Human
brain
development
over
the
early
years
Rianne
Haartsen,
Emily
JH
Jones
and
Mark
H
Johnson
Recentstudiesofthestructuralandfunctionaldevelopmentof
thehumanbrainovertheearlyyearshavehighlightedtherapid
developmentofbrainstructuresandtheirinterconnectivity.
Someregionalfunctionalspecializationsemergewithinthefirst
monthsafterbirth,whileothershaveamoreprotractedcourse
ofdevelopmentspanningoverthefirstdecadeorlonger.While
someanatomicalchangesenabletheemergenceofnew
functions,evidencealsopointstotheimportanceofresting
stateoscillationsinsculptingneuralarchitectureduring
development.Inatypicaldevelopmentdifferencesinbrain
structure,functionandtask-relatedactivityininfancyoften
precedetheemergenceoflaterdiagnosticbehavioural
symptoms. Address
CentreforBrainandCognitiveDevelopment,Departmentof
PsychologicalScience,Birkbeck,UniversityofLondon,HenryWellcome
Building,MaletStreet,LondonWC1E7HX,UnitedKingdom
Correspondingauthor:Haartsen,Rianne([email protected])
CurrentOpinioninBehavioralSciences2016,10:149–154
ThisreviewcomesfromathemedissueonNeuroscienceof
education
EditedbyDe´nesSzu˝cs,FumikoHoeftandJohnGabrieli
http:dx.doi.org/10.1016/j.cobeha.2016.05.015
2352-1546/#2016PublishedbyElsevierLtd.
Introduction
Understandingthedevelopmentofthehumanbrainover thefirstyearsoflifeisofcriticalimportanceforbothbasic science,andforitsapplicationtosocietalandeducational issues.Fromabasicscienceperspective,evidenceabout thestateofreadinessof thehumannewborn’sbrainhas beencentraltoissuesinthenature-nurturedebate[1,2]. From an educational perspective, data onthe develop-mental state ofthe humanbrain over theearly years is relevant for debates such as theeffects of beingraised withinlowsocial-economicstatushouseholds[3], under-standingwaystolevelthecognitivedisparitiesatschool entry,andearlydiagnosisandinterventionforinfants at-riskforlateratypicaloutcomessuchasAutismSpectrum Disorders (ASD) [1] or attention deficit/hyperactivity disorder (ADHD) [4] (see Box 1 for the abbreviations usedthroughoutthisreview).Theincreasingknowledge ontherelationshipbetweenstructureandfunctionshows
theimportanceoftheenvironmentduringearly develop-ment[5],andthereforethesignificanceofhighquality earlyeducation.
The present review focuses on severalissues that have spurred recent debate and research effort. First, we survey currentevidence fromMRI studies onthe ana-tomicaldevelopmentofthehumanbrainfromgestation topre-schoolyears.Next,wesummarizerecentliterature on the functional development of the brain over this period based on methods such as EEG, ERP, NIRS, andfunctionalMRI.Followingthis,wediscusstheissue of how structuraland functional brain development in-teract in termsof causal associations. While a common assumption is that underlying anatomical development allows or enables new mental functions to emerge, in-triguingrecentevidenceisconsistentwithbi-directional causesinwhichneuralactivityatayoungerageshapesthe subsequent changes in brain structural measures—a viewconsistentwiththeInteractiveSpecialization frame-work [6].
Structural
brain
development
Recentadvancesin theanalysisandresolutionof struc-tural MRI have enabled increasingly detailed descrip-tions of anatomical development of the brain from its microstructure, towhole regionsandthestructural con-nectivity between regions. A recent finding is that the growthratesofcorticalthicknessandsurfaceareadiffer acrossbrainregions[7].Theobservedincreasesforboth corticalthicknessandsurfaceareainmostbrainareasare largerduringthefirstyearthaninthesecondyearoflife. However, cortical thinninghas also been observed in a fewareas(e.g.theleftandrightanteriorcingulategyrus, and the leftand right middlecingulate gyrus). Cortical thicknessmaturesearlierthandoescorticalsurfacearea: bytheageof2years,corticalthicknessreaches approxi-mately97% ofadultvalues,whereas thecorticalsurface areaonlyreaches69%oftheadultvalues.Corticalfolding alsoincreaseswithage, andismeasured bythe gyrifica-tionindexastheratiobetweensurfaceareaofthecortex andthesurfaceareaofthecerebralhullofthebrain(the area coveringthebrain whiletouchingthegyri without divingintothesulci)[8,9].Theincreaseincorticalfolding with age is already evident in preterm infants when scanned between 30 and 40 weeks postmenstrual age [9]. The gyrification index shows higher growth rates during thefirstyearof lifethan during thesecondyear of life, with rates of 16.6% and 6.6% respectively [8]. Thesegyrificationindexgrowthratesareheterogeneous across brainregions, andshow differenttopological pat-terns of developmentthan thepatterns of expansionof
thesurfaceareas. Thisisof interestgiventhedifferent geneticcontrolofthesemeasuresofcorticalstructure[1], and the differential effects observed in developmental disordersdiscussed later.
