From ERPs to academics 001

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ContentslistsavailableatScienceDirect

Developmental

Cognitive

Neuroscience

jou rn a l h om epa g e:h t t p : / / w w w . e l s e v i e r . c o m / l o c a te / d c n

From

ERPs

to

academics

Charles

H.

Hillman

a,∗

,

Matthew

B.

Pontifex

a

,

Robert

W.

Motl

a

,

Kevin

C.

O’Leary

a

,

Christopher

R.

Johnson

a

,

Mark

R.

Scudder

a

,

Lauren

B.

Raine

a

,

Darla

M.

Castelli

b

a_University_of_Illinois_at_{Urbana-Champaign,}_United_States b_University_of_Texas_at_Austin,_United_States

a

r

t

i

c

l

e

i

n

f

o

Articlehistory:

Received26April2011

Receivedinrevisedform6July2011 Accepted12July2011

Keywords:

Academicachievement Scholasticperformance P3

Inhibition Workingmemory Executivecontrol

a

b

s

t

r

a

c

t

Standardizedtestshavebeenusedtoforecastscholasticsuccessofschool-agechildren,and havebeenrelatedtointelligence,workingmemory,andinhibitionusing neuropsycholog-icaltests.However,ERPcorrelatesofstandardizedachievementhavenotbeenreported. Thus,therelationshipbetweenacademicachievementandtheP3componentwasassessed inasampleof105childrenduringperformanceonaGo/NoGotask.TheWideRange AchievementTest–3rdeditionwasadministeredtoassessaptitudeinreading,spelling, andarithmetic.RegressionanalysesindicatedanindependentcontributionofP3amplitude toreadingandarithmeticachievementbeyondthevarianceaccountedforbyIQandschool grade.Nosuchrelationshipwasobservedforspelling.ThesedatasuggestthattheP3,which reflectsattentionalprocessesinvolvedinstimulusevaluationandinhibitorycontrolmay beabiomarkerforacademicachievementduringchildhood.

1. Introduction

Standardizedtestsareoftenusedtoforecastscholastic

successfromearlychildhoodthroughvocational,

gradu-ate,andprofessionalstudies (Kuncel andHezlett, 2007;

Kuncelet al.,2004).Insecondaryeducation,federal

ini-tiatives have placed external pressures on schools to

provide studentswithbasiccompetencies in traditional

academicsubjectmatter(e.g.,mathematics,reading,

sci-ence).Suchcompetenciesaremonitoredviastandardized

tests to determine educational program effectiveness,

fundingappropriations,andstudentacademicplacement.

Accordingly,thequantificationandpredictionofacademic

successisappealingforanumberofreasons.

Researchers focused on education have long been

interestedintheunderlyingcognitiveprocessesthat

com-∗ Correspondingauthorat:DepartmentofKinesiology&Community Health,317LouiseFreerHall,906SouthGoodwinAvenue,Universityof Illinois,Urbana,IL61801,UnitedStates.Tel.:+12172442663; fax:+12172447322.

E-mailaddress:[email protected](C.H.Hillman).

prisescholasticperformance(Bulletal.,2008;Diamond

etal.,2007).Severalcomponentcognitiveprocesseshave

demonstrated considerable relatedness with academic

achievement including general cognitive ability (Rohde

and Thompson, 2007), intelligence (Jensen, 1998), and

processingspeed(Jensen,1992),aswellasaspectsof

goal-directedexecutivecontrolfunction(Bull etal.,2008;St.

Clair-ThompsonandGathercole,2006).Specifically,

inhi-bitionand workingmemoryhaveboth beenimplicated

inmathematicalandreadingability,whilealackof

con-sensusexistsregardingtheroleofcognitiveflexibilityon

scholasticperformance(BullandScerif,2001;DeStefano

and LeFevre, 2004; St. Clair-Thompson and Gathercole, 2006). St. Clair-Thompson and Gathercole (2006) used

exploratory factor analysis to study the relationship

betweenexecutivecontrolandacademicachievement(i.e.,

English,mathematics,andscience)in11–12yearold

chil-dren,andidentifiedtwoseparateexecutivecontrolfactors,

oneassociatedwiththeupdatingofthecontentsof

work-ingmemoryandtheotherassociatedwiththeinhibition

ofunrelatedinformation.Thethirdexecutivecontrol

fac-tor(i.e.,cognitiveflexibility)wasnotidentifiedashaving

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adistinctrelationshipwithacademicachievement.Such

findings suggestthat the executivecontrol functionsof

workingmemoryand inhibition are related tolearning

in the academic environment, and are consonant with

otherreportsoftheroleofexecutivecontrolinacademic

achievement,includingthosewhodemonstratedifficulties

inacademicsubjectmatter(deJong,1998;Passolunghiand

Siegel,2001).

