0521896223 cambridge university press principles and practice of lifespan developmental neuropsychology mar 2010

Levin 345 11e Traumatic brain injury across the lifespan: a long-term developmental perspective Jacobus Donders 357 12a Pediatric aspects of epilepsy Lindsey Felix and Scott J.. Section

Principles and Practice of Lifespan Developmental Neuropsychology

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Contact information for authors pagevii

Biography for Jacobus Donders and Scott J Hunter xi

Introduction

Jacobus Donders and Scott J Hunter 1

Section I: Theory and models 3

1 A lifespan review of developmental

neuroanatomy

John Williamson 3

2a Developmental models in pediatric

neuropsychology

Jane Holmes Bernstein 17

2b Models of developmental neuropsychology:

adult and geriatric

Tyler J Story and Deborah K Attix 41

3 Multicultural considerations in lifespan

neuropsychological assessment

Thomas Farmer and Clemente Vega 55

4 Structural and functional neuroimaging

throughout the lifespan

Brenna C McDonald and Andrew J Saykin 69

Section II: Disorders 83

5a Attention deficit hyperactivity disorder

in children and adolescents

David Marks, Joey Trampush and Anil Chacko 83

5b Attention deficit hyperactivity disorder

6a Learning disorders in children and adolescents

Gregory M Stasi and Lori G Tall 127

6b Learning disorders in adults

Elizabeth P Sparrow 143

6c Synthesis of chapters on learning disabilities:overview and additional perspectives

H Lee Swanson 1637a Infants and children with spina bifidaHeather B Taylor, Susan H Landry, LianneEnglish and Marcia Barnes 169

7b Adolescence and emerging adulthood inindividuals with spina bifida: a developmentalneuropsychological perspective

Kathy Zebracki, Michael Zaccariello, FrankZelko and Grayson N Holmbeck 1837c Spina bifida/myelomeningocele andhydrocephalus across the lifespan:

a developmental synthesisIlana Gonik, Scott J Hunter and JamilaCunningham 195

8 Cerebral palsy across the lifespanSeth Warchausky, Desiree White and MarieVan Tubbergen 205

9a Intellectual disability across the lifespanBonnie Klein-Tasman and Kelly Janke 2219b Lifespan aspects of PDD/autism spectrumdisorders (ASD)

Julie M Wolf and Sarah J Paterson 2399c Autism spectrum disorders and intellectualdisability: common themes and points

of divergenceMarianne Barton, Colby Chlebowski andDeborah Fein 251

10a Hearing loss across the lifespan:

neuropsychological perspectivesBetsy Kammerer, Amy Szarkowski and PeterIsquith 257

10b Visual impairment across the lifespan:

neuropsychological perspectivesLisa M Noll and Lana L Harder 277

11a Traumatic brain injury in childhood

Michael W Kirkwood, Keith Owen Yeates and

Jane Holmes Bernstein 299

11b Adult outcomes of pediatric traumatic

brain injury

Miriam Beauchamp, Julian Dooley and Vicki

Anderson 315

11c Neurobehavioral aspects of traumatic brain

injury sustained in adulthood

Tresa Roebuck-Spencer, James Baños, Mark

Sherer and Thomas Novack 329

11d Traumatic brain injury in older

adults

Felicia C Goldstein and Harvey

S Levin 345

11e Traumatic brain injury across the

lifespan: a long-term developmental

perspective

Jacobus Donders 357

12a Pediatric aspects of epilepsy

Lindsey Felix and Scott J Hunter 359

12b A lifespan perspective of cognition in

epilepsy

Michael Seidenberg and Bruce Hermann 371

13a Leukemia and lymphoma across the lifespan

Kevin R Krull and Neelam Jain 379

13b Lifespan aspects of brain tumorsCeliane Rey-Casserly 393

14 Lifespan aspects of endocrine disordersGeoffrey Tremont, Jennifer Duncan Davis andChristine Trask 409

15 Metabolic and neurodegenerative disordersacross the lifespan

Richard Ziegler and Elsa Shapiro 42716a Psychopathological conditions in childrenand adolescents

Abigail B Sivan 44916b Psychopathological conditions in adultsAnthony C Ruocco, Elizabeth Kunchandyand Maureen Lacy 455

16c Neuropsychological aspects ofpsychopathology across the lifespan:

a synthesisAlexandra Zagoloff and Scott J Hunter 469

The color plates are to be found between pp.276

and277

vi

Contact information for authors

Vicki Anderson, Ph.D

Department of Psychology

Royal Children’s Hospital

Parkville, Victoria, Australia

Deborah K Attix, Ph.D

Department of Psychiatry and Behavioral Sciences

Duke University Medical Center

Durham, NC

James Baños, Ph.D., ABPP-Cn

Department of Physical Medicine & Rehabilitation

University of Alabama, Birmingham

Birmingham, AL

Marcia Barnes, Ph.D

Children’s Learning Institute

University of Texas Health Science Center at Houston

Royal Children’s Hospital

Parkville, Victoria, Australia

Colby Chlebowski, M.A

Department of PsychologyUniversity of ConnecticutStorrs, CT

Jamila Cunningham, M.A

Department of PsychologyLoyola University

Chicago, ILJennifer Duncan Davis, Ph.D

Department of Psychiatry and Human BehaviorWarren Alpert School of Medicine of Brown UniversityProvidence, RI

Jacobus Donders, Ph.D

Department of PsychologyMary Free Bed Rehabilitation HospitalGrand Rapids, MI

Julian Dooley, Ph.D

Murdoch Childrens Research InstituteMelbourne, Australia

Lianne EnglishDepartment of PsychologyUniversity of GuelphGuelph, Ontario, CanadaThomas Farmer, Psy.D

The Chicago School of Professional PsychologyChicago, IL

Deborah Fein, Ph.D

Department of PsychologyUniversity of ConnecticutStorrs, CT

Lindsey Felix, Ph.D

Alexian BrothersNeuroscience InstituteChicago, IL

Jodene Goldenring Fine, Ph.D.

Emory University School of Medicine and Wesley

Woods Center on Aging

University of Texas Southwestern Medical School

Children’s Medical Centre

Department of Epidemiology and Cancer Control

St Jude Children’s Research Hospital

Department of Physical Medicine & RehabilitationThe Children’s Hospital

Aurora, COBonnie Klein-Tasman, Ph.D

Department of PsychologyUniversity of Wisconsin, MilwaukeeMilwaukee, WI

Department of PsychiatryUniversity of ChicagoChicago, IL

Baylor College of MedicineHouston, TX

David Marks, Ph.D

Department of PsychiatryMount Sinai Medical CenterNew York, NY

Brenna C McDonald, PsyDDepartments of Radiology and NeurologyIndiana University School of MedicineIndianapolis, IN

viii

Lisa M Noll, Ph.D.

Learning Support Center for Child Psychology

Texas Children’s Hospital

Houston, TX

Thomas Novack, Ph.D

Department of Physical Medicine & Rehabilitation

University of Alabama, Birmingham

Andrew J Saykin, PsyD

Departments of Radiology, Neurology, and Psychiatry

Indiana University School of Medicine

Departments of Psychology & Psychiatry

Michigan State University

East Lansing, MI

Elsa Shapiro, Ph.D

Pediatric Clinical Neuroscience

University of Minnesota Medical Center

Minneapolis, MN

Mark Sherer, Ph.D., ABPP-Cn

TIRR Memorial Hermann

Baylor College of Medicine

Elizabeth P Sparrow, Ph.D

Sparrow Neuropsychology, P.A

Durham, NCGregory M Stasi, Ph.D

Rush Neurobehavioral CenterSkokie, IL

Tyler J Story, Ph.D

Division of NeurologyDuke University Medical CenterDurham, NC

H Lee Swanson, Ph.D

Graduate School of EducationUniversity of California-RiversideRiverside, CA

Amy Szarkowski, Ph.D

Deaf and Hard of Hearing ProgramChildren’s Hospital Boston

Waltham, MALori G Tall, PsyDRush Neurobehavioral CenterSkokie, IL

Christine Trask, Ph.D

Department of Psychiatry and Human BehaviorWarren Alpert School of Medicine of BrownUniversity

Providence, RIGeoffrey Tremont, Ph.D

Neuropsychology Program, Rhode Island HospitalProvidence, RI

Contact information for authors

ix

Marie Van Tubbergen, Ph.D.

Department of Physical Medicine and

Keith Owen Yeates, Ph.D

The Research Institute at Nationwide Children’sHospital

Columbus, OHMichael Zaccariello, Ph.D

Department of Psychiatry and PsychologyMayo Clinic

Alexandra Zagoloff, M.S

Department of PsychologyIllinois Institute of TechnologyChicago, IL

Kathy Zebracki, Ph.D

Department of Behavioral Sciences,Rush University Medical Center,Pediatric Psychologist,

Shriners Hospital for Children,Chicago, IL

Frank Zelko, Ph.D

Neuropsychology Service, Children’s Memorial HospitalDepartment of Psychiatry and Behavioral ScienceFeinberg School of Medicine, Northwestern UniversityChicago, IL

Richard Ziegler, Ph.D

Pediatric Clinical NeuroscienceUniversity of Minnesota Medical CenterMinneapolis, MN

x

Biography for Jacobus Donders

Jacobus Donders obtained his PhD from the University

of Windsor in 1988 He completed his internship at

Henry Ford Hospital in Detroit, MI, and his residency

at the University of Michigan in Ann Arbor, MI

He is currently the Chief Psychologist at Mary Free

Bed Rehabilitation Hospital in Grand Rapids, MI

Dr Donders is board-certified by the American

Board of Professional Psychology in both Clinical

Neuropsychology and Rehabilitation Psychology He

has served on multiple editorial and professional

exec-utive boards, has authored or co-authored more than

100 publications in peer-reviewed journals, and has

co-edited two books about neuropsychological

inter-vention He is a Fellow of the National Academy

of Neuropsychology and of Divisions 40 (Clinical

Neuropsychology) and 22 (Rehabilitation Psychology)

of the American Psychological Association His main

research interests include construct and criterion

valid-ity of neuropsychological test instruments and

predic-tion of outcome in congenital disorders and acquired

brain injury

Biography for Scott J Hunter

Scott J Hunter is an Associate Professor of

Psychiatry, Behavioral Neuroscience, and Pediatrics

in the Pritzker School of Medicine at the University

of Chicago, where he serves as the Director of

Pediatric Neuropsychology and Coordinator for

Child Psychology training Dr Hunter obtained hisPhD in Clinical and Developmental Psychology fromthe University of Illinois at Chicago in 1996 Hecompleted his internship at Northwestern UniversitySchool of Medicine’s Stone Institute of Psychiatry,and residencies in Pediatric Neuropsychology andDevelopmental Disabilities in the Departments

of Pediatrics and Neurology at the University ofRochester He serves as an ad-hoc editor for a number

of peer-reviewed publications, and has authored orco-authored multiple peer-reviewed articles, presen-tations, and book chapters He co-edited PediatricNeuropsychological Intervention (CUP, 2007) withJacobus Donders Both clinically and in his research,

Dr Hunter specializes in identifying and izing neurocognitive and behavioral dysfunction inchildren with complex medical and neurodevelop-mental disorders

character-To Harry van der Vlugt, my original mentor, forsharing his lifespan wisdom and support

Jacobus DondersThis book is dedicated to the memory of ArthurBenton and Rathe Karrer, who each mentored myprofessional development, and to Richard Renfro, forhis ongoing support and understanding during thedevelopment and completion of this project

Scott J Hunter

Jacobus Donders and Scott J Hunter

Neuropsychology is the science and practice of

evaluat-ing and understandevaluat-ing brain–behavior relationships and

providing recommendations for intervention that can be

implemented in the daily lives of persons when brain

dysfunction compromises functioning at home or

school, on the job, or in the community at large The

associated target behaviors and skills can range from

specific cognitive abilities to emotional and psychosocial

functioning This specialty has advanced significantly

over the past several years, but recent well-respected

published works about common neuropsychological

disorders have tended to focus primarily or exclusively

on either children or adults, or have provided separate

discussions of conditions that are traditionally seen more

commonly at either end of the age spectrum (e.g

Morgan and Ricker [1], Snyder et al [2]) Similarly,

there is a dearth of comprehensive discussions in the

available literature to date of various neuropsychological

syndromes in their different manifestations across the

lifespan, and the longitudinal development and

longer-term outcomes of such conditions This has contributed

to a sometimes unwarranted bifurcation within thefield,

where developmental course has been left out of the

diagnostic and treatment equation In response, the

pri-mary goal of this volume is to provide an integrated

review of neuropsychological function and dysfunction

from early childhood through adulthood and, where

possible, old age, to support the understanding and

consideration of the role development plays in the

pre-sentation and outcome of neuropsychological disorders

across the lifespan

Each chapter in this volume is intended as an

empiri-cal review of the current state of knowledge concerning

the manifestation and evaluation of common

neuropsy-chological disorders as well as their intervention, with

additional consideration of what still needs to be done to

improve efficacy of practice and research The first

sec-tion provides a review of the general principles behind

lifespan developmental neuropsychology The second

section examines a number of commonly

encoun-tered neurodevelopmental, behavioral, and cognitive

disorders For many of the disorders, there is one chapterfocusing on pediatric aspects of the condition, oneemphasizing adult and/or geriatric concerns, and a sum-mary commentary chapter that consolidates and synthe-sizes the knowledge shared across the age-specific reviewchapters, with a focus on identifying and guiding areas offurther research and practice in the domain For someconditions (e.g cerebral palsy) there are currently simplynot enough data about outcomes into adulthood towarrant a separate chapter, whereas for other diagnosticgroups (especially some of the neurodegenerative ones,which are often associated with death prior to adult-hood), the emphasis is placed on the time frame inwhich they most commonly occur However, for severalother disorders (e.g traumatic brain injury), there is awealth of information about the correlates of new-onsetcases of the condition at different ages, as well as longi-tudinal outcomes