Connectionsbetween brain regions also show develop-mentalchange.Fibrebundlesarewhitemattertractsthat structurally connect brain regions with each other, and can be traced using tractography imaged by diffusion MRI or DTI (Diffusion Tensor Imaging) [10,11,12]. Tractographyreliesonthediffusivityofwatermolecules in the brain, where water molecules diffuse in parallel directionsalongthewhitemattertractsratherthaninall directions(fractionalanisotropy).Thismethodallowsfor visualizingofthestructuralconnectionsinthebrain,and for further connectivity and graph theory analyses (for moreinformationonthegraphtheoryand its character-istics,seeBox2andFigure1).Asearlyas30weeksfrom gestation,suchmethodsshowthathumanstructuralbrain connectivityshowsa‘richclub’organizationwithspecific cortical‘hubs’connected to each other[12].Overthe subsequent 10 weeks, node degrees increase, path lengthsdecrease,and clustering increases.Balland col-leaguesarguethattherichcluborganizationobservedat this earlyageprovidesa foundationfor thesubsequent developmentoffunctionalconnectivitynetworks. The growth rates ofconnections in the preterm infant brain between 27 and 45 weeks of postmenstrual age differacrossregion-pairconnections,showinghigherrates forconnectionsinthefrontalandoccipitallobesthanin other regions [10]. These connections are part of net-works that are already highly efficient and clustered at term age, but show increased efficiency, clustering and small-worldnesswithincreasingpostnatalage.Structural brainnetworksbecomemorestronglyconnectedwithage during childhood, suggesting an increased number of white matter tracts with higher fractional anisotropy values between brain regions of interest compared to thenumberoftractsatyoungerages[11].Thenetworks
aremore efficient andbetter integratedwith increasing agebetweenbirthandpre-adolescence.Furthermore,the networks become more robust and less vulnerable to injuryorrandomfailurethanthoseexistingshortlyafter birth. A recent review of growth connectomics has hy-pothesized a trade-off between minimizing the energy costofthenetworkandmaximizingitsintegrative topol-ogy.The optimal resultofthese trade-offchangeswith development, resulting in a shift from local networks towardsmoregloballydistributednetworks[13].
Inadditiontofocusingonbraindevelopmentduringthe firstyearsoflife,studiesareinvestigatingthelongitudinal trajectoryofstructuralbraindevelopment.Theythereby identifycommontrajectoriesinlargegroupsof individu-als.Forexample,the‘brainmaturationindex’accurately predictschronologicalagebetweenapproximately5and 18yearsafterbirthbasedonbrainvolumesin37regions measuredusingMRI[14].Accumulating evidencefrom MRIandDTI during development[15],hasledto the generationofa‘braindevelopmentindex’thatcan accu-ratelypredictchronologicalagebetween8and22yearsof agebasedonbrainanatomyin childrenandadolescents [16].Overall,graymattervolumesbegintodecreasefrom mid-childhood,whilewhitemattervolumescontinueto increase with age [1]. Individuals with a higher brain development index-predicted age than actual age (ad-vanced)showanearlierdecreaseingraymattervolumes comparedtoindividualswithsimilarpredictedandactual age (typical)[16]. In contrast,individuals with a lower predictedage(delayed)showalaterdevelopmentalshift,
Box2 Graphtheory
Graphtheorycanbeusedtocharacterizebrainnetworksbyusing
conceptssuchasnodesandedges(seeFigure1).Nodesaresmall
unitsinthenetworks,whichareconnectedbyedges.Short-range
edgesconnectnearbynodes,whereaslong-rangeedgesconnect
nodesthatarefurtherapart.Thedegreeofanodereflectsthe
amountofedgesconnectedtothatnode.Anodewithahighdegree
hasmanyconnectionstoothernodes,whileanodewithalow
degreehasfewconnectionstoothernodes.Pathlengthsarethe
numberoftheedgesbetween2nodes.Networkscanbeintegrated
(moreconnectionsbetweendistantbrainareas)andsegregated
(fewerconnectionsbetweenclosebrainareas).
