealed positive AD biomarkers (raised tau and phosphorylated tau proteins, and reduced amyloid β peptide). High-resolution MRI demonstrated bilateral cortical atrophy mainly located in the parietal lobes, con rmed by a detailed analysis performed by using voxel-based morphometry (VBM) (Fig. 15.6a). In agreement with current clinical criteria (see reference 103) a diagnosis of PCA was made.

During a two-year follow-up, the neuropsychological pro le remained highly asymmetric with language and verbal memory largely preserved, while le visual neglect continued to represent the most severe symptom, and remained a substantial source of handicap in her everyday life.

A detailed anatomical study was conducted in order to study the grey and white matter status. VBM con rmed the bilateral posterior grey matter atrophy, including occipitotemporal and parietal cortices (Fig. 15.6a). Importantly, the tractography study of long-range white matter bres demonstrated white matter damage largely restricted to the right hemisphere, including the superior and inferior

multiple drawn objects are shown superimposed on each other. Patients are asked to name or indicate in a multiple-choice display all the objects seen, but may

In the overlapping gures test,
fail to identify most of them in case of simultagnosia.

CHAPTER 15 disorders of attentional processes 167

longitudinal fasciculi and the inferior fronto-occipital fasciculus, while the homologous le -hemisphere tracts were spared (Fig. 15.6b). ese data suggest that visuospatial de cits typical of PCA (such as neglect) may not result from cortical damage alone, but by a net- work-level dysfunction including white matter damage along the major large-scale pathways. e sparing of all the explored fasciculi in the le hemisphere, despite the cortical involvement of the occipital and parietal lobes, is consistent with the patient’s cognitive pro le, characterized by relatively intact language and calculation abilities.41



Inferior fronto-occipital fasciculus

Inferior longitudinal fasciculus

Superior longitudinal fasciculus

Corpus callosum




Fig. 15.6 PCA-AD patient 3. (a) Voxel-based morphometry as compared with a group of healthy controls. Regions of grey matter atrophy are shown in a colour code indicating the degree of atrophy, ranging from red (lower) to yellow (greater). Atrophy is displayed on the three-dimensional rendering of the Montreal Neurological Institute standard brain. (b) Long-range white matter tracts in the same patient, rendered as maps of fractional anisotropy (FA, an index of microstructural white matter integrity) displayed on the native T1-weighted MRI for both hemispheres. FA values range from 0.40 (yellow, greater damage) to 0.50 (red, lesser damage). In comparison to a group of healthy controls, maximum damage was found in the right frontoparietal superior longitudinal fasciculus. Inferior longitudinal fasciculus and inferior fronto-occipital fasciculus were also a ected in the right hemisphere. ere was also bres loss in the posterior part of corpus callosum. Left hemisphere tracts did not di er from controls. See Box 15.2 for more clinical details.

Reproduced from Cortex, 48(10), Migliaccio R, Agosta F, Toba MN, et al., Brain networks in posterior cortical atrophy: a single case tractography study and literature review, pp. 1298–309, Copyright (2012), with permission from Elsevier.

dishes in a kitchen, and not noticing that the sink is over owing and that a boy is about to fall while attempting to steal cookies behind her back. Patients with simultagnosia typically focus on one or two details of the scene, without being able to describe the others. 31,85

Bálint syndrome

Bálint syndrome is a rare neurovisual disorder characterized by three elements: optic ataxia, oculomotor apraxia, and simultag- nosia.79 In 1909, Rezső Bálint described with the name of ‘psy- chic paralysis of gaze’ the case of a patient who had lost the ability to voluntarily move his gaze from one point to xation to a new stimulus presented in the visual periphery.86 is disorder is also known under the name of oculomotor apraxia. Patients cannot take

FA values

168 SECTION 2 cognitive dysfunction

Box 15.3 Patient 4: Unilateral spatial neglect in PCA-CBD

Patient 4 is a 55-year-old woman, right-handed, was evaluated at about three years from clinical onset. She had a similar clinical history to patient 3; however, she deteriorated very rapidly in the visuospatial domain, while retaining almost normal performance in other cognitive domains. She mainly complained of visual de cit; her caregiver reported de cits occurring in everyday life and clearly result- ing from visuospatial neglect.

Clinical and cognitive evaluation demonstrated signs of le visual neglect (see Fig. 15.3, lower panel, and Fig. 15.5), consisting in a moderate (17 per cent) rightward deviation on visual line bisection, and pathological scores on landscape drawing copy and clock drawing test, with an object-based pattern of omissions. Optic ataxia, visual and auditory le extinctions, along with alexia, and ele- ments of Gerstmann syndrome (dysgraphia, nger agnosia, acalculia) were also present. She presented also constructional, ideomotor, and mielokinetic apraxia, with greater impairment for the execution of bimanual tasks and for the accurate movements and con gura- tions involving the ngers. Memory and language were relatively preserved. Executive functions were slightly impaired. At neurologi- cal examination she was hypomimic and with a mild right-lateralized rigidity. CSF analysis was negative for AD biomarkers (tau and phosphorylated tau proteins, and amyloid β peptide levels were within normal range). MRI showed greater brain atrophy located in the posterior regions bilaterally, and in the frontal areas (with right predominance) (Fig. 15.7). Based on clinical features, such as hypomimia and rigidity, as well as the presence of limb apraxia, a clinical diagnosis of corticobasal syndrome was proposed. A presynaptic dopamine transporter (DAT)-scan study demonstrated an asymmetric decrease of the uptake, with right side predominance, corresponding to the rigidity. is nding con rmed the in vivo diagnosis of corticobasal syndrome.