Each of the chapters in this volume was written byone or more authors who specialize in clinical practice

as well as research with the disorder being discussed

As a result, these experts give the reader an up-to-dateaccount of the state of the art of thefield at this time,and make suggestions for improvement in approachestoward assessment, intervention, and empirical inves-tigation of the disorders as they present across thelifespan We hope that this book will provide a vantagepoint from which to explore lifespan developmentalaspects of a wide range of commonly encounteredneuropsychological disorders We anticipate that itwill be of interest not only to pediatric neuropsychol-ogists but also to professionals in rehabilitation, neu-rology, and various allied healthfields

Association; 2006

Section I

Chapter

neuroanatomy John Williamson

On the development of functional

neural systems

The structure of the brain is in constantflux from the

moment of its conception to thefiring of its final nerve

impulse in death As the brain develops, functional

networks are created that underlie our cognitive and

emotional capacities Our technologies for evaluating

these functional systems have changed over time as

well, evolving from lesion-based case studies,

neuro-pathological analyses, in vivo neurophysiological

tech-niques (e.g electroencephalography), and in vivo

structural evaluation (CT scan, magnetic resonance

imaging (MRI), diffusion tensor imaging (DTI)), to

in vivo functional methodologies (functional magnetic

resonance imaging (fMRI), positron emission

tomog-raphy (PET)) And with these rapidly developing

tech-nologies, we are able to more thoroughly test some of

the earlier hypotheses that were developed about the

nature and function of the brain

Although attempts to localize mental processes to

the brain may be traced to antiquity, the phrenologists

Gall and Spurtzheim may have initiated thefirst

mod-ern attempt, by hypothesizing that language is confined

to the frontal lobes [1] While these early hypotheses

were largely ignored as phrenology fell in ill-repute,

they were resurrected in the early 1860s by Paul

Broca, who, inspired by a discussion of the

phrenolo-gists’ work, sparked a renewed interest in localization of

brain function with his seminal case studies on aphasia

[2] Broca’s explorations were among the earliest

exam-ples of lateralized language dominance

Recently, high-resolution structural MRI was applied

to preserved specimens taken from two of Broca’s

patients, to examine the localization of damage on the

surface and interior of the brains This modern

technol-ogy revealed extensive damage in the medial regions of

the brain and highlighted inconsistencies with previous

hypotheses in the area of the brain identified by Broca,

which is now identified as Broca’s area [3] This is

interesting, both from a historical perspective and also

with respect to our current understandings of the brainsystems involved in the behavioral presentations Brocadescribed (beyond the articulatory functions of the infe-rior frontal gyrus); specifically the extent of behavioralchanges identified by Broca is now more accuratelyreflected by the apparent neuropathology

A contemporary of Broca’s, John HughlingsJackson, offered a different perspective regarding local-ization While Jackson had no problem with the notion

of probabilistic behavior profiles with specific brainlesions (e.g a left inferior frontal lesion most likely willaffect expressive speech), he did not agree with theprevailing idea at the time that these lesion/behaviorobservations represented a confined center of function[4] Jackson proposed a vertical organization of brainfunctions, with each level (e.g brain stem, motor andsensory cortex, and prefrontal cortex) containing a rep-resentation, or component of the function of interest.Though this idea was at the periphery of opinion at thetime, when strict localizationist theory was gainingmomentum, it has come to form the basis of modernthought regarding the mechanisms of brain and behaviorrelationships

Holes and gaps in the models of strict localization ofbehaviors to specific, contained brain regions becamemore salient to the mainstream neuroscience communityover time (cf the disrepute of phrenology and conflictingfindings from lesion/behavior studies) In response, KarlLashley’s search for the memory engram typified anotherera in the exploration of brain–behavior relationships.Using an experimental approach rather than the classiccase study method, Lashley, famously unable to localizememory function in rats (through progressive brain abla-tion), introduced the constructs of equipotentiality andmass action [5] Equipotentiality is the concept that allbrain tissue is equally capable of taking over the function

of any other brain tissue (demonstrated in the visualcortex) and, relatedly, mass action references the ideathat the behavioral impact of a lesion is dependent onits size, not its location Also, although less popularized,

he suggested that, at any given time, the pattern of neural

activity is more important than location when

under-standing higher cognitive functions [6] Although

plasti-city in the human brain does not conform to notions of

equipotentiality, recent research on stem-cell treatments

in neurodegenerative diseases has reinvigorated the

con-struct in an albeit new form Guillame and Zhang [7]

review the use of embryonic stem cells as a neural cell

replacement technique and strides in functional

integra-tion, axonal growth, and neurotransmitter release (e.g the

development of dopamine-producing cells in mouse

brains after stem cell implantation)

Historically, political and social influences on the

philosophy of science trended Western societies away

from the study of brain structures in the

understand-ing of behavior after World War I [8] In contrast,

researchers in the former Soviet Union continued that

approach For example, while in opposition to the idea

of equipotentiality, Filimonov (cited in Luria, 1966 [9,

10]), a Soviet neurologist, presented the concepts of

functional pluripotentialism and graded localization

of functions Specifically, he postulated that no

cere-bral formation is responsible for one unique task, and

that the same tissue is involved in multiple tasks, given

the right conditions These concepts signaled a move

from strict localization approaches to understanding

brain–behavior relationships to a dynamic functional

systems approach (i.e back to a Jacksonian view), most

notably attributed to Alexandr Romanovich Luria His

approach to neuropsychological investigation stood

in contrast to Western psychometric methods, by

instead focusing on the effect of specific brain lesions

on localized/adjacent functional systems (syndrome

analysis) [10]

Luria stated that simple to more complex behavioral

operations are not localized to a particular brain region,

but instead managed by an“elaborate apparatus

con-sisting of various brain structures” [11] Though other

definitions of functional systems, or even neural

net-works, have since been posited, this early view

elo-quently described the construct Luria proposed that

all functional systems must involve three core blocks

including (1) the arousal block, (2) the sensory input

block, and (3) the output/planning unit Structurally,

the arousal unit referenced reticular formation and

related structures that impact cortical arousal; the

sen-sory input unit referenced post central-fissure

struc-tures and the integration of cross-modal sensory data;

and the output/planning unit referenced primarily the

frontal lobes and involved planning and execution of

behavior [12]

Luria presented a theory of functional systemsdevelopment based on these three functional units Hesuggested that the three functional units develop hier-archically in the form of increasingly complex corticalzones These zones correspond to primary, secondary,and tertiary motor and sensory areas, which develop inorder of complexity, with the tertiary planning unit(anatomically demarcated by prefrontal areas) appear-ing last [12] Luria’s developmental theory mirrorsJackson’s proposal that neuro-anatomical developmentproceeds upward from the spinal cord to neocortex andfrom the posterior to anterior [4]

Functional systems, of course, are organizedwithin a far more complicated web than Luria’s orig-inal three-tiered theory Still, modern brain research-ers have“run” with the idea of the functional system.Recent research has explored questions of the nature

of top-down control (vertical integration), with someinvestigators arguing for specific areas within thestream as primary originators (e.g lateral prefrontalcortex [13]), while others argue for different corticalsystems as top-down controllers (e.g fronto-parietaland cingulo-opercular control networks [14]).Functional neuroanatomy is the basis of ourunderstanding of the human condition, as is an under-standing of how that anatomy interacts with the bodyand its environment; a complex dance What we doknow is that almost any behavior, even a slight devia-tion in heartbeat interval, may be influenced bymyriad factors within the nervous system A deviation

of heartbeat interval can be influenced by fluctuations

in physical activity, thinking, and emotional status [15,

16] Our exploration of brain–behavior relationships

is further complicated by language, and more specically the definition of constructs that are chosen to

fi-define these relationships Take, for example, ourunderstanding of a change in heartbeat interval andits relationship to emotion Constructs such as fear,anger, sadness, and happiness describe rather largesubsets of behavior In order to capture these emotions

at a brain level, Arne Ohman has suggested that tion is a “flexibly organized ensemble of responses,which uses whatever environmental support is avail-able to fulfill its biological function” [17]

emo-This is a noticeably loose definition It has to be withconstructs such as emotional memory [18], expressiveaprosodia and receptive aprosodia [19], emotional intel-ligence [20], approach and withdrawal [21], and termssuch as melancholy, wistfulness, euphoria, mirth, anddoldrumsfloating around in the collective consciousness

of researchers and the lay public To understand that

4

minute shift in heartbeat interval, we need to understand

the emotional state of our subject To evaluate the

func-tional systems involved in that heartbeat shift, we need to

understand the interconnecting pathways involved in

vagal (cranial nerve X) control of the heart (direct

para-sympathetic nervous system influence is necessary in a

beat-to-beat change in heart rate) What structures

con-nect to the vagus? What structures concon-nect to those

structures? Are there afferent feedback loops? How do

these control systems develop? The so-called“decade of

the brain” has extended and we have an ever-developing

complexity in our understanding of the brain’s role in

defining what it means to be human It is an exciting time

to be a neuropsychologist

The development of functional neuroanatomy

across the lifespan is a complicated topic This chapter,

necessarily, is not a comprehensive review of the subject,

but is instead a detailed introduction As such, the

purpose of the following sections is to discuss current

research and our current knowledge regarding the

neu-roanatomical structures that are of particular interest

with regard to understanding cognitive and emotional

development The chapter is therefore organized as

follows: (1) Brain structure In this section, we cover

cellular structures and brain areas in their prototypical

forms, discussing general associated functions (2)Brain

development across the lifespan This section covers the

mechanism of brain development and notable changes

over time in anatomy and function

Brain structure

The nervous system is composed of central (CNS),

peripheral (PNS), and enteric branches The brain

and spinal cord form the CNS Nerves that connect

the spinal cord and brain to peripheral structures such

as the heart compose the PNS The enteric nervous

system controls the gastrointestinal system primarily

via communication with the parasympathetic and

sympathetic nervous systems

Brain cells

The brain has two classes of cells, neurons and glia There

are many different types of cells within each class,

although they all share characteristics that distinguish

these nervous system cells from other cells in the body

Generally stated, neurons are specialized electro-chemical

signal transmitters and receivers Glia serve a supporting

role in the brain (e.g nutritional and scavenger functions,

growth factors, blood–brain barrier components, and

myelin–white matter creation) and have a role in genesis during development (e.g radial glia as neuronprogenitors [22])

neuro-NeuronsWithin the adult neocortex, there are billions of neu-rons and 10 to 50 times more glia The total number ofsynapses is estimated to be approximately 0.15 quad-rillion Myelinated white matter is estimated to spanbetween 150 000 and 180 000 kilometers in the youngadult [23,24]

Neurons are composed of a cell body, axon, anddendritic fields The cell body contains less than

a tenth of the cell’s entire volume, with the der contained within the axon and dendrites [25].Synapses are interaction points between neurons

remain-An individual neuron communicates via actionpotential Action potentials are all-or-none electricalevents which are excited (promoted) or inhibited(prevented) based on the nature of synaptic stimu-lation (e.g the nature of chemical and electricalstimulation via neurotransmitters and graded poten-tials) A single neuron may be in direct contact (viasynapse) with thousands of other neurons Thefiringrate of a neuron is influenced by the summation ofinhibitory and excitatory events along the axon anddendritic–synaptic interactions among the numer-ous connections Speed of transmission is a function

of white matter width and myelination

White matter may be myelinated or unmyelinated.Myelination increases transmission speed Myelinsheathes (covering axons) are generated by specializedglial cells in the brain calledoligodendroglia, and in theperiphery by cells calledSchwann cells

Neurons may be classified as unipolar, lar, or bipolar depending on the cell body form andnumber and arrangement of processes Functional char-acteristics are also used in classification (e.g afferentneurons that conduct signals from the periphery to theCNS are also called sensory neurons, and efferent neu-rons that conduct signals from the CNS to the peripheryare also called motor neurons) Further, neurotransmit-ter receptor types are also used to describe neurons.For example, neurons containing serotonin or gluta-mate are referenced as serotonergic or glutaminergicneurons [26]

pseudounipo-NeurotransmittersNeurotransmitters are chemical agents that bind tospecialized receptors on neurons Neurotransmitters

A lifespan review of developmental neuroanatomy

5

specifically relevant to neuropsychology include,

but are not limited to, serotonin (e.g depression/

anxiety), acetylcholine (e.g memory), dopamine

(e.g motor), norepinephrine (e.g depression),

gluta-mate (e.g memory), and gamma-aminobutyric acid

(e.g anxiety) The effect of a particular

neurotrans-mitter on a functional system is largely determined

by receptor types Each neurotransmitter can bind to

multiple receptor types The distribution of receptor

types is not even throughout the brain and may

influence emotional state/traits, disease outcomes

in mental health, and response to

psychopharmaco-logically active medications For example, protein

expression of serotonin receptors in the prefrontal

cortex differentiates successful suicidal patients and

controls [27] Asymmetry in serotonin receptors is

found in depressed patients with greater right

prefron-tal receptor density than left compared with controls

[28] Moreover, higher baseline binding potential in

chronic depression pharmacological treatment is

associated with worse outcomes [29] For a more

comprehensive review of neuronal structure and

function, see Levitan and Kaczmarek [30]

Cranial nerves

There are 12 cranial nerves A solid understanding

of the effects of cranial nerve lesions, or the effects

of upstream lesions on cranial nerve activity, is an

important tool for neuropsychologists in evaluating

patient presentation Cranial nerves have both

sen-sory and motor functions For example, cranial nerve

level control of the muscles of the eye is distributed

across three nerves (the oculomotor, trochlear, and

abducens nerves), whereas sensory information from

the eye is transmitted via the optic nerve The optic

nerve projects from the retina, to the thalamus,

through the temporal and parietal cortices, and to

the calcerine cortex in the occipital lobe Processing

is not performed at the level of the cranial nerves,

which only serve to connect/transmit information

from processing centers Testing cranial nerve

func-tion can, however, give clues as to the nature of a

lesion For example, the optic radiations of the optic

nerve travel close to the surface of the cortex of the

temporal lobe A unilateral lesion of the temporal

lobe can cause a contralateral visual field cut

Examining associated behavioral changes can suggest

a location for a functional lesion For a more detailed

review of cranial nerve functions and assessment see

Monkhouse [31]