Small-worldorrichcluborganizednetworksarecharacterizedby
clustersofhighlyconnectedunits,ormodules.Inaddition,these
modulesareconnectedbylong-rangeconnections.Richclubnodes
orhubsarenodesthathaveahighnodedegree,areconnectedby
shortandlongrangeedgesandtherebyfacilitateintegration
[1,13,30,38].
Graphtheorycanbeappliedtobothstructuralandfunctional
neuroimagingdata.Instudiesonthestructureofthebrainusing
dMRI,brainregionsaredefinedasnodes,andthestructural
connectionsbetweentheseregionssuchaswhitemattertractsare
definedastheedges(e.g.[10]).Incontrast,studiesaimingto
investigatefunctionalconnectivityusingEEGorMEGdefinebrain
regionsofinterestasnodesandsimilaritiesinactivationsinthose
brainregionsasedges(e.g.[39]).
Box1 Abbreviationsusedinthereview
ADHD AttentionDeficit/HyperactivityDisorder
ASD AutismSpectrumDisorder
BOLD Blood-Oxygen-LevelDependent
DTI DiffusionTensorImaging
EEG Electroencephalography
ERP EventRelatedPotential
fMRI functionalMagneticResonanceImaging
fNIRS functionalNear-InfraredSpectroscopy
HRF HemodynamicResponseFunction
MRI MagneticResonanceImaging
thusalaterdecreaseingraymattervolumes,comparedto theothergroups.Thefindingsofthesestudiesshowthat typical brain developmentfollowsacommontrajectory. Thisknowledgecouldhelpustobetteridentifyatypical brain development.
Functional
brain
development
While thestateofanatomical developmentofthebrain clearly imposes constraints oncognition and behaviour, we can more directly assess emerging brain functions throughmethodssuchas EEG,NIRS,andfMRI. Mea-surements of brain function canbe madeeither during task-related states or during rest. During resting state measurements, infants are usually asleep, while older children are asked to lookat afixationcross orto keep theireyes closed.
Functionalresting statenetworksas measuredbyfMRI start to emerge before birth and continue to develop
during the first years of life, characterized by greater fine-tuningandincreasedspecialization[13].Different functional networks have differentdevelopmentaltime courses(forareview,see[17]).Restingstatenetworksare evident as young as 26 weeks prenatal age. Networks involvedinprimarymotorandsensoryareasappearmore adult-likeatthisstage,whilenetworksinvolvedinhigher orderprocessingappearincompleteandfragmentedeven at term age[18]. Between birth and 1 yearof age, the primary sensory-motor and auditory networks are the earliestnetworkstoemerge,followedbythevisual net-workandthentheattentionand‘defaultmode’networks [3,18,19].Defaultmodenetworksaretypicallyviewedas thebaselinestateofthebrain,wheretheinvolvedareas show a decrease in activation during goal-directed and cognitive tasks compared to the activation when the subject is resting with eyes closed but awake [20]. In the infant fMRIstudies, the areas of the adult default mode network and theother adult functional networks areusedasseedregionsfortheconnectivityanalysesof scansofsleepinginfantsbetweenbirthand1yearofage. Finally,thenetworksinvolvedinexecutivecontrolbegin to emerge, for example the salience network. Resting state functionalnetworks canbeusedto classify ageat 6 and 12months withsupport vectormachine methods [21]. This shows that resting state functional networks alsoshowacommondevelopmentaltrajectory,similarto brainanatomyleadingtothebrainmaturationindexand thebraindevelopmentindex.