Fig. 15.7 Native high-resolution structural MRI of PCA-CBS patient 4. Note the bilateral posterior brain atrophy. ere was also mild right frontal atrophy (data not shown). See Box 15.3 for more clinical details.

their eyes o xed object (Holmes87 called this disorder ‘spasm of xation’), in order to produce saccades towards other objects. Slow tracking movements may instead be preserved. e other two ele- ments of Bálint syndrome are simultanagnosia (described in the previous paragraph) and optic ataxia—the inability to produce a correct movement of the hand to reach an object, typically presented in the periphery of visual eld, under visual guidance. Similar to simultanagnosia, the typical lesion locations in Bálint syndrome are parietal or parieto-occipital bilateral. e most common cause is vascular (watershed strokes between middle and posterior cerebral arteries territories), tumour metastasis, or neurodegeneration (e.g. PCA, CBD; see also Boxes 15.2 and 15.3). Regarding optic ataxia, lesions of the superior parietal lobule and to its connections with frontal areas (supplementary motor area and frontal eye elds) appear to play a key role.88

Diagnostic tests

Clinically, oculomotor apraxia can be assessed asking the patient, who is seated in front of the examiner, to move the eyes towards

Cerebral blood flow Grey matter density

–6 t scores 0

Fig. 15.8 Statistical parametric mapping results obtained in a sample of
15 patients with PCA, who underwent structural MRI and single photon emission computed tomography. e gure represents the regions of
signi cant correlation between grey matter atrophy (red), regional brain hypoperfusion (green) and rightwards deviations on the bisection of 20-cm long horizontal lines.

Reproduced from J Neurol Neurosur Ps. 83(9), Andrade K, Kas A, Valabrègue R, et al., Visuospatial de cits in posterior cortical atrophy: structural and functional correlates, pp. 860–3, Copyright (2012), with permission from BMJ Publishing Group Ltd.

a moving target a er having xated the examiner’s nose. e four visual quadrants are evaluated.89

To assess optic ataxia, the examiner asks the patient to xate his or her nose, then to use a designated hand (le or right) to reach a moving target (e.g. a pen) without losing xation. e examiner moves the target across the four visual quadrants.89

Attention and monitoring de cits

in vascular stroke and neurodegeneration

selective, sustained, and divided attention more severe than those found in AD patients. As a consequence, DLB patients typically perform better than AD patients on tests of verbal memory but worse on visuospatial performance tasks. Fluctuations in cognitive function—which may vary over minutes, hours, or days—occur in 50–75 per cent of patients and are associated with shi ing degrees of attention and alertness.102


Disorders of attention are common in neurodegenerative condi- tions. ese disorders o en go undetected by the clinician, but can have a severe impact on patients’ well-being and autonomy. ese patients who are not able to explore their visual environment thor- oughly can be far more handicapped in their daily life than patients with sensory de cits a ecting perception directly, but leaving atten- tion unimpaired, such as impaired visual acuity or homonymous hemianopia. us, the clinician should be aware of the variety of attention disorders which can occur in di erent neurodegenerative conditions, and of the (o en very easy) diagnostic tests that can be used to detect them.


The authors received funding from the Fondation ‘France Alzheimer’, Fondation ‘Philippe Chatrier’ and from the programme ‘Investissements d’Avenir’ ANR-10-IAIHU-06.


1. Di Ferdinando A, Parisi D, and Bartolomeo P. Modeling orienting behavior and its disorders with ‘ecological’ neural networks. J Cognitive Neurosc. 2007;19(6):1033–49.

2. Allport DA. Visual attention. In: Posner MI, editor. Foundations of Cognitive Science. Cambridge, MA: MIT Press, 1989, pp. 631–87.

3. Desimone R and Duncan J. Neural mechanisms of selective visual atten- tion. Annu Rev Neurosci. 1995;18:193–222.

4. Bartolomeo P. Attention Disorders a er Right Brain Damage: Living in Halved Worlds. London: Springer-Verlag, 2014.

5. Robertson IH and Garavan H. Vigilant Attention. In: Gazzaniga MS (ed.). e Cognitive Neurosciences, 3rd edn. Cambirdge, MA:MIT Press, 2004, pp. 563–78.

6. Silvetti M, Seurinck R, and Verguts T. Value and prediction error in medial frontal cortex: integrating the single-unit and systems levels of analysis. Front Hum Neurosci. 2011;5:75.

7. Brown JW. Beyond con ict monitoring: cognitive control and the neu- ral basis of thinking before you Act. Current Directions in Psychological Science. 2013 June 1, 2013;22(3):179–85.