RhombencephalonThe rhombencephalon, or hindbrain, is composed ofthe medulla oblongata, the pons, and the cerebellum.Functionally, the hindbrain contains several structuresinvolved in neural networks regulating autonomicnervous system (ANS) function and arousal Cranialnerves regulating the ANS (vagus), and movements ofthe mouth, throat, neck, and shoulders (glossophar-yngeal, hypoglossal, trigeminal, spinal accessory) arefound in the hindbrain Additional structures includethe reticular formation (basic autonomic functions,respiration), nucleus of the solitary tract (in actuality,this refers to several structures) and the nucleus ambi-guus The nucleus ambiguus and the nucleus of thesolitary tract are the primary interface junctions forthe vagus nerve, which enervates the viscera In think-ing about the development of brain structures andfunctional systems relevant to emotional and cognitivebehaviors, it may be helpful to consider phylogeny andlessons from comparative neuroscience

Transitioning from reptiles to mammals, we seethe emergence of myelinated vagus Returning to ourearlier example of emotion and changes in heartbeatintervals, Porges [32, 33] discusses the impact of thissystem and its development on social engagementbehaviors in humans with his polyvagal perspective,contrasting and elucidating the interactions of brain-stem structures, peripheral afferents, cortical andsubcortical top-down control, and myelinated andunmyelinated vagal efferents Regulation of the auto-nomic nervous system is a complex component ofsocial behaviors and emotional response Cortical, sub-cortical, and other brain structures such as the amyg-dala, hypothalamus, orbitofrontal cortex, and temporalcortex all interact via direct and indirect pathwayswith these hindbrain structures to influence parasym-pathetic and sympathetic nervous system response.Further, the nucleus of the solitary tract receives affer-ent input from the periphery (e.g baroreceptors, whichmonitor and relay changes in blood pressure), which

is in turn distributed to subcortical and cortical tures for processing

struc-These hindbrain structures should be considered asoutput and input nuclei for a range of supportive behav-ioral features in the human (e.g facilitating appropriatearousal levels for performing cognitive, exertional, andsocial functions) Also contained within the rhomben-cephalon are the pons and cerebellum Functionally,these structures contribute to fine motor control viapostural and kinesthetic feedback to volitional areas

6

(e.g premotor and motor cortex) This includes

facili-tating motor movements in speech

In addition to fine motor control, lesions of the

cerebellum have a wide range of behavioral and cognitive

consequences The cerebellum has reciprocal

connec-tions to brainstem nuclei, hypothalamus, and prefrontal

and parietal cortices (among other areas) Behavioral

effects of cerebellar lesions observed in the literature

include autonomic disregulation [34],flattening of affect,

distractibility, impulsiveness, stereotyped behaviors,

depression [35], memory and learning dysfunction,

lan-guage problems, and visuospatial effects [36] Though

these problems in cognition and behavior are clearly less

severe than lesions in associated areas of neocortex and

some reported issues have not been replicated, the variety

of impacts suggests an important role for the cerebellum

in some of these functional systems There are some

interesting clues as to what that role may be

Recent research has shown additional roles of the

cerebellum in speech with lesion effects beyond dystaxic

motor impairments in speech formation Ackerman

et al [37] review recent clinical and functional imaging

data as they pertain to speech syndromes and potential

connections to other cognitive functions following

cer-ebellar lesions They argue that connections to language

areas in the cortex function as conduits to

subvocaliza-tion (self speech) which is involved in verbal working

memory (a right cerebellar/left frontal interaction)

This subvocalization argument is also present in other

modalities (e.g imagined movements) These

connec-tions, along with the hypotheses of planning and

rehear-sal components attributed to cerebellar activity, may

explain the increasing evidence of wide-reaching

cogni-tive and behavioral effects with cerebellar lesions

Mesencephalon

The midbrain includes the substantia nigra (linked

to dopamine production and Parkinson disease), the

superior and inferior colliculi (visual and auditory

sys-tem actions), and a large portion of the reticular

acti-vating system (RAS) The reticular actiacti-vating system,

formed in part by nuclei in the midbrain tegmentum,

plays a role in consciousness The discovery of the RAS

was critical for understanding coma It serves as a

modulator of sleep and wakefulness via connections

to the diencephalic structures, the thalamus (thalamic

reticular nucleus) and hypothalamus These

connec-tions ascending from the reticular formation are part

of the ascending reticular activating system Also nested

within the midbrain are projections from the dorsal

raphe nucleus (from the hindbrain structure, the pons).The raphe is a source of serotonin and is also involved

in the regulation of sleep cycles

The substantia nigra is functionally linked to thebasal ganglia, specifically the caudate nucleus and theputamen (referred to collectively as the striatum) It isdivided into two sections, the pars compacta and thepars reticulata The pars compacta projects to thestriatum and the pars reticulata projects to the supe-rior colliculus and thalamus The substantia nigraprovides dopamine to the basal ganglia and it is part

of the extrapyramidal motor system Lack of mine in the striatum leads to parkinsonian symptoms(rigidity, tremor, slowing); the system still functionswithout the substantia nigra as long as the level ofdopamine is regulated properly

dopa-The superior and inferior colliculi are nected small structures in the midbrain that areinvolved in visual and auditory orientation and atten-tion The superior colliculus receives projections fromthe frontal eyefields (premotor cortex) and controlssaccadic movements The interconnection and func-tional relationship to the prefrontal cortex has led tothe use of saccadic eye movement models in evaluatingthe neural circuitry of schizophrenia and other psychi-atric illnesses thought to involve prefrontal corticalsystems [38]

intercon-TelencephalonThe telencephalon includes the entirety of the cerebralhemispheres including the diencephalon, limbic sys-tem, basal ganglia, and other structures We will con-tinue working our way through the brain from theventral to the dorsal and the caudal to the rostral Webegin the discussion of the telencephalon with thethalamus and hypothalamus

Thalamus and hypothalamusThe thalamus and hypothalamus, among other struc-tures, compose the diencephalon The thalamus is acomplex bilateral structure with extensive reciprocalconnections to major structures throughout the brain,including efferent fibers to cortical regions (thalamo-cortical axons) and afferent fibers from cortical regions(corticothalamic axons) There are 11 thalamic nucleithat are classified as either relay or association nucleibased on their target projections These are specificnuclei There are also nonspecific nuclei, stimulation

of which yields activations along a large area of cortex.The thalamus has nuclei with projections to all major

A lifespan review of developmental neuroanatomy

7

sensory areas except for olfaction Further, it is a

pro-jection site for the RAS (important role for arousal and

sleep; logical, given the sensory connections) For a

comprehensive review of thalamic nuclei and function,

please see Jones [39]

Because of the heterogeneity of nuclei, associated

functional systems, and projections of the thalamus,

it can be difficult to understand which systems are

involved in the neuropsychological sequelae of

thala-mic lesions One approach is to use functional imaging

technologies, such as PET scan, to evaluate diaschesis

effects of a localized thalamic lesion [40]

The thalamus is the most likely location for a

strategic infarct (e.g from a stroke) to cause a

demen-tia This is probably a consequence of the role of the

thalamus in regulating higher-brain activity As a

sub-cortical structure with dense connections throughout

both hemispheres, the thalamus reflects the

lateraliza-tion of funclateraliza-tion of involved cortical areas For

exam-ple, contralateral attentional neglect occurs with

right-sided thalamic lesions A similar presentation is also

evident with right parieto-temporal lesions [41]

Developmentally, abnormalities in thalamic nuclei

(e.g massa intermedia), have been associated with

future manifestations of psychiatric conditions such as

schizophrenia The massa intermedia is detectable early

in development, within 13 to 14 weeks of gestation [42]

There is some evidence that the medial dorsonuclei

reduces in volume as schizophrenia progresses, an

area rich in connections to prefrontal cortex (an area

implicated in the expression of schizophrenia) [43]

Shimizu et al [44] find evidence of a developmental

interaction between the massa intermedia and

medio-dorsonuclei in schizophrenic patients

The hypothalamus is primarily involved in

viscer-omotor, viscerosensory, and endocrine (oxytocin and

vasopressin) functions It directly modulates autonomic

nervous system activity It functions as one connection

point for limbic structures (involved in emotional

reg-ulation) to control of the autonomic nervous system

The stria terminalis, an afferent white matter tract,

connects the amygdaloid bodies to the hypothalamus

The hypothalamus then has direct efferent connections

to brainstem nuclei, including the output nuclei for

vagal control (nucleus ambiguus) and sympathetic

neu-rons in the spinal cord These connections make the

hypothalamus a critical component in functional

sys-tems involved in rage and fear responses

The interaction of three structures, the

hypothal-amus, pituitary gland, and adrenal gland, is

impor-tant in the regulation of mood, sexuality, stress, and

energy usage The so-called adrenal (HPA) axis has been implicated in socialbonding and mate-pairing in comparative neuro-science and human research Developmentally, ithas been found in prairie voles that exposure to oxy-tocin (a hormone produced in the HPA) early on isassociated with capacity for social bonding in adultanimals [45,46]

hypothalamic-pituitary-Further connections also involve the hypothalamus

in memory functions (e.g the hippocampus and millary bodies are connected via the fornix) Lesions tothe mammillary bodies, a hypothalamic structure, cancause severe anterograde memory deficits Deterioration

mam-of this system is associated with the development mam-ofAlzheimer’s disease

Basal gangliaThe basal ganglia are a set of subcortical grey matterstructures most often associated with aspects of motorcontrol, though recent research demonstrates addi-tional roles in functional systems, including cognitivedomains such as attention Unlike primary motor cor-tex lesions, paralysis does not occur with basal gangliadamage Instead, abnormal voluntary movements atrest, and initiation and inertia deficits are typical.The structures included in the basal ganglia vary bynomenclature, but commonly reference the caudateand putamen (i.e dorsal striatum or neo-striatum),globus pallidus (internal and external segments), sub-stantia nigra, and subthalamic nucleus Other nomen-clatures include the amygdala (discussed here withlimbic system structures), and the nucleus accumbensand olfactory tubercle (ventral striatum)

There are two pathways of activity in the basal glia with opposing behavioral outcomes, the indirect andthe direct pathways These pathways facilitate and inhibittheflow of information through the thalamus and oper-ate simultaneously (the overall effect is a function of thecurrent balance of activation pattern between the path-ways) Activation of the direct pathway increases thala-mic activity and activity of the cortex Activation of theindirect pathway decreases thalamic activity and activity

gan-of the cortex Damage to the basal ganglia can eitherdecrease or increase movement depending on whichstructures/neurotransmitters are impacted within thedirect and indirect pathways

Several neurodegenerative disorders are associatedwith basal ganglia structures including Parkinson dis-ease, Huntington disease, Wilson disease, and variousmultisystem atrophies (MSAs) Psychiatric disorders

8

that appear in childhood including attention deficit

hyperactivity disorder (ADHD) and Tourette syndrome

are also associated with abnormalities in the basal

gan-glia Recent studies have shown reduced overall caudate

volumes and lateralized differences in caudate and

globus pallidus volumes (left greater than right) in

chil-dren diagnosed with ADHD [47] Further, fractional

anisotropy, a measure of apparent white matter integrity

using a structural imaging technique called diffusion

tensor imaging (DTI), is reduced in ventral prefrontal

to caudate pathways in children with ADHD [48]

Behaviorally, this prefrontal/caudal circuit is thought to

relate to inhibitory control (e.g a go–no go task) As for

etiological factors, there is recent evidence that early diet

can influence future caudate volumes and intellectual

aptitude [49], suggesting a potential avenue for

environ-mental factors such as nutrition on neural structure and

cognitive/behavioral outcome

The role of basal ganglia structures in cognitive

pro-cesses is multi-factorial Aron et al [50] present

converg-ing evidence on the role of a fronto-basal ganglia network

in inhibiting both action and cognition They review

both comparative and human data using go–no go

tasks and conclude that the fronto-basal ganglia systems

are critical in determining individual differences in a

variety of human behaviors, stating, “Variation to key

nodes in this circuitry (or to their connections) could

produce important individual differences, for example,

in aspects of personality, in the response to therapy

for eating disorders, and in liability toward and

recovery from addiction Developmental, traumatic,

or experimentally induced alterations to key nodes in

the control circuit lead to psychiatric symptoms such

as inattention, perseveration, obsessional thinking

and mania, and could also have relevance for

move-ment and stuttering.”