The thalamus is an important subcortical structure throughwhichallsensoryinformationpassestothecortex [1].Restingstatefunctional MRIrecordedduringsleep showsthatfunctionalconnectionsbetweenthethalamus and sensorimotor areas, and between thalamus and the salience networkalready existin neonates [22].During the first2 years of life, thalamicfunctional connections withthemedialvisualnetworkandwiththedefaultmode networkbegintodevelop.Thethalamusistopologically divisible into different functional areas at the time of birth, in asimilarfashionas seenin adults.Some func-tional connections to the cortex are more widespread, whileothersarelimitedto particularareasinthecortex. At 38–42weeksgestational age, prematureinfants rela-tivetoterminfantsshowdecreasedfunctional connectiv-ity between the thalamus and fronto-parietal insular, anterior cingulate, and prefrontal areas, but increased connectivitybetweenthethalamusandthesensorymotor cortex[23].Thisshowsthatprematurityhasasignificant effectontheconnectivitybetweenthethalamusandthe cortex.
Turningtotask-relatedbrainactivation,wenowfocuson thecorticalspecializationofthesocialbrainareastosocial stimuli.AnfNIRSstudy(seeBox3)inone-dayto four-day-oldnewbornsfoundthatchannelsovertheposterior temporalregionshowedahigherresponsewhenviewing
Figure1
Node Edge
Strong long-range edge between modules Weak long-range edge between modules Short path length
Long path length Rich club node / hub
b
Current Opinion in Behavioral Sciences
a
Brainnetworks.Nodes(orangedots)areconnectedbyshortand
long-rangeedges(lightbluelines)withinmodules(ingreendottedcircle).
Connectionsbetweennodes,forexamplenodeaandnodeb,can
haveashortpathlength(solidyellowarrow)oralonglength(dotted
yellowarrow).Richclubnodes(redglowingdots)areconnected
acrossmoduleswithstrong(soliddarkbluelines)andweak(dotted
darkbluelines)long-rangeedges.
dynamicsocialvideostimuliascomparedtomechanical non-socialstimuli.Intriguingly,thedegreeofspecificity oftemporalcorticalactivationtosocialstimuliincreased withtheageinhoursoftheinfants[24].Thesedataare consistentwiththenotionthatpartsofthesocialbrainare selectivelyactivated to social stimuli shortly from after birth, but may require brief experience to tune them. UsingasimilarfNIRSparadigm,infantsaround5-month old show specialized responses to visual social stimuli, andalargerresponsein theposteriorsuperior temporal sulcus to human vocal than non-vocal auditory stimuli [25,26].Further,EEGspectralpowershowswidespread changesin thebreadthanddepth of brain activationto socialversusnon-socialnaturalisticstimulibetween6and 12months[27].Theseobservationsarein linewiththe hypothesis suggesting relatively early, but experience-dependent,corticalspecializationto socialstimuli.
The
relation
between
structural
and
functional
brain
development
Ingeneral,regionslinkedbystrongstructuralconnections also tend to have strong functional connections [28]. However,therearealsofindingsshowingstrong function-al connectivity between areas without clear structural connectivitytosupportit.Inaddition,functional connec-tivityduringresting-statecanchangeovertimeandwith taskdemands,whereastheunderlyingstructuralanatomy remains largely stable [29]. Changes in functional con-nectivitywhilestructuralconnectivity isfixed mightbe explainedbyaglobalintegrationofsegregatedmodules [30].Thelong-rangeconnectionsinthisarrangementare flexibleand havetheabilityto facilitatetheintegration dependingonthetaskdemands.
Whileitiscommonlyassumedthatanatomical develop-mentwithinregionsenablesorallowsfortheemergence ofnew brain functions,contemporary theoriesof devel-opingbrainfunctionemphasizethepotentialimportance of bi-directionalstructure-function relations, in whicha
persisting brain functional state can sculpt underlying neuralarchitecture[6].Inhumandevelopment,arecent study shows that slower microstructural development between27and46weekspostconception(29–48weeks gestationalage)inprematureinfantswasrelatedtolower levelsof neurodevelopmental functioning at theage of 2years[31].Higherlevelsofspontaneousbrainactivityin preterm newborns measured shortly after birth around 30weeksgestationalagearerelatedtofasterratesofbrain growth between birth and term equivalent age, or 40weeksgestational age[5].Infantswithshorter per-iodsoflowlevelsofspontaneousbrainactivityshoweda fastergrowthrateinoverallbrainvolumeandsubcortical graymattervolumes,supportingtheideathatdeveloping brainstructurecanbeshapedbyprecedingactivitystates.