8. Possin KL. Visual spatial cognition in neurodegenerative disease. Neurocase. 2010 Dec;16(6):466–87.

9. Buschman TJ and Miller EK. Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. Science. 2007 March 30, 2007;315(5820):1860–2.

10. Corbetta M and Shulman GL. Control of goal-directed and stimulus- driven attention in the brain. Nature Neurosci. 2002;3(3):201–15.
11. Singh-Curry V and Husain M. e functional role of the inferior par-

ietal lobe in the dorsal and ventral stream dichotomy. Neuropsychologia.

2009 May;47(6):1434–48.
12. Nobre AC, Sebestyen GN, Gitelman DR, et al. Functional localization of

the system for visuospatial attention using positron emission tomog-

raphy. Brain. 1997;120:515–33.
13. Bourgeois A, Chica AB, Valero-Cabré A, et al. Cortical control of inhib-

ition of return: Exploring the causal contributions of the le parietal cortex. Cortex. 2013.

Focusing attention in space and sustaining it in time, as well as monitoring behaviour, are o en considered to be mediated by cortical and subcortical frontal structures90–92 and by their con- nections with parietotemporal regions.4,11,16 Two principal neu- rodegenerative diseases can show de cits in these cognitive domains: AD and frontotemporal dementia (FTD, particularly behavioural-variant FTD).

Many clinical and cognitive studies have compared attention and monitoring in AD and FTD. Based on di erent patterns of neuro- degeneration, peculiar general clinical and cognitive pro les have been described. Early memory impairment and following language, praxis, and visuospatial de cits are typically described in AD. In AD, the trajectory of the damage includes the hippocampal and perihip- pocampal regions, where the neurodegeneration originates causing memory failure, to the more posterior associative temporoparietal areas. Conversely, early changes in social conduct, insight, a ect- ive behaviour, along with impaired initiative, verbal uency, atten- tion, planning, set-shi ing, problem-solving, and working memory depend on pathological changes in the orbitofrontal and dorsolateral prefrontal cortex, characteristically a ected in patients with FTD.93

Notwithstanding their profound biological, anatomical, and cognitive di erences, AD and FTD can have similar consequences in executive function. Executive de cits re ect an impaired inte- gration of the frontal lobes with di erent brain areas, and in par- ticular with more posterior brain regions. ese functional and anatomical connections are damaged in both AD and FTD, thus perhaps accounting for their similarity in this speci c domain. For this reason, it might prove di cult to di erentiate, on the basis of these functions, patients with FTD and AD, particularly when AD patients are younger and atypical.

From the functional point of view, several large-scale brain net- works, described as being dysfunctional in AD and FTD, are impli- cated in attention and monitoring behaviour, such as networks implicated in salience processing,94 executive processes,95 attention/

working memory processes, as well as the dorsal attentional net-

work.97 ese functional networks are mainly impaired in FTD98 and may represent a pathophysiological signature of this disease.

Little is known on the potential occurrence of visuospatial atten- tion de cits in FTD, although patients with vascular stroke in the frontal lobes can sometimes demonstrate signs of spatial neglect.99 Note, however, that frontal lobe neglect is typically observed a er


Patients with DLB can show much more substantial de cits of attention. ey can demonstrate a combination of severe atten- tional de cits and visuospatial dysfunction that can help to di er- entiate DLB from AD. DLB patients usually su er from de cits in

lateral frontal damage,
tional networks see Fig. 15.1), whereas in the behavioural variant of FTD, the atrophy a ects rst and foremost the frontomedian brain regions, the anterior insula, and the thalamus.101

(i.e. in the prefrontal nodes of the atten-

CHAPTER 15 disorders of attentional processes 169

170 SECTION 2 cognitive dysfunction

14. Petrides M and Pandya DN. Projections to the frontal cortex from the posterior parietal region in the rhesus monkey. J Comp Neurol. 1984 Sep 1;228(1):105–16.

15. Schmahmann JD and Pandya DN. Fiber Pathways of the Brain. New York, NY: Oxford University Press, 2006.

16. iebaut de Schotten M, Dell’Acqua F, et al. A lateralized brain network for visuospatial attention. Nature Neurosci. 2011 Sep 18;14(10):1245–6.

17. Bowers D and Heilman KM. Pseudoneglect: E ects of hemispace on a tactile line bisection task. Neuropsychologia. 1980;18:491–8.

18. Jewell G and McCourt ME. Pseudoneglect: a review and meta-analysis of performance factors in line bisection tasks. Neuropsychologia. 2000;38(1):93–110.

19. Toba MN, Cavanagh P, and Bartolomeo P. Attention biases the perceived midpoint of horizontal lines. Neuropsychologia. 2011;49(2):238–346.

20. Husain M and Nachev P. Space and the parietal cortex. Trends Cognit Sci. 2007 Jan;11(1):30–66.

21. Mishkin M, Ungerleider LG, and Macko KA. Object vision and spatial vision: Two cortical pathways. Trends Neurosci. 1983;6:414–7.