Limbic system

The limbic system is a network of structures involving

subcortical, cortical, and brainstem regions that play a

role in emotional behaviors including emotionally

related memory/learning and social interactions

Important subcortical gray matter structures of the

limbic system include the amygdala, nucleus

accum-bens, and hypothalamic nuclei (as illustrated above in

the HPA), among others Cortical structures include

aspects of the prefrontal cortex (orbitofrontal),

cin-gulate gyrus, and the hippocampus

The amygdala, probably the most central structure

(conceptually) of the limbic system, is almond-shaped

and located deep in the anterior temporal lobe Thereare multiple nuclei which can be divided into twogroups, a basolateral group and a corticomedialgroup The amygdala is rich with connections to cort-ical areas including the orbitofrontal cortex and tem-poroparietial cortex, subcortical structures includingthe basal ganglia, thalamus, hypothalamus, brainstemstructures including autonomic output nuclei, and thehippocampus (a phylogenetically older area of cortexinvolved in memory consolidation)

The amygdala is involved in functional systems ofemotion, reward, learning, memory, attention, and moti-vation Though researchers have strongly focused on fearconditioning and negative emotions in the amygdala (therole of the amygdala in fear startle reflex), it also has arole in positive emotion For a review of the role of theamygdala in positive affect see Murray [51] Direct stim-ulation of the amygdala via electrodes has been shown tomost probably elicit fear or anger responses In rats,electrical stimulation of the amygdala elicits aggressivevocalizations [52] In humans, in a study of 74 patientsundergoing presurgical screening for epilepsy, fearresponses were most frequent with amygdala stimulation(higher rate for women than men) [53]

Functionally, in addition to a central role in tional processing, the amygdala has a role in olfaction(the corticomedial cell group is directly connected tothe olfactory bulbs), though there are also intercon-nections to other sensory areas The amygdala appears

emo-to respond emo-to threatening sensory stimuli via zation of fight or flight responses [54], but it alsoresponds to positive sensory stimuli The key is notthe modality of the sensory input or the valence, theamygdala will respond to all, but whether the sensorydata contain affective content The amygdala alsoenhances cognitive performance in the context ofemotional stimuli (e.g emotional memory formationvia linkages to the hippocampus) [55]

mobili-Developmental disorders such as autism have beenlinked to abnormal changes over time in the amygdala

In addition to increased white matter volumes andoverall head size early in autism, in a study of youngchildren with autism (36–56 months of age), theamygdala was enlarged by 13–16% Amygdala vol-ume differences, both larger and smaller, are found inmany psychiatric conditions, including schizophrenia,depression, bipolar disorder, generalized anxiety disor-der, and borderline personality disorder Sometimes,conflicts appear with one study showing increasedamygdala volume in depression and another showingdecreased amygdala volume Tebartz et al [56] suggest

A lifespan review of developmental neuroanatomy

9

a resolution to such conflicting results may be a

func-tion of the“dominant mode of emotional informational

processing.” They hypothesize that an enlarged

amyg-dala may relate to depressed mood, anhedonia, phobic

anxiety, and rumination and that a smaller amygdala

may relate to emotional instability, aggression, and

psychotic anxiety

Another limbic structure, the hippocampus, is

located ventrally and medially in the temporal lobe, and

can be divided into four regions, designated CA1, CA2,

CA3, and CA4 CA stands for cornu ammonis A major

input pathway to the hippocampus stems from the

ento-rhinal cortex and the main output pathway from the

fornix The hippocampus is a critical structure to

learn-ing new information Damage to the hippocampus can

cause severe anterograde learning deficits such as in

Korsakoff’s syndrome, a condition caused by vitamin

deficiencies in chronic alcohol abuse that damages

hip-pocampal structures Classically, the role of the

hippo-campus in memory was brought to the attention of the

scientific community via a case study in 1957 [57] of a

patient who underwent bilateral temporal lobe

resec-tions, referred to as HM HM had intact remote and

autobiographical memory until the surgical procedure,

but was unable to learn new information subsequently

Corkin [58] reviews 45 years of research on HM

Laterality and extent of peripheral involvement

determine the type and severity of memory impairment

with hippocampal lesions Involvement of projection

areas such as the entorhinal cortex increases the severity

of anterograde deficit This is the system that

deterio-rates in cortical dementias such as Alzheimer’s disease

Bilateral lesions produce dense anterograde memory

deficits A unilateral left or right hemisphere lesion will

produce verbal or spatial memory deficits, respectively

Normal development of the hippocampus can be

interrupted by environmental factors Hippocampal

volumes are reduced in victims of childhood abuse

[59] Pediatric temporal lobe epilepsy can also have a

significant impact on hippocampal development

Hippocampal atrophy in children with epilepsy has

been shown to relate to reduced neuropsychological

performance [60]

Cerebral cortex

The cortex is divided into four lobes, the frontal,

temporal, parietal, and occipital As was discussed

ear-lier in the chapter on top-down control and the

organ-ization of functional systems, the cortex is the most

highly organized and complex aspect of brain

management The cortex is thought to be necessaryfor conscious behaviors (thalamo-cortical relation-ships), though recent research suggests that somelevel of consciousness can exist without the cortex[61] There are two hemispheres divided by a largefissure called the longitudinal fissure They are generallysuperficially symmetrical and structures are mirroredacross the two Though there are individual differences

in brain structure, on average it is known that the rightfrontal lobe tends to be wider than the left and the leftplanum temporale of the superior temporal cortex islarger than the right (thought to be related to languagedevelopment) Recent neuroimaging research has alsodemonstrated substantial differences in white matterconnectivity; for example, in systems underlying lan-guage functions between the left and right hemisphereusing diffusion tensor imaging [62]

Several helpful mapping systems have been created

to identify various brain regions Brodmann’s map isone of the best-known systems and it is based oncellular architecture (seeFig 1.1)

9 8

2 5 7

19

18

17 18 19 37 20 21

257

19

18

17 18 19 37 20

38 11 10 9 8

33

24

23 31

26 29 30 27 25 34 28 38 35

32

12

38 11

10

46

40 39 41

The motor and sensory areas of cortex are divided

by a largefissure called the central sulcus (also known

as the Rolandic fissure and cruciate fissure) This

divides frontal and parietal areas and represents

a steep functional boundary The regions on either

side of the fissure are the primary motor cortex

(Brodmann’s area 4, anterior of the fissure) and

pri-mary somatosensory cortex (Brodmann’s areas 3, 1,

and 2, posterior of thefissure) Organizationally, it is

helpful to think in terms of primary, secondary, and

tertiary association cortex Functions progress from

simple to complex, from unimodal to multi-modal

Each sensory system is composed of a primary

projection area and secondary and tertiary association

areas Functionally, the primary projection areas are

thefirst area of cortex to receive information from a

specific sensory system Sensory data reaching the

primary projection area are necessary for conscious

perception Lesion of primary sensory cortex can

result in a loss of awareness of the affected modality;

however, the individual may still respond reflexively to

the modality (e.g blindsight) Further sensory

pro-cessing occurs in secondary association cortex, but it

is still limited to one modality Finally, tertiary

associ-ation cortex (e.g Brodmann’s area 7 in the parietal

lobe) integrates data from multiple sensory modalities

The primary sensory projection areas are as

fol-lows: (1) vision = occipital cortex (calcerine cortex,

Brodmann’s area 17), (2) audition = superior temporal

gyrus, temporal lobe (Brodmann’s areas 41 and 42),

(3) somatosensation = postcentral gyrus, parietal cortex

(Brodmann’s areas 3, 1, and 2), (4) gustation = parietal

operculum (Brodmann’s area 43), (5) olfaction =

ante-rior tip of the temporal lobe (Brodmann’s area 38)

The secondary and tertiary association cortices

sur-round and extend from the primary projection areas

(e.g visual association areas roughly correspond to

Brodmann’s areas 18 and 19)

In a normally organized brain, the left hemisphere

is dominant for language functions Around 90%

of the population is estimated to be right-handed

Sinistrality is a clue that a brain is not normally

organ-ized Recent neuroimaging studies have demonstrated

different activation patterns in left-handers when

pro-cessing language, with greater bilateral activations and

shifts towards right-hemisphere language processing

[63] Assumptions about localization and

lateraliza-tion of funclateraliza-tion should be treated with greater caulateraliza-tion

in these cases The occurrence of sinistrality appears

to be a combination of genetic and environmental

factors Sinistrality is over-represented in several

neurological/psychiatric conditions such as epilepsy,autism, and schizophrenia A recent study demon-strates a potential genetic link between sinistralityand schizophrenia [64]

The hemispheres are functionally specialized todeal both with different kinds of information and thesame information in different ways Although an in-depth review of laterality is well beyond the scope ofthis chapter, a few common areas of study includelanguage, neglect (attentional space), memory (non-verbal versus verbal), and emotion

In a normally organized brain, different aspects oflanguage functions are divided across the hemisphereswith semantic content, production, and rhythm local-ized to the left hemisphere, and expressive and recep-tive prosody/melody localized to the right hemisphere.Further, there is evidence that the right superior tem-poral lobe is instrumental in the identification of indi-vidual voices [65] Lesions, depending on laterality andposition relative to the central sulcus (anterior orposterior), will have expressive or receptive conse-quences, or both (e.g a right frontal lesion may pro-duce an expressive aprosodia, or inability to modulatethe tone of speech output in a meaningful way,whereas a left frontal lesion may produce an expressiveaphasia, inability to produce speechfluently)

In emotion, laterality is not a simple matter Forexample, a model of aspects of emotional experiencethat has been applied across the lifespan is proposed

by Fox and Davidson [66] They present a view ofemotional expression with emphasis on right andleft frontal modulation Much of Fox’s work hasconsisted of developmental EEG research Specifi-cally, Fox infers right and left frontal activationfrom localized alpha bandwidth (~8–12 Hz) sup-pression Two constructs are proffered as indicative

of left versus right frontal activation respectively,approach and withdrawal

Approach and withdrawal behaviors as recentlyconceptualized refer to social interactions Approachbehaviors are associated with positive affect and with-drawal behaviors are associated with negative affect.These behaviors are evident, at least in some form,

as early as infancy In one study, with a group selectioncriterion of motor reactivity and a disposition compo-nent (assessed through parent report and observation)infants with high motor reactivity and a dispositiontowards negative affect were found to be more likely

to evidence greater right frontal EEG asymmetry,supporting the notion of right frontal mediation ofnegative emotion [67]

A lifespan review of developmental neuroanatomy

11

In another study, with implications for the extent

of behavioral generalization of Fox’s constructs from

EEG records, it is demonstrated that resting frontal

EEG asymmetry and social behavior during peer play

were related to the occurrence of maladaptive behavior

in preschool-aged children Fox et al [68] assert that

resting frontal asymmetry within the alpha band may

be a marker for certain temperamental dispositions

Brain development

Higher-order cognitive and emotional development

in humans is in part a byproduct of consciousness

Human consciousness and cognitive and emotional

characteristics develop through the integration of

increasingly complex functional systems starting

early in life The process of neural development begins

simply (cell division) Brain weight increases from

the heft of a few dozen cells to about 800 g at birth

(males > females), to 1200 g at six years old, to around

1500 g and back down again to 1100–1300 g in the very

elderly [69]

Among the very first markers of neural

develop-ment, prenatally, is the appearance of the neural

groove The neural groove progresses to form the

neural plate and then the neural tube Progenitor

cells along the various zones (ventricular,

intermedi-ate, and marginal in order of appearance) of the early

developing nervous system develop into neurons and

glial cells, forming the basic context of spinal and brain

systems The neural tube eventually forms into the

central nervous system and it evolves from posterior

to anterior with modifications to accommodate

speci-alized brain regions along the rostral–caudal stream

through a process called neurulation

Neural tube defects are a leading cause of infant

mortality in the USA and a mechanism of future

disability in live births (5.59 per 10 000 live births)

[70] Ingestion of folic acid supplements drastically

reduces risk Neural tube defects, often manifesting

as incomplete closure, can present in different ways

depending on the etiology and the extent of

malfor-mation The most common defects include spina

bifida and anencephaly Anencephaly results in

incomplete formation of the brain and skull

Consciousness cannot occur and neonates generally

die within a few days of birth

Spina bifida malformations occur in three

varia-tions, occulta, meningocele, and cystic The most

severe condition is spina bifida meningocele, which

can result in significant disability The symptoms areprimarily physical (degree of paralysis, bowel andbladder control problems, and scoliosis), though cog-nitive issues also occur, especially with co-occurrence

of hydrocephalus (15–25% of meningocele cases).Neuropsychological impairments tend to center ondelayed/absent development of executive functionsover time [71], and memory deficits including pro-spective and episodic memories [72]

A related condition, the Arnold-Chiari tion, occurs in almost all children born with spinabifida meningocele, though it also occurs independ-ently The Arnold-Chiari formation is the etiology ofhydrocephalus in spina bifida meningocele The cer-ebellum is herniated through the foramen magnum inthe base of the skull, blocking the ventricular system.Severity is graded from one to four (four is the mostsevere) It is often undetected and symptoms, if theyoccur, can manifest later in life and include deficitsassociated with hindbrain functions (cranial nerves)and the cerebellum

malforma-By ten weeks after conception, all of the majorstructures of the central nervous system are recogniz-able by their appearance Functional capacity is notachieved until much later The earliest detection of

“normal” EEG patterns in neonates has been denced as young as 24 weeks after conception [73].This is about the time that production of neuronshalts At this point, there can be as many as twice thenumber of neurons present as in the mature adultbrain After this, there is programmed cell death.Sleep stages, such as REM, can be matched behavior-ally and via EEG as early as 25 weeks post-conceptionage [74] The earliest detection of auditory response(auditory evoked potentials) is at a post-conceptionage of 27 weeks Evoked potentials change over time,even after birth, shifting temporally [75], as do EEGpatterns in general (e.g infant alpha)

evi-There are several cellular processes that are tant to understand in the developing brain Amongthem apoptosis, synaptogenesis, and myelination occurthroughout the lifespan and are critical in brain plas-ticity and processes such as learning Apoptosis, orprogrammed cell death, is an active process in braindevelopment It plays a prominent role in eliminatingthe excess neuronal growth produced prenatally and inshaping synaptic connections

impor-Synaptogenesis is, as one might expect, the tion of synapses It is a dynamic process and occursthroughout the lifespan Synapses form and are

forma-12

replaced if they are not reciprocated properly by the

target cell The process is called synaptic stabilization

Not all synapses are equally susceptible to replacement

For a variety of reasons, synaptic plasticity is

nec-essary throughout the lifespan, e.g in the case of

learning A vexing problem in literatures on cellular

processes in learning is the formation and

strengthen-ing of new synapses A hypothesis that has received

increasing support is that of synaptic tagging and

capture (STC) proposed by Frey and Morris in 1997

[76] Barco et al review ten years of subsequent

research and conclude that the model remains the

most compelling hypothesis to explain

synapse-specific plasticity processes [77] The concept

stipu-lates that, “the persistence of changes in synaptic

strength is mediated by the generation of a transient

local synaptic tag at recently activated synapses and by

the production of plasticity-related proteins that can

be used or captured only at those synapses marked by

the tag.” This is a necessary factor for selection of

synaptic modification at the cellular level In other

words, this is the process by which synapses are

iden-tified and strengthened in facilitation of long-term

structural change in learning

In the development of higher-level primates

includ-ing humans, it becomes apparent that connectivity is

a major discriminating factor in the evolution of

cog-nitive functions There is a disproportionate increase

in white matter volume throughout primate evolution,

with prefrontal white matter differentiating humans

[78] There is both myelinated and unmyelinated

white matter in the brain Myelin is created by

oligo-dendrocytes (specialized glia) in the central nervous

system This process is called myelination It begins

around the 24th week post conception and increases

dramatically through adolescence, with a slow increase

through as late as the fourth decade of life [79]