Atypical
brain
development
Whiletothispointwefocussedprimarilyonthetypical developmentalpathforhumanbraindevelopment,there isgreatinterestinusingmeasuresofbraindevelopment asearlybiomarkersforlateremergingconditions. Takingtheexampleofautism,infantsatfamilialriskfor ASDshowstructural,functionaland task-related differ-encesbeforethe onsetof diagnosticbehavioural symp-toms [32]. For example, structural differences include that infants that develop ASD at a later age have an increased corpus callosum early in life [33]. Volume differencesaregreatestat6monthsofageanddiminish around24 months. Furthermore, thesize of the corpus callosumat 6 months of age and the thicknessat both 6 and 12 months of age are positively correlated with repetitive behaviours at 2 years of age. In terms of functional connectivity, using fNIRS infants atrisk for ASDhaveincreasedfunctionalconnectivityat3months comparedtotheirlowriskcontrolpeers[34].At12months of age, infants atrisk for ASDshowed decreased func-tionalconnectivitycomparedwiththeothergroup.These fNIRS results suggest a developmental trend with in-creasing functional connectivity for low risk control infants during the first year of life, while in high risk ASDinfants functional connectivity seemsto decrease, possiblyindicatinganadaptiveresponse[35].However, an independent study found that 14-month-old infants laterdiagnosedwithASDshowincreasedEEG connectiv-ityinthealphafrequencyrangecomparedtootherinfants [36].Themeasuresofincreasedconnectivityinthehigh risk-ASDgroupwererelatedtoanincreaseinrepetitive and restrictive behaviours at the age of 3 years. Thus, whilstresultsintheNIRSstudyshowunderconnectivity at12months,theEEGresultsshowoverconnectivityat 14months.Thesecontrastingfindingsmight arisefrom thedifferentparadigmsused—apassivelisteningtaskin the NIRS study, and watching social and non-social stimuli in the EEG study. Other possibilities are the differentunderlyingmechanismsbothmethodsmeasure (oxygenationofthebloodversuselectricalactivityinthe
Box3 MethodsandrecentkeyfindingsinfNIRS
FunctionalNearInfraredSpectroscopy(fNIRS)measureslevelsof
oxyhemoglobinanddeoxyhemoglobinbymeasuringrefractednear
infraredlightthatisdirectedintothebrain.Thesemeasurements
approximatelyequatetotheblood-oxygen-leveldependent(BOLD)
signalmeasuredinfMRI.fNIRShasbothadvantagesand
disadvan-tagesincomparisontoMRIformeasuringinfantbrainfunction.As
bothmethodsmeasurethehemodynamicresponsefunction(HRF),its
importanttonotethattheinfantHRFdiffersfromthatobservedin
adults,beingbothsmalleramplitudeandcomparativelydelayedin
onset[40].Whilewecannotsimultaneouslymeasurebrainstructurein
fNIRS,itismoretoleranttomovementallowingtask-relatedstatesin
awakeinfantstobestudied.fNIRSisusedtostudydifferentbrain
processesinyounginfants,suchasobjectprocessing,face
processing,processingofhumanmotion,languageprocessingand
learning,unimodalperceptualprocessing,multisensoryprocessing,
brain); brain regions measured (anterior and posterior areas versus the whole scalp), or differences between groupsofinfantsatfamilialriskforASDandthosewith alaterdiagnosis.Finally,5-month-oldinfantsfamilialrisk forASDalsoshowtask-relateddifferencesinbrain activ-ity [25]. For example, evidence of reduced selective temporal lobe activation in response to viewing social stimulicomparedtoinfantsatlowriskforASDhasbeen found.Inthesamestudy,infantsatfamilialriskshoweda smallerhumanvocal-selectiveresponsethaninfantswith alowriskforASD.Theseresultsconfirmarelativelackof cortical specializationto socialstimuli at4–6 monthsof agein atleastasubset ofinfantsatriskfor ASD.