Todate,theseinterestinglinkagesbetweenacademic

achievementandexecutive controlfunctionshave been

explored solely via task performance or in-class

sys-tematic observation (Mahar et al., 2006; Grieco et al.,

2009),andhaveneverbeeninvestigatedusing

neuroelec-tricmeasurement.Thestudyoftheneuroelectricsystem

provides a more direct means by which to examine

underlyingcognitiveoperationsthatoccurbetween

stim-ulusengagementandresponseexecution.Inparticular,a

classoftheelectroencephalogram,knownasevent-related

brain potentials (ERPs), provides online measurement

ofcognitive processing;thus,potentially shedding light

onspecificaspectsof cognitionthat constitute

variabil-ity in scholastic performance. The P3 (i.e., P3b, P300)

is a largepositive-going peak of an ERP, which occurs

approximately300–800msfollowingstimulusonsetwith

maximum amplitude over the parietal cortex (Donchin

etal., 1986).Thisendogenous component is thoughtto

reflect neuronal activityassociated withthe revisionof

thementalrepresentationofthepreviousevent(Donchin,

1981),suchthatP3amplitudeisdeterminedbythe

allo-cation of attentional resources toward the updating of

workingmemory(Donchinand Coles,1988).P3 latency

isgenerally consideredasameasure ofstimulus

detec-tionandevaluationtime(IlanandPolich,1999;Magliero

etal.,1984),whichisoftenindependentofresponse

selec-tionand behavioral action (Verleger, 1997).BecauseP3

is sensitiveto a host of cognitive and biological

deter-minants(see Polich and Kok, 1995for review),it is an

intriguing component of the neuroelectric system that

may lend itself well to the study of individual

differ-ences.

In the current study, a Go/NoGo task was used to

elicit an ERP, because prior research suggests that the

NoGo-P3providesadirectmeasureofinhibitorycontrol;

thus serving as a biological marker for aspects of

cog-nitiveand/orneuralinhibitorycontrol(Kamarajanetal.,

2005).Thistaskrequiresindividualstodiscernbetween

twostimuliunderseparateinstructionconditions.Inthe

Gocondition, individuals are presented witha train of

stimuliandareinstructedtorespondonlyontherare

occa-sionwhena targetstimulusispresented.Such stimulus

presentationprobabilitiesrequireattentionalvigilanceto

thetasktoaccuratelydetecttheinfrequentGostimulus

inordertoupdatethecontentsoftheworkingmemory

representation ofthe stimulusenvironment, whereby a

prominentP3 potential overlying theparietal regionof

thescalp is observed. In the NoGo condition,a similar

trainofstimuliareprovidedandindividualsareinstructed

torespondtothemajority ofstimuli, suppressingtheir

response ononly the rare occasion. As such, theNoGo

conditionrequiresinhibition of theprepotentresponse,

and elicits a P3 characterizedby a fronto-centralscalp

distribution that is thought to index inhibitory control

(Johnstoneetal.,2007;Kamarajanetal.,2005;Smithetal., 2004).

In theexperiment reportedherein,we examinedthe

associationbetweenpreadolescentchildren’sGo/NoGoP3

amplitudewiththeirperformanceonarithmeticand

read-ing comprehension achievement from the Wide Range

AchievementTest– 3rdedition(WRAT3).Wehypothesized

that theP3would serve asa biologicalmarkerfor

per-formanceontheWRAT3,withlargeramplitudereflecting

betterachievementtestperformance.Wefurtherexpected

thatthisrelationshipwouldemergedespitetheinclusion

ofothermeasures(i.e.,IQ)withestablishedrelationships

toacademicachievement,suggestingtheuniquenessofP3

intheexplanationofscholasticperformance.

2. Method

2.1. Participants

Onehundredfivepreadolescent children (42female;