22. Goodale MA and Milner AD. Separate visual pathways for perception and action. Trends Neurosci. 1992 Jan;15(1):20–5.

23. Catani M, Jones DK, Donato R, et al. Occipito-temporal connections in the human brain. Brain. 2003 Sep;126(Pt 9):2093–107.

24. ytche DH and Blom JD, Catani M. Disorders of visual perception. J Neurol Neurosur Ps. 2010 Oct 22;81(11):1280–7.

25. Seeley WW, Crawford RK, Zhou J, et al. Neurodegenerative dis- eases target large-scale human brain networks. Neuron. 2009 Apr 16;62(1):42–52.

26. Migliaccio R, Agosta F, Scola E, Magnani G, Cappa SF, Pagani E, et al. Ventral and dorsal visual streams in posterior cortical atrophy: a DT MRI study. Neurobiol Aging. 2012 Nov;33(11):2572–84.

27. Bartolomeo P. A parieto-frontal network for spatial awareness in the right hemisphere of the human brain. Archives of Neurology. 2006;63:1238–41.

28. Bartolomeo P, iebaut de Schotten M, et al. Le unilateral neglect as a disconnection syndrome. Cereb Cortex. 2007;45(14):3127–48.

29. Parton A, Malhotra P, and Husain M. Hemispatial neglect. J Neurol Neurosur Ps. 2004;75(1):13–21.

30. Azouvi P, Bartolomeo P, Beis J-M, et al. A battery of tests for the quan- titative assessment of unilateral neglect. Restorative Neurology and Neuroscience. 2006;24(4–6):273–85.

31. Gainotti G, D’Erme P, and Bartolomeo P. Early orientation of attention toward the half space ipsilateral to the lesion in patients with unilateral brain damage. J Neurol Neurosur Ps. 1991;54:1082–9.

32. Beis JM, Keller C, Morin N, et al. Right spatial neglect a er le hemi- sphere stroke: Qualitative and Quantitative Study. Neurology. 2004 11 9;63(9):1600–5.

33. Bartolomeo P, Chokron S, and Gainotti G. Laterally directed arm movements and right unilateral neglect a er le hemisphere damage. Neuropsychologia. 2001;39(10):1013–21.

34. Luaute J, Halligan P, Rode G, et al. Visuo-spatial neglect: a system- atic review of current interventions and their e ectiveness. Neurosci Biobehav Rev. 2006;30(7):961–82.

35. Gorgoraptis N, Mah YH, Machner B, et al. e e ects of the dopa- mine agonist rotigotine on hemispatial neglect following stroke. Brain. 2012 Jul 2.

36. Mendez MF, Cherrier MM, and Cymerman JS. Hemispatial neglect on visual search tasks in Alzheimer’s disease. Neuropsy Neuropsy Be. 1997;10:203–8.

37. Bartolomeo P, Dalla Barba G, Boissé MT, et al. Right-side neglect in Alzheimer’s disease. Neurology. 1998;51(4):1207–9.

38. Ishiai S, Koyama Y, Seki K, et al. Unilateral spatial neglect in AD: signi – cance of line bisection performance. Neurology. 2000 Aug 8;55(3):364–70.

39. Venneri A, Pentore R, Cotticelli B, et al. Unilateral spatial neglect in the
late stage of Alzheimer’s disease. Cortex. 1998;34(5):743–52.

40. Andrade K, Samri D, Sarazin M, et al. Visual neglect in posterior corti-

41. Migliaccio R, Agosta F, Toba MN, Saet al. Brain networks in posterior cortical atrophy: A single case tractography study and literature review. Cortex. 2012 Nov;48(10):1298–309.

42. Bartolomeo P and Chokron S. Levels of impairment in unilateral neg- lect. In: F Boller and J Grafman J (eds). Handbook of Neuropsychology. 2nd edn. Amsterdam: Elsevier Science Publishers, 2001, pp. 67–98.

43. Halligan PW and Bartolomeo P. Visual neglect. In: Ramachandran V (ed.). Encyclopedia of Human Behavior, 2nd edn. 2012, pp. 652–64. 44. Silveri MC, Ciccarelli N, and Cappa A. Unilateral spatial neglect in

degenerative brain pathology. Neuropsychology. 2011;25(5):554–66.
45. Parasuraman R, Greenwood PM, Haxby JV, et al. Visuospatial attention

dementia of the Alzheimer type. Brain. 1992;115 (Pt 3):711–33.
46. Balota DA and Faust ME. Attention in dementia of the Alzheimer’s

type. In: F Boller and J Grafman (eds). Handbook of Neuropsychology.

2nd edn. Amsterdam: Elsevier Science Publishers, 2001, pp. 51–80. 47. Danckert J, Maru P, Crowe S, et al. Inhibitory processes in covert

orienting in patients with Alzheimer’s disease. Neuropsychology.