Conclusions
Recentresearchhighlightstheveryrapiddevelopmentof brain structure and function over the early years. Core resting state networks begin to function from prenatal stages, and mayhelp sculpt subsequentpatterns of re-gionalstructureandconnectivity.Sometask-related pat-ternsofneuralactivationmaybecomeevidentwithinthe firstdaysafterbirth,whileothersshowaveryprolonged timetableandareheavilyinfluencedbypostnatal experi-ence.Thecomplexbi-directionalrelationbetween struc-ture and function may contribute to the substantial resilienceandadaptationshownbythedevelopingbrain [35].Thisbi-directionalrelationshowstheimportance of theearly environment, andthe high quality ofearly education. However,marked atypicalitiesin earlybrain developmentcanbeassociatedwithdevelopmental dis-orderssuchas ASD.
Research on early development of thebrain could also help toidentifyearlymarkersforcognitive functioning. For example, visual-spatial workingmemory is astrong predictorforacademicachievementandhasbeenrelated tostructuralbraindevelopmentininfantsat1and2years of age[22] andchildren between6 and20 yearsof age [37].Theseearlymarkerscanhelpidentifyinfantsatrisk forlaterdifficultiesincognitiveperformanceandfunction asatargetforearlyinterventionduringeducation.Amore nuancedunderstandingofearlybraindevelopmentmay bethekeytomoreeffectiveearlytreatmentapproaches fordevelopmentaldisordersandpooracademic achieve-ment atlater ages.
Conflict
of
interest
Nothing declared.
Acknowledgements
ThisworkhasbeensupportedbyagrantfromtheEuropeanCommunity’s
Horizon2020Programundergrantagreementn8642996(Brainview)(RH).
EmilyJoneshasreceivedsupportfromtheInnovativeMedicinesInitiative
JointUndertakingundergrantagreementn8115300,resourcesofwhichare
composedoffinancialcontributionfromtheEuropeanUnion’sSeventh
FrameworkProgramme(FP7/2007-2013)andEFPIAcompanies’inkind
contribution.MarkJohnsonhasreceivedsupportfromtheUKMedical
ResearchCouncil.
References
1. JohnsonMH,DeHaanM:DevelopmentalCognitiveNeuroscience: AnIntroduction.JohnWiley&Sons;2015.
2. Dehaene-LambertzG,SpelkeES:Theinfancyofthehuman brain.Neuron2015,88:93-109.
3. GaoW,AlcauterS,EltonA,Hernandez-CastilloCR,SmithJK, RamirezJ,LinW:Functionalnetworkdevelopmentduringthe firstyear:relativesequenceandsocioeconomiccorrelations. CerebCortex2015,25:2919-2928.
4. JesteSS,FrohlichJ,LooSK:Electrophysiologicalbiomarkers ofdiagnosisandoutcomeinneurodevelopmentaldisorders. CurrOpinNeurol2015,28:110-116.
5.
BendersMJ,PalmuK,MenacheC,Borradori-TolsaC,LazeyrasF, SizonenkoS,DuboisJ,VanhataloS,Hu¨ppiPS:Earlybrain activityrelatestosubsequentbraingrowthinpremature infants.CerebCortex2015,25:3014-3024.
Thispaperprovidesanexampleofhowmeasuresofbrainactivityatone
agepredictlateraspectsofbrainstructuralarchitecture.
6. JohnsonMH:Interactivespecialization:adomain-general frameworkforhumanfunctionalbraindevelopment? Dev CognNeurosci2011,1:7-21.
7. LyallAE,ShiF,GengX,WoolsonS,LiG,WangL,HamerRM, ShenD,GilmoreJH:Dynamicdevelopmentofregionalcortical thicknessandsurfaceareainearlychildhood.CerebCortex 2015,25:2204-2212.
8. LiG,WangL,ShiF,LyallAE,LinW,GilmoreJH,ShenD:Mapping longitudinaldevelopmentoflocalcorticalgyrificationin infantsfrombirthto2yearsofage.JNeurosci2014, 34:4228-4238.
9. MoeskopsP,BendersMJNL,KersbergenKJ,GroenendaalF,De VriesLS,ViergeverMA,IsˇgumI:Developmentofcortical morphologyevaluatedwithlongitudinalMRbrainimagesof preterminfants.PLoSONE2015,10:1-22.
10. BrownCJ,MillerSP,BoothBG,AndrewsS,ChauV,PoskittKJ, HamarnehG:Structuralnetworkanalysisofbraindevelopment inyoungpretermneonates.Neuroimage2014,101:667-680.