mean age: 8.8±0.6 years) fromtheeast-central Illinois

regionwererecruitedtoserveasparticipants.Theracial

composition wassimilartothatofthecountywith45%

Caucasian,31%AfricanAmerican,13%Asian,and11%

Bi-racialorotherethnicities.Allparticipantsprovidedwritten

assentandtheirlegalguardiansprovidedwritteninformed

consentinaccordancewiththeInstitutionalReviewBoard

of theUniversity of Illinoisat Urbana-Champaign.Prior

to testing, legal guardians’ completed a health history

anddemographicsquestionnaire,reportedthattheirchild

was free of neurological diseases, attentional disorders

(asindexed byscoresbelowthe80thpercentileonthe

ADHDRatingScaleIV;DuPauletal.,1998),individualized

educational plans,orphysical disabilities,and indicated

normalorcorrectedtonormalvision.Socioeconomic

sta-tus(SES)wasdeterminedusingatrichotomousindexbased

on:participationinfreeorreduced-pricelunchprogram

atschool,thehighestlevelofeducationobtainedbythe

mother andfather, andnumberof parentswhoworked

full-time(Birnbaumetal.,2002)1_._Legal_{guardian’s,}_in

col-laborationwiththeirchild,completedtheTannerStaging

System (Tanner, 1962), indicating that theparticipant’s

pubertal status wasat or below a score of 2 (i.e.,

pre-pubescent)ona5-pointscale.Additionally,childrenwere

administeredtheKaufmanBriefIntelligenceTest(K-BIT;

KaufmanandKaufman,1990)byatrainedexperimenter

toassessintelligencequotient,aswellastheEdinburgh

HandednessInventory(Oldfield,1971)todeterminehand

dominance.Demographicdataforallparticipantsis

pro-videdinTable1.

1_{Participants’}_{socioeconomic}_status_(SES)_was_classified_into_three

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Table1

Mean(SD)valuesforparticipantdemographics.

Variable Allparticipants

N 105

Age(years) 8.8(.6)

Tannerstage 1.6(.5)

K-BITcomposite(IQ) 108.3(11.3)

Socioeconomicstatus(SES) 1.9(.9)

Bodymassindex(kg/m2₎ _19.6_(4.7)

WRAT3readingachievement 110.0(13.1)

WRAT3spellingachievement 106.1(14.5)

WRAT3arithmeticachievement 101.3(15.8)

2.2. Measures

2.2.1. Academicachievementassessment

Academicachievementwasassessedindividuallyinthe contentareasofreading (i.e.,thenumber ofwords cor-rectly pronounced aloud), spelling (i.e., the number of words correctly spelled), and arithmetic (i.e., the num-berof mathematical computationscorrectly completed) using the Wide Range Achievement Test – 3rd edition (WRAT3;WideRange,Inc.,Wilmington,DE).TheWRAT3 isapaperandpencilbasedacademicachievement assess-mentthathasbeenage-normedreferencedandhasbeen stronglycorrelatedwiththeCaliforniaAchievementTest– Form E and theStanford Achievement Test (Wilkinson, 1993).

2.2.2. Neurocognitiveassessment

Neuroelectric and behavioral indices of performance

(i.e.,reactiontime,responseaccuracy)werecollectedin

responsetoaGo/NoGotask(seeTable2).IntheGotask,

participantswereinstructedtorespondwitharighthand

thumbpressonlywhentheysawaninfrequenttarget

stim-ulus(i.e.,acartoondrawingofalion)andtoignorethe

frequentnon-targetstimulus(i.e.,acartoondrawingofa

tiger).In theNoGotask, whichwaspresented following

theGotask,instructionsreversedtheresponsemappings

ofthetargetandnon-targetstimuli,suchthatparticipants

wererequired torespondtothefrequentstimulus(i.e.,

a cartoondrawingofa tiger)andinhibitthepre-potent

responsetotheinfrequentstimulus(i.e.,acartoondrawing

ofalion).ThismanipulationallowsfortheelicitationofaP3

inresponsetotheinfrequentstimulusforbothtasks,with

theamplitudeoftheP3beingrelatedtoworking

mem-orydemandsinresponsetotheGotasktargetcondition

(Polich,2007)andinhibitorycontroldemandsinresponse

totheNoGotasknon-targetcondition(Johnstone etal.,

2007;Kamarajanetal.,2005;Smithetal.,2004).Ineach

task,participantscompletedtwoblocksof125trials,with

Table2

TaskperformancefortheGo/NoGotask.

Measure Responseaccuracy(%correct) RT(ms)

Gotarget 91.7±9.2 521.9±77.9

Gonontarget 97.9±2.3 –

Nogotarget 79.6±14.9 419.9±71.7

Nogonontarget 71.2±14.3 –

Note:Mean±SD.

thelionandtigerstimulipresentedwithaprobabilityof .2and.8,respectively.Stimuliappearedfor200msona blackbackground,witha1700msinter-trialinterval.Prior tobeginningeachtask,participantscompletedablockof 40practicetrials.