48. Wright MJ, Burns RJ, Ge en GM, and Ge en LB. Covert orientation of

visual attention in Parkinson’s disease: an impairment in the mainte-

nance of attention. Neuropsychologia. 1990;28(2):151–9.
49. Cristinzio C, Bononi M, Piacentini S, et al. Attentional networks in

Parkinson’s disease. Behavioural Neurology. 2013;27(4):495–500. 50. Couette M, Bachoud-Lévi AC, Brugières P, et al Orienting of

spatial attention in Huntington’s Disease. Neuropsychologia.

51. Georgiou-Karistianis N, Farrow M, Wilson-Ching M, et al. De cits

in selective attention in symptomatic Huntington disease: assess- ment using an attentional blink paradigm. Cogn Behav Neurol. 2012 Mar;25(1):1–6.

52. Rafal RD, Posner MI, Friedman JH, et al. Orienting of visual attention in progressive supranuclear palsy. Brain. 1988;111(Pt 2):267–80.

53. Gainotti G, Messerli P, and Tissot R. Qualitative analysis of unilateral spatial neglect in relation to the laterality of cerebral lesions. J Neurol Neurosur Ps. 1972;35:545–50.

54. Marshall JC and Halligan PW. Visuo-spatial neglect: a new copying test to assess perceptual parsing. J Neurol. 1993;240(1):37–40.

55. Walker R. Spatial and object-based neglect. Neurocase. 1995;1:371–83. 56. Albert ML. A simple test of visual neglect. Neurology. 1973;23:658–64. 57. Mesulam MM. Attention, confusional states and neglect. In: MM

Mesulam (ed.). Principles of Behavioral Neurology. Philadelphia,

PA: F.A. Davis, 1985, pp. 125–68.
58. Gauthier L, Dehaut F, and Joanette Y. e bells test: A quantitative and

qualitative test for visual neglect. Int J Clin Neuropsych. 1989;11:49–53. 59. Halligan PW, Cockburn J, and Wilson B. e behavioural assessment of

visual neglect. Neuropsychological Rehabilitation. 1991;1:5–32.
60. Bartolomeo P, D’Erme P, and Gainotti G. e relationship between

visuospatial and representational neglect. Neurology. 1994;44:1710–4. 61. Schenkenberg T, Bradford DC, and Ajax ET. Line bisection and unilat-

eral visual neglect in patients with neurologic impairment. Neurology.

62. Marshall JC and Halligan PW. When right goes le : An investigation of

line bisection in a case of visual neglect. Cortex. 1989;25(3):503–15. 63. Heilman KM and Valenstein E. Mechanisms underlying hemispatial

neglect. Ann Neurol. 1979;5:166–70.
64. Binder J, Marshall R, Lazar R, et al. Distinct syndromes of hemineglect.

Arch Neurol–Chicago. 1992;49(11):1187–94.
65. Andrade K, Kas A, Valabrègue R, et al. Visuospatial de cits in posterior

cortical atrophy: structural and functional correlates. J Neurol Neurosur

Ps. 2012;83(9):860–3.
66. Vuilleumier PO and Rafal RD. A systematic study of visual extinction.

Between- and within- eld de cits of attention in hemispatial neglect.

Brain. 2000 Jun;123 (Pt 6):1263–79.
67. Bartolomeo P, Perri R, and Gainotti G. e in uence of limb crossing

on le tactile extinction. J Neurol Neurosur Ps. 2004;75(1):49–55.
68. De Renzi E, Gentilini M, and Pattacini F. Auditory extinction following

cal atrophy. BMC Neurology. 2010;10:68.

hemisphere damage. Neuropsychologia. 1984;22(6):733–44.

69. Bellas DN, Novelly RA, Eskenazi B, et al. e nature of unilat- eral neglect in the olfactory sensory system. Neuropsychologia. 1988;26(1):45–52.

70. Mattingley JB, Driver J, Beschin N, et al. Attentional competition between modalities: extinction between touch and vision a er right hemisphere damage. Neuropsychologia. 1997;35(6):867–80.

71. Bender MB. Disorders in Perception. Spring eld, Ill.: omas, 1952.

72. Critchley M. e Parietal Lobes. New York: Hafner, 1953.

73. Marzi CA, Girelli M, Natale E, et al. What exactly is extinguished
in unilateral visual extinction? Neurophysiological evidence.
Neuropsychologia. 2001;39(12):1354–66.

74. Oda H, Ohkawa S, and Maeda K. Hemispatial visual defect in
Alzheimer’s disease. Neurocase. 2008;14(2):141–6.

75. D’Erme P, Bartolomeo P, and Masullo C. Alzheimer’s disease
presenting with visuo-spatial disorders. Ital J Neurol Sci. 1991

76. Frisoni GB, Pievani M, Testa C, et al. e topography of grey mat-
ter involvement in early and late onset Alzheimer’s disease. Brain.
2007;130(Pt 3):720–30.

77. Andrade K, Kas A, Samri D, et al. Visuospatial de cits and hemi-
spheric perfusion asymmetries in posterior cortical atrophy. Cortex.

78. Doricchi F, iebaut de Schotten M, et al. White matter (dis)connections
and gray matter (dys)functions in visual neglect: Gaining insights into
the brain networks of spatial awareness. Cortex. 2008;44(8):983–95.