11. HuangH,ShuN,MishraV,JeonT,ChalakL,WangZJ,RollinsN,
GongG,ChengH,PengYetal.:Developmentofhumanbrain
structuralnetworksthroughinfancyandchildhood.Cereb
Cortex2015http://dx.doi.org/10.1093/cercor/bht335.
12.
BallG,AljabarP,ZebariS,TusorN,ArichiT,MerchantN, RobinsonEC,OgundipeE,RueckertD,EdwardsADetal.: Rich-cluborganizationofthenewbornhumanbrain.ProcNatlAcad SciUSA2014,111:7456-7461.
Thispaperisthefirsttoinvestigatethedevelopmentofstructural
con-nectivityintheprenatalperiodusingthebrainnetworkapproach.
13.
Ve´rtesPE,BullmoreET:Annualresearchreview:growth connectomics—theorganizationandreorganizationofbrain networksduringnormalandabnormaldevelopment.JChild PsycholPsychiatry2015,56:299-320.
Thisreviewdiscussestheconceptsregardingbrainnetworksatdifferent
levelsoforganization,andappliesthesetodifferentneuroimaging
meth-odsoverdevelopment.
14. CaoB,MwangiB,HasanKM,SelvarajS,ZeniCP, Zunta-SoaresGB,SoaresJC:Developmentandvalidationofabrain maturationindexusinglongitudinalneuroanatomicalscans. Neuroimage2015,117:311-318.
15. WalkerL,ChangL-C,NayakA,IrfanogluMO,BotteronKN,
McCrackenJ,McKinstryRC,RivkinMJ,WangD-J,RumseyJ
etal.:Thediffusiontensorimaging(DTI)componentoftheNIH
MRIstudyofnormalbraindevelopment(PedsDTI).Neuroimage
2015http://dx.doi.org/10.1016/j.neuroimage.2015.05.083.
16. ErusG,BattapadyH,SatterthwaiteTD,HakonarsonH,GurRE,
DavatzikosC,GurRC:Imagingpatternsofbraindevelopment
andtheirrelationshiptocognition.CerebCortex2014http://
dx.doi.org/10.1093/cercor/bht425.
17. HoffGEA-J,VandenHeuvelMP,BendersMJNL,KersbergenKJ, DeVriesLS:Ondevelopmentoffunctionalbrainconnectivityin theyoungbrain.FrontHumNeurosci2013,7:650.
18. SmyserCD,NeilJJ:Useofresting-statefunctionalMRIto studybraindevelopmentandinjuryinneonates.Semin Perinatol2015,39:130-140.
19. LinW,ZhuQ,GaoW,ChenY,TohC-H,StynerM,GerigG, SmithJK,BiswalB,GilmoreJH:FunctionalconnectivityMR imagingrevealscorticalfunctionalconnectivityinthe developingbrain.AmJNeuroradiol(AJNR)2008,29:1883-1889.
20. RaichleME,MacLeodAM,SnyderAZ,PowersWJ,GusnardDA, ShulmanGL:Adefaultmodeofbrainfunction.ProcNatlAcad SciUSA2001,98:676-682.
21. PruettJRJr,KandalaS,HoertelS,SnyderAZ,ElisonJT,NishinoT, FeczkoE,DosenbachN,NardosB,PowerJetal.:Accurateage classificationof6and12month-oldinfantsbasedon resting-statefunctionalconnectivitymagneticresonanceimaging data.DevCognNeurosci2015,12:123-133.
22. AlcauterS,LinW,SmithJK,ShortSJ,GoldmanBD,ReznickJS, GilmoreJH,GaoW:Developmentofthalamocortical connectivityduringinfancyanditscognitivecorrelations.J Neurosci2014,34:9067-9075.
23. ToulminH,BeckmannCF,O’MuircheartaighJ,BallG,NongenaP, MakropoulosA,EderiesA,CounsellSJ,KenneaN,ArichiTetal.: Specializationandintegrationoffunctionalthalamocortical connectivityinthehumaninfant.ProcNatlAcadSciUSA2015, 112:201422638.
24.
FarroniT,ChiarelliAM,Lloyd-FoxS,MassaccesiS,MerlaA,Di GangiV,MattarelloT,FaragunaD,JohnsonMH:Infantcortex respondstootherhumansfromshortlyafterbirth.SciRep 2013,3:2851.