With the development of diffusion tensor imaging

over a decade ago [80], due to its sensitivity to changes

in white matter structure, there have been several

valuable studies of normal development of white

mat-ter from childhood through adulthood The trend is

that maturation is associated with increased fractional

anisotropy Fractional anisotropy values increase with

greater myelin presence More recently, efforts have

been made to quantify regionally specific changes in

white matter integrity and association with cognitive

development In a cross-sectional design, Qui et al

[81] find increased FA in cerebellar, right temporal,

superior frontal, and parietal white matter with age

In the elderly, neuropathological studies have gested a faster rate of white matter loss than greymatter loss Neuroimaging results with conventionalstructural methods have been less clear with respect tochanges in white matter as both significant and non-significant results have been reported Diffusion tensorimaging consistently shows a decline in fractional ani-sotropy with age [82] Regionally, the areas that appear

sug-to be most affected include prefrontal white matter, thesplenium, and periventricular white matter

Disorders of white matter tend to preferentiallyimpact fronto-subcortical functional systems Damage towhite matter anywhere in the brain results in hypoperfu-sion of frontal cortex [83] We see in disorders of whitematter such as multiple sclerosis, small vessel ischemicdisease, and dementia due to HIV among others, a fronto-subcortical syndrome with characteristic behavioral andcognitive features such as executive functioning deficits,bradyphrenia, abulia, apathy, and encoding problems

Among gray matter structures, the prefrontal tex is the latest to fully develop, extending into youngadulthood, and thefirst to decline heading into to oldage John Hughlings Jackson termed this pattern offunctional decline“dissolution”, namely, those func-tions which appear last in evolutionary terms, andwhich emerge later in human development, are themost fragile and are among thefirst lost

cor-This late development of prefrontal-related tional systems coincides behaviorally with rapidchanges in social behaviors, decision-making, risk-taking behaviors, and the transition from child toadult in terms of responsibility Comparisons of frontalactivity with functional imaging between childhoodand adolescence show gender-specific increases inprocessing affective faces, for example (right frontalincreases for boys and bilateral increases for girls)[84] This activity tends to decrease and become morefocal in adults [85] Cognitive tasks show similar devel-opmental curves, with decreased and more focal frontalactivity in well-performing adults With aging, increasedfrontal lobe activity to cognitive demand is shownwith decreased efficiency in performance, suggest-ing more effort/resources are necessary to achieveperformance results [86] Clearly, consideration ofneuroanatomical development across the lifespan is

func-a criticfunc-al emphfunc-asis in driving our understfunc-anding ofthe behavior of life Integrating our rapidly advanc-ing ability to analyze structural and functionalchanges in neural network activity into theories oflifespan development is the future of ourfield

A lifespan review of developmental neuroanatomy

13

1 Gall FJ, Spurtzheim G.Recherches sur le système nerveux

en général et sur celui de cerveau en particulier Paris:

F Schoell; 1809

2 Broca P Nouvelle observation d’aphémie produite

par une lésion de la troisième circonvolution

frontale.Bull Soc Anat (Paris), 2e serie

1861a;6:398 407

3 Dronkers NF, Plaisant O, Iba Zizen MT, Cabanis EA

Paul Broca’s historic cases: high resolution MR imaging

of the brains of Leborgne and Lelong.Brain

2007;130:1432 41

4 Taylor J, ed.Selected Wrtitings of John Hughlings

Jackson London: Hodder and Stoughton, 1931

5 Lashley KS Factors limiting recovery after central

nervous lesions.J Nerv Ment Dis 1938;888:733 55

6 Lashley KS.Brain Mechanisms and Intelligence Chicago:

University of Chicago Press, 1929

7 Guillame DJ, Zhang SC Human embryonic stem cells: a

potential source of transplantable neural progenitor

cells.Neurosurg Focus 2008;24:E3

8 Heilman K, Valenstein E.Clinical Neuropsychology,

3rd edn Oxford: Oxford University Press; 1993

9 Filimonov IN Localization of functions in the cerebral

cortex.Nevropat I Psikhiat 1940;9

10 Luria AR, Teuber HL, Pribram KH.Higher Cortical

Functions in Man New York: Consultants Bureau; 1966,

13 Miller EK, Cohen JD An integrative theory of

prefrontal cortex function.Annu Rev Neurosci

2001;24:167 202

14 Dosenbach N, Fair DA, Cohen AL, Schlaggar BL,

Peterson SE A dual networks architecture of top down

control.Trends Cogn Sci 2008;12:99 105

15 James W What is an Emotion?Mind 1884;9:188 205

16 Rand B.The Classical Psychologists Boston: Houghton

Mifflin; 1912: 672 84

17 Ohman, A Presidential Address, 1985 Face the beast

and fear the face: animal and social fears as prototypes

for evolutionary analyses of emotion.Psychophysiology

1986;23:123 45

18 Fornari RV, Moreira KM, Oliveira MG Effects of

selective M1 muscarinic receptor antagonist

dicyclomine on emotional memory.Learn Mem

2000;7:287 92

19 Ross ED The aprosodias: functional anatomicorganization of the affective components of language inthe right hemisphere.Arch Neurol 1981;38:561 8

20 Golemen D.Emotional Intelligence New York: BantamBooks; 1995

21 Davidson RJ Affective style and affective disorders:perspectives from affective neuroscience

Neuropsychological perspectives on affective andanxiety disorder.Cogn Emot 1998;12:307 30

22 Mo Z, Moore AR, Filipovic R, Ogawa Y, Kazuhiro I,Antic SD, Zecevic N Human cortical neurons originatefrom radial glia and neuron restricted progenitors

J Neurosci 2007;27:4132 45

23 Pakkenberg B, Pelvig D, Marner L, Bundgaard MJ,Jorgen H, Gunderson G, Nyenhgaard JR, Regeur L.Aging and the human neocortex.Exp Gerontol2003;38:95 9

24 Braendgaard H, Evan SM, Howard CV, Gunderson

HJ G The total number of neurons in the humanneocortex unbiasedly estimated using optical dissectors

27 Pandey GN, Dwivedi Y, Ren X, Rizavi HS, Faludi G,Sorpso A, Palkovits M Regional distribution andrelative abundance of serotonin (2c) receptors in humanbrain: effects of suicide Neurochem Res 2006;31:167 76

28 D’haenen H, Bossuyt A, Mertens J, Bossuyt Piron C,Gijsemans M, Kaufman L SPECT imaging ofserotonin2 receptors in depression.Psychiatry Res1992;45:227 37

29 Moses Kolko EL, Price JC, Thase ME, Meltzer CC,Kupfer DJ, Mathis CA, Bogers WD, Berman SR, Houck

PR, Schneider TN, Drevets WC Measurement of

5 HT1A receptor binding in depressed adults before andafter antidepressant drug treatment using positronemission tomography and [11C]WAY 100635.Synapse2007;61:523 30

30 Levitan IB, Kaczmarek LK.The Neuron: Cell andMolecular Biology Oxford: Oxford University Press;2002

31 Monkhouse S.Cranial Nerves: Functional Anatomy.Cambridge: Cambridge University Press; 2006

32 Porges SW The polyvagal perspective.Biol Psychol2007;74;116 43

33 Porges SW Social engagement and attachment:

a phylogenetic perspective.Ann NY Acad Sci2003;1008:31 47

14

34 Annoni JM, Ptak R, Caldara Schnetzer AS, Khateb A,

Pollerman BZ Decoupling of autonomic and cognitive

emotional reactions after cerebellar stroke.Ann

Neurology 2003;53:654 8

35 Schmahmann JD, Weilburg JB, Sherman JC The

neuropsychiatry of the cerebellum: insights from the

clinic.Cerebellum 2007;6:254 67

36 Timmann D, Daum I Cerebellar contributions to

cognitive functions: a progress report after two decades

of research.Cerebellum 2007;6:159 62

37 Ackerman H, Mathiak K, Riecker A The contribution of

the cerebellum to speech production and speech

perception: clinical and functional imaging data

Cerebellum 2007;6:202 13

38 Winograd Gurvich C, Fitzgerald PB, Georgiou

Karistianis N, Millist L, White O Inhibitory control and

spatial working memory: a saccadic eye movement study

of negative symptoms in schizophrenia.Psychiatry Res

2008;157:9 19

39 Jones EG.The Thalamus, 2nd edn Cambridge:

Cambridge University Press; 2007

40 Shim YS, Kim JS, Shon YM, Chung YA, Ahn KJ, Yang

DW A serial study of regional cerebral bloodflow

deficits in patients with left anterior thalamic infarction:

anatomical and neuropsychological correlates.J Neurol

Sci 2008;266:84 91

41 Valenstein E, Heilman KM, Watson RT, Van Den Abell

T Nonsensory neglect from parietotemporal lesions in

monkeys.Neurology 1982;32:1198 201

42 Rosales RK, Lemay MJ, Yakovlev PI The

development and involution of massa intermedia

with regard to age and sex.J Neuropath Exp Neuro

1968;27:166

43 Preuss UW, Zetzsche T, Jager M, Groll C, Frodl T,

Bottlender R, Leinsinger G, Hegerl U, Hahn K, Moller

HJ, Meisenzahl EM Thalamic volume infirst episode

and chronic schizophrenic subjects: a volumetric MRI

study.Schizophr Res 2005;73:91 101

44 Shimizu M, Fujiwara H, Hiraol K, Namiki C, Fukuyama

H, Hayashi Y, Murai T Structural abnormalities of the

adhesion interthalamica and mediodorsal nuclei of the

thalamus in schizophrenia.Schizophr Res 2008 [Epub

ahead of print]

45 Carter CS Developmental consequences of oxytocin

Physiol Behav 2003;79:383 97

46 Grippo AJ, Cushing BS, Carter CS Depression like

behavior and stressor induced

neuroendocrine activation in female prairie voles

exposed to chronic social isolation.Psychosom Med

2007;69:149 57

47 Uhikova P, Paclt I, Vaneckova M, Morcinek T, Seidel Z,

Krasensky J, Danes J Asymmetry of basal ganglia in

children with attention deficit hyperactivity disorder

Neuro Endocrinol Lett 2007;28:604 9

48 Casey BJ, Epstein JN, Buhle J, Liston C, Davidson MC,Tonev ST, Spicer J, Niogi S, Millner AJ, Reiss A, Garrett

A, Hinshaw SP, Greenhill LL, Shafritz KM, Vitolo A,Kotler LA, Jarrett MA, Glover G Frontostriatalconnectivity and its role in parent child dyads withADHD.Am J Psychiatry 2007;164:1729 36

49 Isaacs EB, Gadian DG, Sabatini S, Chong WK, Quinn

BT, Fischl BR, Lucas A The effect of early human diet oncaudate volumes and IQ.Pediatr Res 2008;63:308 14

50 Aron AR, Durston S, Eagle DM, Logan GD, Stinear CM,Stuphorn V Converging evidence for a fronto basalganglia network for inhibitory control of action andcognition.J Neurosci 2007;27:11860 4

51 Murray EA The amygdala, reward and emotion.TrendsCogn Sci 2007;11:489 97

52 Blanchard DC, Blanchard RJ Innate and conditionedreactions to threat in rats with amygdaloid lesions.AnnuRev Psychol 1972;39:43 68

53 Meletti S, Tassi L, Mai R, Fini N, Tassinari CA, Russo GL.Emotions induced by intracerbral electrical stimulation ofthe temporal lobe.Epilepsia 2006;47: 47 51

54 Chen SW, Shemyakin A, Wiedenmayer CP The role ofthe amygdala and olfaction in unconditioned fear indeveloping rats.J Neurosci26:233 40

55 Packard MG, Teather LA Amygdala modulation ofmultiple memory systems: hippocampus and caudateputamen.Neurobiol Learn Mem 1998;69:163 203

56 Tebartz L, Ebert D, Hesslinger B Amygdala volume statusmight reflect dominant mode of emotional informationprocessing.Arch Gen Psychiatry 2007;64:251

57 Scoville WB, Milner B Loss of recent memory afterbilateral hippocampal lesions.J Neurol NeurosurgPsychiatry 1957;20:11 21

58 Corkin S What’s new with the amnesic patient H.M.?

Nat Rev Neurosci 2002;3:153 60

59 Grassi Oliveira R, Ashy M, Stein LM Psychobiology ofchildhood maltreatment: effects of allostatic load? RevBras Psiquitr 2008;30:60 8

60 Guimaraes CA, Bonilha L, Franzon RC, Li LM, Gendes

F, Guerreiro MM Distribution of regional gray matterabnormalities in a pediatric population with temporallobe epilepsy and correlation with neuropsychologicalperformance.Epilepsy Behav 2007;11:558 66

61 Merker B Consciousness without a cerebral cortex: achallenge for neuroscience and medicine.Behav BrainSci 2007;30:63 81

62 Glasser MF, Rilling JK DTI tractography of the humanbrain’s language pathways Cereb Cortex 2008 [Epubahead of print]

A lifespan review of developmental neuroanatomy

15

63 Jorgens S, Kleiser R, Indefrey P, Seitz RJ Handedness

and functional MRI activation patterns in sentence

processing.Neuroreport 2007;18: 1339 443

64 Francks C, Maegawa S, Laurèn J, Abrahams BS, Velayos

Baeza A, Medland SE, Colella S, Groszer M, McAuley

EZ, Caffrey TM, Timmusk T, Pruunsild P, Koppel I,

Lind PA, Matsumoto Itaba N, Nicod J, Xiong L,

Joober R, Enard W, Krinsky B, Nanba E, Richardson AJ,

Riley BP, Martin NG, Strittmatter SM, Möller HJ,

Rujescu D, St Clair D, Muglia P, Roos JL, Fisher SE,

Wade Martins R, Rouleau GA, Stein JF, Karayiorgou M,

Geschwind DH, Ragoussis J, Kendler KS, Airaksinen

MS, Oshimura M, DeLisi LE, Monaco AP LRRTM1 on

chromosome 2p12 is a maternally suppressed gene that

is associated paternally with handedness and

schizophrenia.Mol Psychiatry 2007;12:1129 39

65 Belin P, Zatorre RJ Adaptation to speaker’s voice in

right anterior temporal lobe.Neuroreport

2003;14:2105 9

66 Fox NA, Davidson RJ Hemispheric substrates for affect:

a developmental model In Fox NA, Davidson RJ, eds

The Psychobiology of Affective Development Hillsdale,

NJ: Erlbaum; 1984

67 Fox NA, Schmidt LA, Calkins SD, Rubin KH, Coplan RJ

The role of frontal activation in the regulation and

dysregulation of social behavior during the preschool

years.Dev Psychopathol 1996;8:89 102

68 Fox NA, Calkins SD, Porges SW, Rubin KH Frontal

activation asymmetry and social competence at four

years of age.Child Dev 1995;66:1770 84

69 Dekaban AS, Sadowsky D Changes in brain weights

during the span of human life: relation of brain weights

to body heights and body weightsAnn Neurol 1978;