79. Rizzo M and Vecera SP. Psychoanatomical substrates of Balint’s syn-
drome. J Neurol Neurosur Ps. 2002 Feb;72(2):162–78.

80. Wolpert I. Die Simultanagnosie: Störung der
Gesamtau assung. Zeitschri für die gesamte Neurologie und Psychiatrie.

81. Clavagnier S, Fruhmann Berger M, Klockgether T, et al. Restricted
ocular exploration does not seem to explain simultanagnosia.
Neuropsychologia. 2006;44(12):2330–6.

82. Naccache L, Slachevsky A, Levy R, et al. Simultanagnosia in a patient
with right brain lesions. J Neurol. 2000;247(8):650–1.

83. Chechlacz M, Rotshtein P, Hansen PC, et al e neural underpinings
of simultanagnosia: disconnecting the visuospatial attention network.
J Cogn Neurosci. 2012;24(3):718–35.

84. Goodglass H and Kaplan E. e Assessment of Aphasia and Related
Disorders. Philadelphia: Lea & Febiger, 1983.

85. Poppelreuter W. Die psychischen Schädigungen durch Kopfschuss im
Kriege 1914-1916. Leipzig: Voss, 1917.

86. Husain M and Stein J. Rezsö Bálint and his most celebrated case. Arch
Neurol. 1988;45(1):89–93.

87. Holmes G. Spasm of xation. Trans Ophthalmol Soc UK.

88. Pisella L, Ota H, Vighetto A, et al. Optic ataxia and Bálint’s syndrome: neuropsychological and neurophysiological prospects. In: PJ Vinken and GW Bruyn (eds). Handbook of Clinical Neurology. Amsterdam: Elsevier, 2008, pp. 393–415.

89. Kas A, de Souza LC, Samri D, et al. Neural correlates of cogni- tive impairment in posterior cortical atrophy. Brain. 2011;134(Pt 5):1464–78.

90. Duncan J. e structure of cognition: attentional episodes in mind and brain. Neuron. 2013;80(1):35–50.

91. Fuster JM. e Prefrontal Cortex: Anatomy, Physiology and Neuropsychology of the Frontal Lobe. 3rd edn. Philadelphia, PA: Lippincott-Raven, 1997.

92. Miller EK. e prefrontal cortex and cognitive control. Nature Neurosci. 2000;1(1):59.

93. Rosen HJ, Gorno-Tempini ML, Goldman WP, et al. Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology. 2002 Jan 22;58(2):198–208.

94. Seeley WW, Menon V, Schatzberg AF, et al. Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci. 2007 Feb 28;27(9):2349–56.

95. Seeley WW, Crawford R, Rascovsky K, et al. Frontal paralimbic network atrophy in very mild behavioral variant frontotemporal dementia. Arch Neurol. 2008 Feb;65(2):249–55.

96. Damoiseaux JS, Rombouts SA, Barkhof F, et al. Consistent resting- state networks across healthy subjects. Proc Natl Acad Sci USA. 2006 Sep 12;103(37):13848–53.

97. Fox MD, Corbetta M, Snyder AZ, et al. Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proc Natl Acad Sci USA. 2006 June 27, 2006;103(26):10046–51.

98. Filippi M, Agosta F, Scola E, et al. Functional network connectivity in the behavioral variant of frontotemporal dementia. Cortex. 2012 Oct 24.

99. Husain M and Kennard C. Visual neglect associated with frontal lobe infarction. J Neurol. 1996 Sep;243(9):652–7.

100. Vallar G. Extrapersonal visual unilateral spatial neglect and its neuro- anatomy. Neuroimage. 2001;14(1 Pt 2):S52–S8.

101. Schroeter ML, Raczka K, Neumann J, et al. Neural networks in frontotemporal dementia—A meta-analysis. Neurobiol Aging. 2008;29(3):418–26.

102. McKeith I, Mintzer J, Aarsland D, et al. Dementia with Lewy bodies. Lancet Neurol. 2004;3(1):19–28.

103. Migliaccio R, Agosta F, Rascovsky K, et al. Clinical syndromes associated with posterior atrophy: early age at onset AD spectrum. Neurology. 2009 Nov 10;73(19):1571–8.

104. Corbetta M, Kincade JM, and Shulman GL. Neural systems for visual orienting and their relationships to spatial working memory. J Cogn Neurosci. 2002 Apr 1;14(3):508–23.

CHAPTER 15 disorders of attentional processes 171



Georg Goldenberg

Concepts and classi cation of apraxia De nition of apraxia

e term apraxia refers to ‘higher-level’ disorders of motor con- trol. ere is, however, no general agreement as to what counts as a high or a low level of motor control. Most agree though that apraxia should not be used to describe di culties that might be attributed entirely to weakness, or loss of sensation, rigidity, tremor, or dysto- nia. However, this would be a diagnosis of exclusion. Moreover, in many neurological conditions apraxia can occur in the context of one or more of these de cits. Consequently, the history of apraxia has brought forward a wide variety of diverging de nitions and classi cations (Box 16.1).

e most in uential of them was proposed some hundred years ago by the German psychiatrist Hugo Liepmann.1,2 He distin- guished two consecutive phases of voluntary motor action. e rst is the creation of mental images of the intended actions, and the second their transduction into appropriate motor commands. Liepmann named disturbances of the rst phase ‘ideational’ and that of the second phase ‘ideo-kinetic’ apraxia, which later authors re-baptized as ideomotor apraxia,2,3 a distinction that still remains

in widespread use (but see Box 16.1 for discussion of the utility of this distinction).