Thisstudyprovidesthefirstexperimentalevidenceofcortical
specializa-tionemergingduringthefirstfewdaysafterbirth.
25. Lloyd-FoxS,BlasiA,ElwellCE,CharmanT,MurphyD, JohnsonMH:Reducedneuralsensitivitytosocialstimuliin infantsatriskforautism.ProcBiolSci2013,280:20123026.
26. Lloyd-FoxS,BlasiA,VoleinA,EverdellN,ElwellCE,JohnsonMH: Socialperceptionininfancy:anearinfraredspectroscopy study.ChildDev2009,80:986-999.
27. JonesEJH,VenemaK,LowyR,EarlRK,WebbSJ:
Developmentalchangesininfantbrainactivityduring
naturalisticsocialexperiences.DevPsychobiol2015http://
dx.doi.org/10.1002/dev.21336.
28. BullmoreE,SpornsO:Complexbrainnetworks:graph theoreticalanalysisofstructuralandfunctionalsystems.Nat RevNeurosci2009,10:186-198.
29. WangZ,DaiZ,GongG,ZhouC,HeY:Understanding
structural-functionalrelationshipsinthehumanbrain:alarge-scale
networkperspective.Neuroscientist2014http://dx.doi.org/
10.1177/1073858414537560.
30. ParkH-J,FristonKJ:Structuralandfunctionalbrainnetworks: fromconnectionstocognition.Science2013,342:1238411.
31. BallG,SrinivasanL,AljabarP,CounsellSJ,DurighelG,HajnalJV, RutherfordM,EdwardsD:Developmentofcortical
microstructureinthepretermhumanbrain.ProcNatlAcadSci USA2013,110:9541-9546.
32. JonesEJH,GligaT,BedfordR,CharmanT,JohnsonMH: Developmentalpathwaystoautism:areviewofprospective studiesofinfantsatrisk.NeurosciBiobehavRev2014,39:1-33.
33. WolffJJ,GerigG,LewisJD,SodaT,StynerMA,VachetC,
BotteronKN,ElisonJT,DagerSR,EstesAMetal.:Alteredcorpus
callosummorphologyassociatedwithautismoverthefirst
2yearsoflife.Brain2015http://dx.doi.org/10.1093/brain/
awv118.
34. KeehnB,WagnerJB,Tager-FlusbergH,NelsonCA:Functional connectivityinthefirstyearoflifeininfantsat-riskforautism: apreliminarynear-infraredspectroscopystudy.FrontHum Neurosci2013,7:444.
35.
JohnsonMH,JonesE,GligaT:Brainadaptationandalternative developmentaltrajectories.DevPsychopathol2015,
27:425-444.
Explainstheemergence ofcommonneurodevelopmental disordersin
terms ofadaptivedeviationsofthe typicaltrajectoryofhuman brain
development.
36. OrekhovaEV,ElsabbaghM,JonesEJH,DawsonG,CharmanT, JohnsonMH,TheBASISTeam:EEGhyper-connectivityin high-riskinfantsisassociatedwithlaterautism.JNeurodevDisord 2014,6:40.
37. UllmanH,AlmeidaR,KlingbergT:Structuralmaturationand brainactivitypredictfutureworkingmemorycapacityduring childhooddevelopment.JNeurosci2014,34:1592-1598.
38. Ve´rtesPE,Alexander-BlochAF,BullmoreET:Generativemodels ofrichclubsinHebbianneuronalnetworksandlarge-scale humanbrainnetworks.PhilosTransRSocB:BiolSci2014,369.
39. BoersmaM,KemnerC,DeReusMA,CollinG,SnijdersTM, HofmanD,BuitelaarJK,StamCJ,vandenHeuvelMP:Disrupted functionalbrainnetworksinautistictoddlers.BrainConnect 2013,3:41-49.
40. HarrisJJ,ReynellC,AttwellD:Thephysiologyofdevelopmental changesinBOLDfunctionalimagingsignals.DevCogn Neurosci2011,1:199-216.
41. WilcoxT,BiondiM:fNIRSinthedevelopmentalsciences.Wiley InterdiscipRevCognSci2015,6:263-283.
42. AslinRN,ShuklaM,EmbersonLL:Hemodynamiccorrelatesof cognitioninhumaninfants.AnnuRevPsychol2015,3:349-379.