4:345 56

70 Williams LJ, Rasmussen SA, Flores A, Kirby RS,

Edmonds LD Decline in the prevalence of spina bifida

and anecephaly by race/ethnicity: 1995 2002.Pediatrics

2005;116:580 6

71 Tarazi RA, Zabel TA, Mahone EM Age related

differences in executive function among children with

spina bifida/hydrocephalus based on parent behavior

ratings.Clin Neuropsychol 2007 [Epub ahead of print]

72 Dennis M, Jewell D, Drake J, Misakyan T, Spiegler B,

Hetherington R, Gentili F, Barnes M Prospective,

declarative, and nondeclarative memory in young

adults with spina bifida J Int Neuropsychol Soc

2007;13:312 23

73 Clancy RR, Bergqvist AGC, Dlugos DJ Neonatal

electroencephalography In Ebersol JS, Pedley TA, eds

Current Practice of Clinical Electroencephalography,

3rd edn Philadelphia, PA: Lippincott Williams &

Williams; 2003:160 234

74 Scher MS, Johnson MW, Holditch Davis D Cyclicity ofneonatal sleep behaviors at 25 to 30 weeks

postconceptional age.Pediatr Res 2005;57:879 82

75 Schleussner E, Schneider U Developmental changes

of auditory evokedfields in fetuses Exp Neurol2004;190:59 64

76 Frey U, Morris RG Synaptic tagging and long termpotentiation.Nature 1997;385:533 6

77 Barco A, Lopez de Armentia M, Alarcon JM

Synapse specific stabilization of plasticity processes: thesynaptic tagging and capture hypothesis revisited

10 years later.Neurosci Biobehav Rev 2008;32:831 51

78 Schoenemann PT, Sheehan MJ, Glotzer LD Prefrontalwhite matter volume is disproportionately larger inhumans than in other primates.Nat Neurosci 2005;8:

242 52

79 Courchesne E, Chisum HJ, Townsend J, Cowles A,Covington J, Egaas B, Harwood M, Hinds S, Press GA.Normal brain development and aging: quantitativeanalysis at in vivo MR imaging in healthy volunteers.Radiology 2000;216:672 82

80 Basser PJ, Matiello J, LeBihan D MR diffusiontensor spectroscopy and imaging.Biophys J 1994;66:259 67

81 Qiu D, Tan LH, Zhou K, Khong PL Diffusion tensorimaging of normal white matter maturation from latechildhood to young adulthood: voxel wise evaluation ofmean diffusivity, fractional anisotropy, radial and axialdiffusivities, and correlation with reading development.Neuroimage 2008 [Epub ahead of press]

82 Abe O, Aoki S, Hayashi N, Yamada H, Kunimatsu A,Mori H, Youikawa T, Okubo T, Ohtomo K Normalaging in the central nervous system: quantitative MRdiffusion tensor analysis Neurobiol Aging 2002;23:

433 41

83 Tullberg M, Fletcher E, DeCarlie C, Mungas D, Reed BR,Harvey DJ, Weiner MW, Chui HC, Jagust WJ Whitematter lesions impair frontal lobe function regardless oftheir location.Neurology 2004;63:246 53

84 Yurgelun Todd DA, Killgore WD Fear related activity

in the prefrontal cortex increases with age duringadolescence: a preliminary fMRI study.Neurosci Lett2006;406:194 9

85 Monk CS, McClure EB, Nelson EE, Zarahn E, Bilder

RM, Leibenluft E, Charney DS, Ernst M, Pine DS.Adolescent immaturity in attention related brainengagement to emotional facial expressions

neuropsychology Jane Holmes Bernstein

“A single good model is worth a thousand empirical studies”

James Heckman (Nobel Prize, Economics, 2000)

quoted by David Kirp [1]

“Good models are like good tools: they do a certain job rea

sonably well… simple models that work well for a wide variety

of jobs are especially valuable… (they yield) islands of concep

tual clarity in the midst of otherwise mind numbing complexity

and diversity”

Richerson and Boyd [2]Introduction

On what grounds does a hard-nosed number-crunching

economist make such a claim? What does he mean?

What are the implications for the elaboration of the

knowledge base? For clinical practice?

A model is a tool for thinking, for organizing a

body of data into a theoretically coherent construct

whose validity can be tested Thinking in both

research and clinical arenas is based on a constant

interaction between models and evidence The

chal-lenge of empirical data (evidence) is that at any one

point there may be much to make sense of Data are

not always internally consistent; and, until established

by multiple replications across data sets, evidence

is constantly subject to discussion, argument, and

change Models may not be subject to as rapid change

as the evidence base They cannot, nonetheless, be

static: as evidence accumulates, models must be

scru-tinized and reformulated

There are two major sources of change in science

One is the shift in the zeitgeist, the way in which people

view the world, to which scientific developments

con-tribute, but do not solely define; the second derives

from developments in technology Both of these are

shaped by the modeling⇆evidence transactions that

are critical to the advancement of knowledge and

influence them in turn

Change in the zeitgeist and the advent of new

technologies have had major implications for the

behavioral neurosciences In the modern era,

behav-ioral neurology and neuropsychology got their start in

the observations of language breakdown made by Dax,Broca, and Wernicke in the late nineteenth century,and the nature of language has remained a focus ofintense scrutiny This is easy to understand: our lan-guage capacities are central to our existence, and untilrecently their believed uniqueness reinforced habits

of thought that put human beings at the pinnacle

of a hierarchical view of life However, in the wake ofthe “Modern Synthesis” of evolutionary theory andgenetics, the intellectual context in which we viewour position in the natural world has changed dramat-ically, and the implications of the modern synthesishave gained traction in scientific thinking What isperhaps the most important– and hard-won – impact

is the recognition that humans do not represent somesort of pinnacle of life on earth This change in view-point has opened thefloodgates for cross-species com-parisons of behavior and adaptation, which allow us

to explore in greater detail (and with much greaterhumility) what we share with other organisms, andhow we as a species were shaped by natural forces thatadapted us to our environments over time The range

of models available to extend our thinking has ingly expanded many-fold The inclusion of an evolu-tionary framework has great potential for integratingmultiple disciplines [3]

accord-The advent of modern neuroimaging technologyhas in the last several decades also changed the inves-tigative landscape significantly and promoted progress

in behavioral neuroscience at a rapid rate Multipleforms of neurodiagnostic imaging have been intro-duced, assessing structure and function at the ana-tomical level (computed tomography (CT), positronemission tomography (PET), magnetic resonanceimaging (MRI)); the physiological level (single photonemission computed tomography (SPECT), quantita-tive electroencephalography (qEEG) and transcranialmagnetic stimulation (TMS)); and the functional level(functional magnetic resonance imaging (fMRI), dif-fuse tensor imaging (DTI)) The ability to image thebrain in action via fMRI, tractography and TMS

has led to a remarkable rapprochement of

neuro-science and experimental psychology – and to the

new cognitive neurosciences (developmental, social

cognitive, affective) Other developments that augur

well to advance our understanding of behavior come

from such different disciplines as genetics and

com-puter modeling Microarray technologies that support

multivariate genetic analysis and gene expression

mapping are being used to determine the role of

genes and epigenetic processes in the risk for and

manifestation of diseases and disorders, both medical

and psychiatric [4] Computer models range from the

cellular level to that of cognition and behavior [5]

The technology-supported paradigms that are

increasingly available to support the testing of

pro-posed models also bring their own constraints

Computer modeling is a powerful technique that can

answer questions of how things may work, but it does

not necessarily address what actually works or why

Similarly, functional neurodiagnostic imaging may

provide detailed information about discrete

compo-nents of complex behavior, but it is not easy to

extrap-olate from behavior that occurs “in the tube” to

behavior that is elicited in response to the meaning,

goals, and intentions of the individual in the world

There are considerable hurdles to be overcome in fully

understanding the data obtained from these new

tech-nologies, both methodologically (what, in the neural

substrate, is being indexed– exactly?); and practically

(what is the relationship between behavior observed in

the specific technology setting and behavior observed in

the real world?) Nonetheless, these paradigms allow

us to ask questions that we have not been able to ask

before, and, in so doing, further our understanding of

brain–behavior and structure–function relationships

Modeling in development

The core concept of development is that of

dynamic change over time in response to experience

Developmental models have to incorporate concepts

of change– but also of continuity/stability The genetic

processes that facilitate selection allow organisms to

change more or less rapidly to meet changing

condi-tions in their environments Absent such external

change, however, genetic processes function to

main-tain the match between the organism and its niche

Concepts of development imply a“start-state” to

change from and an“end-state” to change to [6] The

start-state for the human organism is the information

in the genome This represents the end-state of themacro-developmental processes of evolution Modelbuilding in development thus addresses two questions:one – at the species level – considers the evolution

of the brain to this point, asking what changes overtime have shaped the brain– and the behavior – of thespecies The other– at the individual level – asks howand when species-specific brain organization andbehavior is acquired by the individual

These questions cannot be addressed without ence to the contexts that have constrained and canal-ized developmental trajectories over time Models

refer-of development– both evolutionary and ontogenetic –entail an environment in which the organism acts

At the evolutionary level, the environment has shapedthe species’ behavioral repertoire, providing biologi-cally prepared capacities that must be activated inresponse to particular environmental demands Atthe individual level, it is experience with this particularenvironment that shapes the neural architecture sup-porting the individual’s behavior Over time and underspecific environmental forces, the individual acting inconcert with others in a population has the potentialfor rerouting the trajectory of the species

The long history of chronic polarization aroundthe nature–nurture debate has been rendered moot inmany aspects by thefindings of modern neuroscience.Since the formulation of the modern synthesis– and inspite of constant critique from both within and outsidescience – our understanding of the relationship ofintrinsic neurobiological characteristics and extrinsicenvironmental influences is that it is one of vital inter-dependence Both nature and nurture must operatetogether and questioning must be guided by the twoqueries offered by Mayr [7]: how does the organismwork? and why is it advantageous to work that way?The concept of development is one that has notbeen easy to integrate at the behavioral level wherehumans are the focus of investigation Developmentalthinking runs counter to long-prevailing concepts ofthe nature of cognition Psychological theory in theWestern tradition has been dominated by the idea

of the autonomous individual as the center of edge and cognition [8] The fundamental assumption

knowl-is that “the boundaries of the individual provide theproper framework within which psychological pro-cesses can be adequately analyzed” [9] Cognition isthus conceptualized as a set of processes that are inter-nal and accessible only to the person to whom theybelong Furthermore, in Western thought, scientific

18

investigations have been strongly shaped by the

Platonic essence tradition and conducted in terms of

dichotomous-sources-of-variation strategies The

for-mer is simply not a developmental concept; the other

requires careful evaluation of the appropriateness of

its application to developmentally framed questions

In neuropsychology, a major challenge to the

con-struction of developmental models is the specialization

of the adult human brain This view was derived from

observation of the selective disruptive effects of brain

lesions in parsing behavioral capacities in the

neurol-ogy tradition and from investigative paradigms that

parse target behavioral capacities into subcomponents

in the experimental psychology tradition These two

investigative approaches quickly merged into what is

now known as cognitive neuroscience The primary

strategy has been one of dissociation As behavior was

subject to more and more dissection, brain

organiza-tion was revealed to be highly specialized– and

inter-preted as mediated by special-purpose modules that

function more or less independently, although the

nature of the modules and the degree of their

inde-pendence remain the subject of debate

When the focus is on brain development and

organization in children, however, there is a problem:

the modules of the adult cognitive architecture cannot

be presumed to be present They have to emerge in

some process of modularization that takes place over

time Thus, models based on a view of adult modular

architecture cannot be correct as a description of the

child’s developing capacities Nonetheless, such

mod-els have proved over and over again to be very

seduc-tive, and have been utilized on numerous occasions to

attempt to make sense of pediatric brain function

It has been unfortunate– though not surprising –

for the developmental behavioral sciences that the

neural specialization model of the adult brain meshed

perfectly with the (up to recently) dominant

“cogni-tive” paradigm in modern Western psychology and led

to the“downward extension” of adult models – both

of brain organization and behavioral measurement–

into the pediatric arena However, it did so because

the model as it applied to behavioral measurement

meshed perfectly with what was already “on the

ground” Measurement tools for children were

con-structed in the shape and form of those derived for

adults in the cognitive tradition

The influence of the modern synthesis on thinking

across all branches of scientific endeavor has, however,

paved the way for a re-evaluation of brain functioning

and organization Developmental thinking in lar benefits from this, and is starting to act as a power-ful antidote to the influence that has existed to datefrom both cognitive models of neural organizationand behavioral measurement tools that are con-structed in an older cognitive tradition

particu-Models in clinical practiceThe increased influence and application of develop-mental modes of thinking in understanding behavior

is particularly exciting for the clinician The guidingquestions at the level of the organism are those thatthe pediatric clinician wrestles with on a daily basis inworking with an individual: how does an organismachieve adaptive success? What is an optimal out-come? What is needed to facilitate this? What factorscould constrain the individual from reaching theexpected end-state? What is the role of the individual’sunique experiences to date and opportunities in thefuture? And for the clinician specifically: how can

I best intervene to maximize the outcome?