Although ‘apraxia’ has been applied to disturbances of widely dif- ferent actions (e.g. lid closure, gait, gestures, or even spatial con- structions), there is a core of clinical manifestations a ecting limb function which have been the focus of the concept. ey include:

◆ imitation of gestures
◆ communicative gestures on command and pantomime of tool use ◆ use of tools and objects

De cits in all of these occur predominantly a er le brain lesions and are frequently, though not invariably, associated with aphasia. In contrast to ‘low-level’ motor symptoms associated with unilat- eral hemispheric damage, they a ect not only the contralesional limb (on the side of the body opposite to the cerebral lesion) but also the ipsilesional limb. In sections below, we examine each of these domains and how to examine for de cits in patients. In addi- tion, we consider a particular aspect of tool and object use that involves:

◆ Multi-step actions involving several tools and objects

Box 16.1 Development of concepts of apraxia

Based on the associationist model of brain function prevalent at that time, Liepmann assumed that mental images emerge from revival of memory traces of previous sensations. He speculated that their translation into motor commands was accomplished by bres that connect posterior sensory brain regions to the motor cortex in the anterior part of the brain. ese bres pass below the parietal cortex. Parietal lesions interrupt them and to cause ‘ideo-kinetic’ (now known as ideo-motor) apraxia.4,5

In the middle of the twentiethth century, when the localizing approach to mental function gave way to more functional and holistic theories, Liepmann’s anatomical distinction between ideational and ideomotor apraxia fell into disfavour and was replaced by other sys- tems of classi cation. Noteworthy, all of them retained some kind of dichotomy between high and low levels of motor controls. us, for example, they considered as opposites: autonomous action versus. environmental dependency; coping with novelty versus routine action, and abstract symbolic gestures versus material interactions with concrete objects (see references 6, 7, 8, and reference 9 for extensive historical review).

In the last third of the twentieth century, the renaissance of cerebral localization of mental function revamped Liepmann’s ideas, which have strongly in uenced modern accounts of apraxia and its cerebral localization.10–14

Ideomotor and ideational apraxia

Liepmann reasoned that in actual tool use, the interaction between the moving hand and external objects can compensate for an inability to direct movements that might arise because of a failure to transduce mental images into appropriate motor commands. In such cases, the de cit should be conspicuously apparent when actions have to be made without external counterpart. According to this reasoning ideomo- tor apraxia should a ect imitation and the demonstration of communicative gestures but spare actual use of tools and objects.1 Most modern authors who respect the traditional classi cation of apraxia adhere to this suggestion and apply the label ‘ideomotor’ to defective imita- tion as well as defective demonstration of communicative gestures, or compute compound scores from both for a diagnosis of ideomotor apraxia.15–22

174 SECTION 2 cognitive dysfunction

However, the unity of imitation and demonstration of communicative gestures has been challenged by double dissociations between them. ere are patients who are unable to correctly demonstrate communicative gestures but imitate awlessly.23 and others who have no problems with the demonstration of communicative gestures but commit many errors on imitation.24–27 eir common classi cation as ‘ideomotor’ apraxia is misleading because it veils fundamental di erences.

Most authors agree to apply the term ‘ideational apraxia’ for faulty use of tools and objects but there is disagreement about the scope and nature of these errors. Liepmann had adopted the description of this variant of apraxia from the Prague psychiatrist, Arnold Pick.28 who had reported gross errors in everyday multi-step actions like dressing or preparing a pipe by patients with dementia. Pick argued that most errors could be referred to perseveration and to neglect of the overarching goal of the multi-step sequence, rather than betray- ing problems that are speci c for tool use. Liepmann agreed that ideational apraxia is the expression of a ‘mental insu ciency which manifests itself in the domain of action but has its roots in de cits which are not speci c for action’.29

By contrast, an alternative tradition originating with a seminal thesis of the French neurologist, Joseph Morlaas,30 postulates that idea- tional apraxia can occur in patients without dementia and that it a ects also the isolated use of single tools. Morlaas suggested the term ‘agnosia of utilization’ to characterize the selective inability to recognize the way an object has to be used.30,31

In sum, the distinction between ‘ideational’ and ‘ideomotor’ does not correspond well with the clinical boundaries between dif- ferent manifestations of apraxia and is confusing. It seems more productive to abandon it and to divide apraxia according to the a ected domain of action. ere are four of them: imitation of gestures, production of communicative gestures, use of single tools, and multi-step actions involving several tools and objects. eir autonomy is underlined by di erences between the localizations of lesions interfering with each of them (Fig. 16.1).