Until relatively recently, clinicians have been poorlyserved by the neuropsychological knowledge base.The“individual-as-cognizer” model and “dichotomous-sources-of-variation” methodologies do not enrich theportrait of a real person in the real world, and so fail tomeet the mandate of clinicians– to match the personmore effectively to the demands of his or her world.This mismatch is one source of the failure of clinicians

to respond enthusiastically to evidence-based practicethinking and guidelines

Nonetheless, in the modern era, clinical practicemust be evidence-based Such a statement hardlyseems controversial: with the welfare and lives ofpeople at issue, clinicians can hardly go around mak-ing up treatments on an ad hoc basis However, callsfor evidence-based medicine and clinical psychologicalpractice are all too often resisted by clinicians; clinicalpractice guidelines may be treated as nonrelevant to anindividual’s practice; and long lags can occur betweenthe identification of new successful treatments andtheir application This gap between practice guidelinesderived from research knowledge and the actualbehavior of clinicians is of concern Arguably, mentalhealth clinicians are even more vulnerablethan physicians to resisting standardized guidelines,inasmuch as the focus of treatment/intervention isbehavior and an individual’s behavioral repertoire ishighly individual, constantly influenced by transactionsDevelopmental models in pediatric neuropsychology

19

with the full range of intrapersonal and interpersonal

environmental variables that are more or less unique to

him or her

One reason for the resistance seems to be a lack of

consensus about the nature of evidence-based practice

(EBP) EBP is widely viewed as emphasizing data

(evi-dence) collected under research conditions, with the

randomized clinical trial all too often being held up

as the gold standard, in spite of the availability of

detailed analyses of a range of relevant data sources

(effectiveness studies, single-subject designs,

process-outcome studies, qualitative analyses, hypothesis

gen-eration/evaluation, metaanalyses and the like) The

label “evidence-based” has focused the discussion

on research knowledge even though the Institute of

Medicine’s defining report Crossing the Quality Chasm

[10] provided a much more nuanced view of the

endeavor, one that requires the integration of “the

best available research evidence, clinical expertise,

client values and available resources” The

contri-bution of practice-based evidence has also been

out-lined Nonetheless, in spite of this clear recognition of

their critical role in EBP, many clinicians continue to

resist evidence-based clinical practice guidelines,

argu-ing that they are not responsive to the experience of

the individual patients they actually see in the office,

and thus cannot be a substitute for the practitioner’s

knowledge and experience with individual patients

There are reasons for this attitude among clinicians

that need to be examined– and taken seriously by both

research teams and clinical practitioners

One very substantial problem for the application to

clinical settings of the data collected in research

inves-tigations is the mismatch between the two modes of

thinking Research investigations seek universals, are

variable-centered and aim to maximize internal

valid-ity Clinical investigations deal with individuals, are

person-centered and have as a primary goal the

max-imization of external validity The products of the one

cannot simply be transferred wholesale to the other

Standards for research investigations (especially in the

behavioral or mental health domains) are often too

rigorous to be useful in real conditions, a situation

that easily provokes resistance to standards-based

care How is this tension resolved? How is

research-obtained knowledge applied to the individual person

who seeks care?

The interpretation of the research product to the

real world setting of the individual who seeks care

requires that thoughtful clinicians build coherent

models of their clinical behavior Indeed, cliniciansare master makers of models Like everyone else, they

do it all the time As clinicians, however, they have

a responsibility to know that they are modeling andgenerating hypotheses whenever observing behavior.Modeling does not await the evaluation of systemati-cally collected data in the clinical interview Cliniciansgenerate hypotheses on first meeting the patient/client – or reading the medical record Failing torecognize that they are doing so means that theyalso fail to evaluate the many sources of bias (social/interpersonal, methodological) that can potentiallyundermine their“judgment under uncertainty” [11].Model-building – rigorous, systematic and prin-cipled– is at the core of clinical expertise In evidence-based practice, the “big E” of Evidence must becomplemented by the“big E” of Expertise Researchevidence is useless if the practitioner does not knowhow to use it– which data to select, when and how toapply them Indeed, clinicians typically organize theirthinking within a theoretical framework to do justthis [12] The core of the clinician’s expertise then is

a theory-based“good (working) model” as advocated

by Heckman and it is the need for a thinking structurethat guides both the selection and the application ofrelevant knowledge that is the emphasis of his boldstatement

Both of the“big Es” must be subjected to the sameintensity of methodological scrutiny The latter is,however, frequently given short shrift in this regard.Training in clinical neuropsychology in particularcan be very vulnerable, on the one hand, to an over-emphasis on exciting developments in neuroimagingtechniques and cognitive neuroscience and, on theother hand, to a more or less rigid application of thepsychological test batteries preferred by a trainingsite – with at times less, or even no, comprehensiveinstruction in the nature of clinical work itself True, it

is hard to encompass in a few years of training all ofthe information currently available in an excitingfieldlike neuropsychology, but clinical neuropsychologiststraining the next generation of professionals need toprovide students with afirm theoretical foundation ofthe assessment process itself that will guide their think-ing as the knowledge base with which they work grows,changes, and is refined

The good working model guides clinical practice.The model is“working” to the extent that it is not fixed

in stone but must be subject to ongoing scrutiny andrevised as new knowledge becomes available In the

20

clinical setting, the model that you use guides, but

can also seriously limit, what you look for, what you

see and how you interpret your observations

Clinically, the utility of a model depends on its ability

to account both for normal behavioral functioning

and for different patterns of behavioral breakdown,

to be implemented in assessment strategies, and to

provide a principled approach to management and

intervention

Actually, however, for the clinician “the good

working model” is a misnomer The clinician typically

works within a theoretical framework in which more

than one working model is required to encompass

the range of activity As a clinical neuropsychologist

working with children, I parse the domain in which

I am working into three primary components: the

organism, the potential threats to development to

which the organism is subject (including the impact

of diseases/disorders and that of adverse

environmen-tal experience), and theassessment strategy The model

of the organism– how the organism works – is central,

shaping the understanding of how threats to

develop-ment have their impact, and determining how the

assessment of behavior proceeds The organism is

viewed through the lens of the

brain-context-development matrix [13] The model of the organism

necessarily incorporates models of brain, models

of context (physical, psychological) and models of

development

Modeling the organism The primary model

guid-ing the clinician is the model of the organism in

question How does this organism work? All

assess-ment is based on current views of the expected

capaci-ties of the individuals under study There is little point

in trying to evaluate behavior in the absence of a sense

of what behavior the organism is capable of, nor can

the impact of a given disorder be assessed without a

sense of the organism’s capacities under typical

conditions Models of neuro psychological

function-ing must be based onbrain; an understanding of brain

cannot be achieved – as I have argued elsewhere –

without an analysis of context; models of the

neuro-behavioral capacities of the child must reflect its

developing status and thus must incorporate

development

Within this larger brain-context-development

matrix for modeling the organism, there are two

other strands of investigation in which specific models

are invoked to help organize the available data and set

up the questions that will lead to greater understanding

of the concepts involved One set of models attempts tospecify how brain is related to behavior (brain–behav-ior relationships) Another seeks to account for thenature of specific behavioral capacities such as lan-guage, spatial cognition, social behavior, executivecapacities and so forth As previously noted, thesemodels draw from neurology and neuroscience onthe one hand and from experimental psychology onthe other Currently,“neuropsychology” has given way

to“neuroscience” and modeling of specific behavioralcapacities rarely takes place without reference to thepotential neural substrates that support the behavior inquestion Indeed, the cross-fertilization provided bythese two sources of models is what has given thefield its power as a source of new insights In theclinical setting the contribution of these models isfurther extended by models drawn from clinical psy-chology All are brought together under the umbrella

of the model of the assessment process itself with thegoal of making as comprehensive and nuanced adescription of the individual as possible as the basisfor acting to promote his or her optimal adaptation inthe future

Modeling the disorders The disorders that threatenthe lives and the optimal development of children aredifferent from those that affect adults Structuralanomalies, genetic syndromes, and prematuritychange the course of development from the beginning.Different types of brain tumor and seizure disorder areseen at different ages, require different treatments andhaving different consequences for behavior Even theconditions that seem comparable across ages– stroke,head injury– have different types of outcomes whenthey occur in a developing brain (see the chaptersconcerning traumatic brain injury in this volume).The core principle is that the neuropathologies ofchildhood occur in the context of dynamic changeover the course of development and thus the pathologybecomes part of the developmental course Behavioraldevelopment can be derailed and behavioral outcomeschanged Genetic and structural disorders set up con-ditions for alternative developmental trajectories; lateracquired derailments have potential for resulting inso-called“late effects” Models of brain–behavior rela-tionships that derive their data from neuropathologymust address the altered dynamics of the brain–expe-rience interactions of the child with changed neuralcapacity Determination of such relationships in thechild cannot proceed without reference to develop-mental processes, both typical and atypical

Developmental models in pediatric neuropsychology

21

The knowledge base of developmental

models

In neuropsychology, developmental modeling calls

on an extended knowledge base that can be roughly

parsed by the so-called“wh” questions: what, where,

when, how The knowledge bases that address thewhat

question are those of the behavioral sciences,

psychol-ogy and cognitive neuroscience Thefindings of these

disciplines are central to the discipline of

neuropsy-chology and have been extensively outlined in a variety

of texts, both comprehensive and focused on specific

domains In recent years, as neuropsychological

investigations of children’s behavior have increased,

relevant texts have focused on neuropsychological

development in the child To date, these have largely

been the work of clinicians and have focused on the

behavioral impact of threats to normal development

in the presence of disease or disorder and/or the

strategies needed to evaluate and treat children who

present for clinical services The where question is

answered by the neurosciences, embracing biology,

physiology, and chemistry; neuroanatomy and

embry-ology; neuropathembry-ology; and behavioral neurology

Again, the range of texts available is extensive and

specific systems warrant their own extended

descrip-tions Neuropsychologists gain familiarity with the

what and the where knowledge bases as part of their

training – and develop models for future research

investigations or for clinical practice based on this

emphasis However, when the goal is modeling of

developmental processes, the what and where data

require supplementation, by data addressing when

andhow

Addressing when in developmental

modeling

Thewhen question is addressed through the

knowl-edge bases of the evolutionary sciences, developmental

psychology and the developmental neurosciences

These disciplines all seek to understand the dynamic

processes that have created and continue to shape

biological organisms Thewhen question is concerned

with time passing It deals in start-states and end-states

and the nature of the journey between them

The start-state of the individual’s journey is

the end-state of the macrodevelopmental processes

of evolution Evolution is affected by changes in

developmental mechanisms over time Successful

adaptation at any point in a species’ or an individual’sdevelopmental trajectory entails both flexibility andstability The understanding of development in bothits phylogenetic (evolutionary) and its ontogenetic(individual) manifestations requires appreciation ofthis dramatic tension at the core of the construct:change and continuity Development proceeds via pro-cesses that maintain and reinforce existing structures,

as well as setting up the conditions for the formation ofnew ones– with the latter always constrained by whatpre-exists At the‘macro’ level of evolutionary develop-ment, selection acts to maintain those morphologiesand behaviors that support successful adaptation to

a given niche by removing fitness-reducing alleles –constraining variability for stable functioning incurrent contexts, as well as to facilitate new responsi-tivity to changed environmental conditions– providingadaptiveflexibility in future contexts At the individuallevel, this involves the products of biological evolution–already evolved proclivities or preparedness to learn–and of epigenesis– the expression of the potentiality

in response to the actual– and unique – experience ofthe individual

Across evolutionary time, behavior is selected

to solve problems that are species-relevant and topromote optimal adaptation to the setting in whichthe animal finds itself The potent force is that

of survival – of the species and of the individual.Protection, nutrition and reproduction are central –and the structures, both neural and behavioral,selected to support them are critical substrates for all

of our subsequently acquired behavioral capacities.Acquisition of the species-specific behavioral reper-toire will be the developmental task of the individual.Optimal adaptation for any organism is defined

by the environment in which it lives Both the largerplanetary environment with its specific physical prop-erties and more specific ecological niches shape theevolution of species For humans, for example, theanthropological record reveals a relationship betweenthe inhospitableness of the environment and thesize of the human brain and paleoclimatological datareveal that periods of harsh environmental conditionsare correlated with rapid changes in human brain[14,15] Climate variation demands behavioralflexi-bility for success– and brain power to facilitate it Thishighly flexible adaptive repertoire of humans meansthat they can respond not only to different physicalconditions, but also to highly complex, non-physicalenvironments of their own making, those that are

22

shaped by social organization and language The

acquisition of culture that these facilitated then shaped

the modern human brain-mind, an impact that cannot

easily be overstated The point at which genes and

culture became intertwined in a mutual relationship

can be considered a major transition in human

evolu-tion [2]

The evolution of culture – the shared meanings

(knowledge, beliefs, values) embedded in systems of

kinship, cosmology, law and ritual– itself depends on

Darwinian principles operating within and between

populations Human beings transmit large amounts

of information by imitation, by instruction, and by

verbal communication This leads to an extraordinary

range of behavioral variation, even in the same

envi-ronment, on which selection processes can work

Indeed, the ability both to transmit and to receive

this information shapes the brain to be more

respon-sive to the information itself Cultural evolutionary

processes in specific environments lead to the

evolu-tion of uniquely human social instincts, and the ways

in which we learn, feel and think shape the culture in

which we live Those cultural variants that are most

easily learned, remembered and/or taught then tend to

persist and spread The rate of cultural change is

con-strained by evolved rate of brain development and rate

at which culture can be acquired by learning Broadly

speaking, at this point in our social and economic

evolution, it takes 15 to 25 years to complete physical

development and cultural learning, with the years

from twenty tofifty being the window for fully realized

cultural transmission (allowing for the erosion of

cognitive capacity with greater age) The importance

of the cultural environment to the evolution of the

human species is echoed in the development of

the individual Family environment and resources,

parenting/caretaking style and beliefs, personal and

societal beliefs and values, all shape the acquisition of

thinking, social, and regulatory capacities in the

indi-vidual, and can influence in significant ways the

response to disease or adversity These effects can be

seen at a basic biological level– the impact of stress

on fundamental neuroendocrine systems [16] or of

adverse conditions on the development of

neuropep-tide systems critical for social behavior [17] They can

be seen at the level of acquisition of the behavioral

repertoire, for example early adversity on subsequent

neurobehavioral development [18] and the impact of

socioeconomic variables on the acquisition of basic

skills in young children [19] They can also influence,

both positively and negatively, outcomes post-injury,i.e., family variables have bidirectional influence onbehavioral outcomes in pediatric head injury [20]

The end-state of the evolutionary journey then isthe start-state of the individual Evolution prepares thebiological organism for its role as a member of thespecies to which it belongs The individual’s develop-mental trajectory is the journey from biological pre-paredness to the end-state of the adult in the particularenvironment obtaining at the time Modeling thisjourney requires consideration both of models ofthe end-state to be achieved and of models of thejourney itself– and of the interaction between them.Constraints imposed by the end-state shape the under-standing of the nature of the architecture on arrival–and potentially redefine the end-state given its expres-sion across time, within a particular environment Asnew knowledge is acquired in the biological neuro-sciences, the realities of how biological mechanismsand processes constrain and reshape models of theoverall system and its construction are more deeplyappreciated In this way developmental thinking influ-ences cognitive science

Developmental psychology has actively generatedmodels to account for the development of cognition.These range from nativist, innate specification ofbehavioral capacities/maturation of genetically speci-fied forms; to associationist, experience with properties

of objects in the world leads to mental associations ofthose properties; toconstructivist, integration of intel-lect and senses to create constructed representations.For many theorists, the acquisition of new knowledgewithin a social context is preeminent– and needs to beexplained As a result, sociocognitive models that aim

to integrate the social dimension into the other modelsare the focus of ongoing research [21] With the advent

of new modes of thought and new technologies inthe post-modern synthesis era, such model-building

is now the province of the “developmental sciences” and, as such, models are being tested andreformulated in the light of newfindings in the widerbrain sciences In this context, combined models seemlikely to have a betterfit with the workings of otherprinciples that are widely applicable to the building

neuro-of brain and behavior The combination neuro-of nativistand constructivist models as explicated most fully

by Karmiloff-Smith et al [22] appears to align mostcomfortably with the“gene + plasticity” story

The nativist + constructivist position is, however,being further extended to integrate the role ofDevelopmental models in pediatric neuropsychology

23

experience and context even more fully into a model of

the individual actually behaving The observation that

the sea squirt, one of the workhorses of neural science

research, only has neural cells during the time it is

moving around, which it then digests once it enters

its stationary life stage, invites consideration of the

brain as a system not for cognizing but for action

[23] and has provided a rationale for the development

of ecologically framed dynamic systems models of the

mind This perspective argues against the inherent

reductionism of the cognitive neurosciences paradigm,

explicitly resists the decontextualized representations

of mind that derive from the classical understanding,

and proposes that the mind is“an emergent property

of interactions of brain, body and world” [24],

prompting systematic study of the dynamics of

trans-actions between them Without reference to the

contexts in which behavior– and the processes that

support it – has been forged (from the biological

neurosciences), the cognitive neurosciences fail to

sit-uate their findings in a model of how the organism

actually behaves, a powerful constraint on any theory

of human behavior Integrating evolutionary thinking

with cognitive and dynamic systems modeling holds

promise to achieve a more comprehensive account [3]

Addressing how in developmental

modeling

The how question accesses two major mechanisms

critical for the building of the neural and cognitive

architecture: genes and epigenetics and plasticity

Answering thehow question also requires some sense

of the framework within which these processes are

assumed to work A discussion of developmental

mod-els cannot proceed without reference to a concept that

has polarized much debate– that of modularity How

one understands this concept shapes the theoretical

framework within which models are generated– and

how specific processes are deemed to contribute In

1983, Fodor [25] used this concept in making a

dis-tinction between perception and cognition– between

input systems that are encapsulated, mandatory, fast

operating, and hardwired, and central systems that

are unencapsulated and domain-neutral The former

he described as modular in architecture The concept

proved enticing: its match with the specialization

models of brain–behavior relationships in the adult

human brain derived from neuropsychology, and

behavioral neurology investigations led to it being

extended well beyond Fodor’s initial formulation tocharacterize “cognitive” domains such as language,spatial processing, and social processing, in addition

to basic sensory inputs Modularity in the sense ofcommitted processing units is widely accepted as

a core feature of the cognitive architecture of theadult human brain Fodor’s “cognition” has beenreplaced by a modular concept of executive functions

or processes at the behavioral level (Baddeley’s centralexecutive) that itself has been subject to modularfractionation at the neural level

The concept– and its cognitive tradition – has alsobeen adopted into the evolutionary context, being used

in the evolutionary psychology sense of biologicalpreparedness, the end-state of macro (evolutionary)development The innate proclivities, the products

of our evolutionary history that prepare us to meetspecies-specific behavioral expectations, are consideredmodules The evolutionary psychologists Cosmidesand Tooby have proposed a multiplicity of mentalmodules, arguing that the modern human mindevolved under selection pressure in Pleistocene envi-ronments and is made up of a wide range of modulesthat address specific adaptive challenges in that setting[26] The modules are now not only not restricted

to sensory inputs, but are“content-rich” in that theyprovide both rules for solving problems and the infor-mation needed to do so In this view the developmentalmodel proposes that the modules come on line atdifferent times in ontogenetic development

It is not clear that the concept of modularity willcontinue to prove an optimal description of adultbrain organization as greater knowledge of neuralfunctioning emerges The behavioral modules ofcognition – linguistic, spatial, social – are no longerthought to be supported in some sort of modularfashion at the neural level: network models whereinbehavioral functions are supported by transactionsamong systems with nodes in different networks arenow being widely explored The same ‘nodes’ mayparticipate in more than one network; given networksmay support a range of different behavioral functions.Other data available now, however, significantlyconstrain the“promiscuous modularity” mindset [27]and provide further reason for strong influenceexerted on the thinking of neuropsychologists by theobservations of specialization of function manifest inadult behavior to be resisted At deeper levels of anal-ysis this specialization is not the rule At the gene level,for example, essential genes encoding hub proteins

24

(as opposed to disease genes) are expressed widely in

tissues of different types At the neural level, all areas

of cortex initially send outputs to nearly all types of

cortical targets (via extra branching of axons) With

experience, these are pruned back so that visual areas

project to subcortical visual processors, auditory to

auditory, and the like [28] What must be explicated

by the developmental scholar is how the organism

goes from a brain that is widely interconnected and

undifferentiated to one that can be described in terms

of specialized modules

The current data support the position that

devel-opmentally the gradient is from global to local

pro-cessing mechanisms The overall logic of development

is one of association, rather than dissociation: from

interactivity to competition to compensation to

redundancy to specialization to localization to

modu-larization [29] Development in this view is a

modula-rizing process that takes place over the lifespan of an

individual and is dependent on the developmental

transactions between brain and context over time

(see Johnson et al.’s interactive specialization model

[30]) For one mechanism in support of this general

framework, Elman and his colleagues [31] have

argued that the logic instantiated in the work on

gene expression and cortical sprouting also obtains

at the behavioral development level: the availability

of domain-relevant learning algorithms (the

biologi-cally prepared end-states of evolutionary processes)

“jumpstart” the infant brain Initially all algorithms

attempt to process all inputs Eventually, however,

one becomes the winner (probably the most

domain-relevant one), leading to domain specificity that

becomes even more narrowly specified (modularized)

and efficient with continued experience over time

Biological proclivities, the end-state of

evolution-ary development, are the foundations of subsequent

cognitive capacities; they are encoded in the genome

and provide the start-state for individual development

Behavior will emerge and be continually elaborated as

the individual experiences the world; processes of

plasticity will sculpt and re-sculpt the neural

architec-ture in response to the brain–environment interaction

as it is experienced by the individual over time The

precise nature of the steps from biological proclivity

to adult modularity may be debated for some time to

come but the outline seems clear

More complete models will need to take into

account both evolutionary and ontogenetic

perspec-tives At the one end, different brain systems are

more or less conserved, and dedicated processing units (modules?) that provide informationabout the environment that “cannot be obtained bythought in an ecologically useful timeframe” [32] arecrucial for survival At the other end, within behavioraldomains, different functions can be parsed into thosethat are relatively“focal” in representation and thosethat depend on widespread activations across net-works Processes of elaboration also appear to reflectboth increasing specialization of and increasinglysophisticated interactions among brain systems/networks– among other things, to maximize the effi-ciency of resource utilization in the adult brain [33]

information-Genes and epigeneticsThe gene story involves genomic information andepigenetic processes The genome is the end-state ofevolutionary development, providing the infant with abasic species-specific plan with which to begin to mapthe actual world in which it finds itself Epigeneticprocesses control gene activity over time, regulatingthe turning-on and turning-off of gene expression[34] Gene action is inherently developmental, inher-ently contextually embedded [35] The expression ofgenetic information from the individual’s genome laysout the body plan and the large-scale neural structuresrelated by tissue organization and cell type Epigeneticprocesses in dynamic transactions with experience inthe environment permit the brain to“learn” the nature

of itself in a given setting and sculpt andfine-tune thespecialized networks needed for mature function Thelaying down of structures and circuits begins in utero.Postnatally, the dance between structure and experi-ence speeds up exponentially as the infant has greaterand greater access to stimulation: not only sensory, butnow social, communicative, cognitive – and rapidlydevelops the capacity to engage with all the stimuli ofthe world on his or her own recognizance

The application of genetically informed models tothe understanding of the child’s behavior will requireclear differentiation of the role of single genes and ofmultiple genes in the elaboration of complex behaviorsand appreciation of the difference in genetic contribu-tions to normal function and to disease It is unlikelythat the complexity of processes underlying a behav-ioral skill such as reading, for example, could be orch-estrated by a single gene or even gene family.However, by the same token, it is entirely plausiblethat the uncomplicated acquisition of such a complexlyDevelopmental models in pediatric neuropsychology

25

orchestrated skill could easily be derailed by the action

or inaction of a few genes Genetically informed

mod-eling will also require close analysis of the biology–

environment interaction Kovas and Plomin [36]

argue, for example, that pleiotropy (one gene in

fluen-ces many traits) and polygenicity (many genes in

flu-ence one trait) mean that the impact of genes on brain

and behavior is“generalist” and not modular In their

analysis of the genetic contributions to learning

abil-ities and disabilabil-ities, for example, they conclude that

discrepancies in children’s profiles of performance are

largely due to “specialist” environments But, as the

genetic revolution in neuroscience bears more and

more fruit, it appears that the range of variables that

both researchers and clinicians will need to consider

in the brain–behavior analysis only grows – and that

gene–environment interactions will have to be

con-sidered in light of very specific genetic characteristics

of the individual Thus, adverse environments, that–

generally speaking– can be so detrimental to

neuro-behavioral development may not be so maladaptive

for everyone, but may vary as, for example, a function

of serotonin gene structure in the individual [37]

Plasticity

Plasticity is “an obligatory consequence of neural

activity in response to environmental pressures,

func-tional significance and experience” [38], a “baseline

property of the brain” [39] It is neutral with respect

to outcome, being the fundamental mechanism for

learning and development, but also the cause of

path-ology and subsequent clinical disorders It is not a

process that builds a brain and then stops, but an

inherent property of the nervous system that is always

present Alternative connectivity is held in check by

normal functioning in the world In parallel to the

forces operating at the evolutionary level, as long as

the individual keeps acting within his/her repertoire,

that is, in an environment with specific parameters,

then the attained brain organization remains stable

Should the individual’s repertoire change, then plastic

responses will re-shape the system to adapt to the

new status Thus, losing sight results in allocation of

receptivefields previously committed to visual cortical

inputs to auditory and/or tactile inputs [40];

con-straining or losing a digit or limb leads to reshaping

of the receptive fields [41] Such resculpting of

con-nections may not work to a patient’s advantage, as

when an undermined body plan leads to secondary

“phantom” experiences including severe and (to

date) largely intractable pain [42] It may, however,

be the basis for therapeutic strategies that after injurychange outcomes for the better, as in constraint-induced therapy [43] But disease or injury is not theonly way the individual’s repertoire may change.Plastic responses are recruited when an individualcommits to a demanding musical or motor discipline.The brains of musicians [44], of chess players [45], and

of expert golfers [46] are resculpted as they achieve theamount of practice needed for expert performance Ofnote is the fact that the increased skill the individualsgain seems to be specific to the domain of practice.There are two major components of plasticity:expression of normal physiological responses thatare subject to inhibitory control when the relevantstimuli are present, and cross modal plasticity denovo in response to severe sensory deprivation [47].Processes involve unmasking of existing connections(shifts of strength in existing connections) and estab-lishment of new connections The meaning of stimuli

to the organism is crucial– and is reflected in the range

of activation elicited For example, phonemic wordgeneration elicits focal brain activity associated withauditory processing; semantic word representationactivates multiple sites, including visual

Other mechanisms are integral to the workings ofplasticity Competition for connectivity is salient andspecific processes of apoptosis with their own trajecto-ries and time lines are crucial sculptors of architecture

in the developing brain [48] The balance between tatory and inhibitory processes is also dynamic [49],and has important implications for pharmacologicalinterventions in pediatric epilepsy, for example.Additional themes related to howTwo additional themes are central to the how ofdevelopment – timing and white matter Issues oftiming are critical to all models of developmentalchange and stability Both genes + epigenes and plas-ticity are dependent on the timing of expectableinputs Critical and/or sensitive periods are those dur-ing which exposure to relevant stimulation is optimal.Both the onset and the offset of such periods can bebiologically specified: gene activity both switches onand switches off a developmental process The classicdemonstration of this principle was provided by Hubeland Wiesel, who showed that development of thecolumnar organization of the visual receptive fields

exci-in the cat depended on visual experience withexci-in aparticular time frame The practical application is

26