Pantomime of tool use

Imitation of meaningless gestures

Use of single familiar tools

Hand postures Finger postures

Mechanical Problem Solving

Functional Knowledge

Fig. 16.1 Putative intra-hemispheric localization of left-sided lesions causing di erent manifestations of apraxia. Imitation of meaningless hand postures and mechanical problem solving depend on integrity of parietal region. By contrast, pantomime of tool use and retrieval of functional knowledge are vulnerable to temporal lesions. Imitation of nger con guration as well as performance of multi-step actions with multiple tools and objects are less strictly localized and can be impaired also by right hemisphere lesions.

Adapted from Goldenberg G. Neuropsychologie—Grundlagen, Klinik, Rehabilitation, Copyright (2007), with permission from Elsevier GmbH, Urban & Fischer, Munich.

Imitation of gestures

Success or failure of imitation of gestures may depend on the kind of gestures that are examined. A major distinction is that between meaningless and meaningful gestures (the meaning of meaningful gestures can be understood by other persons, thus they are, by def- inition, communicative, and I use the terms ‘communicative’ and ‘meaningful’ interchangeably).23,32–34 is distinction derives from the fact that meaningful gestures have representations in semantic memory that associate their shapes with de ned meanings. eir imitation may be accomplished by recognition of that meaning and reproduction of the corresponding shape. By contrast, the imita- tion of meaningless gestures requires reproduction of the shape of the gesture without support from semantic memory. Another factor

in uencing the success of imitation is whether single static postures or movement sequences are examined. Generally, sequences are more sensitive to brain damage but also less speci c for its localiza- tion.35–37 Here, we concentrate on the imitation of static meaning- less gestures (Fig. 16.2).

Clinical diagnosis

Defective imitation will rarely be conspicuous in spontaneous behaviour but can easily be demonstrated on clinical examination. Even patients with severe aphasia mostly understand the instruc- tion to imitate the examiner’s actions. As with all manifestations of apraxia, the limb ipsilateral to the lesion should be tested to exclude contamination of results by the e ects of hemiparesis. Many

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clinicians ask patients to start their imitation only immediately a er they have demonstrated the gesture. is brief delay introduces a working memory load that probably contributes to uncover- ing mild impairments. But patients with severe apraxia will show de cits even if the examiner’s posture is still visible to them. e most reliable sign for the diagnosis of apraxia are spatially wrong nal positions. Frequently, the movement path leading to the nal position is hesitating with searching and self-correction, but there are apraxic patients who reach wrong nal postures with swi and secure movements.38

Localization of lesions

It has been suggested that creation of this abstract representa- tion relies on ‘body-part coding’ that enables reduction of gestures to simple spatial relationships between a limited number of de ned body parts.40,48,49 e body-part speci city of the neural substrates of defective imitation can be accounted for by the assumption that body-part coding is bound to integrity of le parietal regions, but that frontal, subcortical, and right hemisphere regions are required when gestures pose high demands on the distribution of spatial attention or on selection between perceptually highly confusable items. Di erential demands of hand, nger, and footpostures on body-part coding, attention, and selection might explain why di erent regions are cru- cial for their successful imitation.39,44,50,51 e discrepancy between the associations of responsible brain lesions with body parts and the somatotopic organization of motor cortex further underlines the inde- pendence of apraxia from the anatomy of ‘low-level’ motor control.

Communicative gestures and pantomime

of tool use

e clinical examination of communicative gestures probes ges- tures that have a habitual shape and meaning, allowing unam- biguous assessment of their correctness. Gestures that ful l this condition are either ‘emblems’ that have a conventional meaning like thumb up for ‘OK’, or pantomimes of tool use that indicate objects by miming their use. Usually, diagnosis and research on apraxia concentrates on pantomime of tool use. A practical reason for this preference is that aphasic patients may not understand the verbal label of emblems, whereas comprehension of the name of a tool whose use they should demonstrate can be facilitated by show- ing the tool or a picture of it.

Clinical diagnosis

In clinical practice, a patient is asked by the examiner to demon- strate how he would make a common gesture (‘emblem’) or use a common tool. Comprehension of the instruction may pose prob- lems when examining patients with severe aphasia, even if the tool whose use should be pantomimed is pointed to or shown on a photo. Failure of comprehension is rather obvious when patients grasp for the demonstrated object, try to name or describe it,52 or outline with the nger a more or less recognizable shape on the table.

e typical locations of lesions causing defective imitation depend on the body part performing it. Fig. 16.2 displays static postures of the nger, the hand, and the foot that have been used for assess- ing this body-part speci city.39–41 Whereas defective imitation of hand postures is nearly exclusively bound to le hemisphere lesions, imitation of nger and foot postures is also susceptible to right hemisphere lesions.39,42–44 Within the le hemisphere, defect- ive imitation of hand postures is strongly linked to parietal lobe damage whereas defective imitation of nger postures can also be caused by frontal and subcortical lesions.40,41,45–47

eoretical implications

e route from perception to imitation of meaningless gestures i