2.2.3. ERPrecording

Electroencephalographic(EEG) activity wasrecorded from 64 electrode sites (FPz, Fz, FCz, Cz, CPz, Pz, POz, Oz, FP1/2, F7/5/3/1/2/4/6/8, FT7/8, FC3/1/2/4, T7/8, C5/3/1/2/4/6, M1/2, TP7/8, CB1/2, P7/5/3/1/2/4/6/8, PO7/5/3/4/6/8, O1/2) arranged in an extended montage based on the International 10-10 system (Chatrian et

al., 1985) using a Neuroscan Quik-cap (Compumedics,

Inc,Charlotte,NC). Recordingswerereferenced to

aver-agedmastoids(M1,M2),withAFzservingastheground

electrode, and impedance less than 10k. Additional

electrodes were placed above and below the left orbit

andontheoutercanthusofeacheyetomonitor

electro-oculographic (EOG) activity with a bipolar recording.

Continuous data were digitized at a sampling rate of

500Hz,amplified500timeswithaDCto70Hzfilter,anda

60HznotchfilterusingaNeuroscanSynamps2amplifier.

ContinuousdatawerecorrectedofflineforEOGartifacts

usingaspatialfilter(CompumedicsInc.,Neuroscan,2003).

Stimulus-locked epochs were created for correct trials

from −100 to 1000ms around the stimulus, baseline

correctedusingthe−100to0mspre-stimulusperiod,and

filteredusingazerophase shiftlow-passfilterat 30Hz

(24dB/octave).Trialswithartifactexceeding±75␮Vwere

rejected.TheP3componentwasevaluatedasthelargest

positivegoingpeakwithina350–600mslatencywindow,

respectively.Amplitudewasmeasuredasthedifference

betweenthe pre-stimulusbaseline and maximum peak

amplitude; peak latencywas defined asthe time point

corresponding to the maximum amplitude. Given that

thetopographic maximaoftheP3totheGotasktarget

conditionandtheNoGotasknon-targetconditionvaried

betweenthecentraland parietal regionsacross

partici-pants,P3 amplitude and latency wascalculated within

each participant and task as the mean value across 9

electrode sitesin a centro-parietalhot-spot(C1, Cz,C2,

CP1,CPz,CP2,P1,Pz,P2).Onaverage,31.6±6.8trialswere

includedintheGotaskanalysesand27.9±6.3trialswere

includedintheNoGotaskanalyses.

2.3. Procedure

2.3.1. Day1

Academicachievementassessment. On the firstvisit

to the laboratory, participants completed an informed

assent,EdinburghHandednessInventory(Oldfield,1971),

as well as the Kaufman Brief Intelligence Test (K-BIT;

KaufmanandKaufman,1990).Concurrently,participants’

legalguardianscompletedaninformedconsent,health

his-toryand demographicsquestionnaire, theADHD Rating

ScaleIV(DuPauletal.,1998),andamodifiedTannerStaging

System questionnaire. Participants were then

adminis-tered the Wide Range Achievement Test – 3rd edition

[image:3.561.42.263.73.168.2] [image:3.561.40.261.625.679.2]

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2.3.2. Day2

Neurocognitiveassessment.Onthesecondvisit(Mdays

fromday1=11.8±8.8),participantswerefittedwitha

64-channelQuik-cap(CompumedicsNeuroscanInc.,ElPaso,

TX)andseatedinasoundattenuatedroomwherethe

neu-roelectrictestingtookplace.Followingtheprovisionoftask

instructions,participantswereaffordedtheopportunityto

askquestionsandfortypracticetrialswereadministered

priortothestartoftesting.Uponcompletionofthelasttask

condition,all electrodeswereremovedand participants

werebriefedonthepurposeoftheexperiment.

3. Results

3.1. Dataanalysis

Bivariate correlation analyses were conducted using

Pearsonproduct-momentcorrelationcoefficientsbetween

the three domains of academic achievement and the

descriptivevariables(e.g.,age,sex,BMI,etc.),the

behav-ioralvariables (i.e., RTand accuracy)and ERPvariables

(i.e.,amplitudeandlatency).Hierarchicallinearregression

analyseswerethenperformedtoexplainvarianceinthe

domainsofacademicachievement.Thiswasundertaken

byregressingdomainsofacademicachievementon

sta-tisticallysignificantdescriptivecorrelates(e.g.,IQ)inStep

1andstatisticallysignificantbehavioralandERPvariables

inStep2.ThesignificanceofthechangeintheR-square

valuebetweenthetwoStepswasusedtojudgethe

inde-pendentcontributionofbehavioralandERPvariablesfor

explainingvarianceinacademicachievementbeyondthat

ofthedescriptivevariables.Thisanalysiswasperformed

separately for each of the three domains of academic

achievement.Aconservativep-valueof.01wasadopted

alongwithaone-tailedtestforjudgingstatistical

signif-icance in allanalyses given the number of tests in the

bivariateandregression analyses.Thedataanalysiswas

performedinPASWStatistics,18.0.

3.2. Bivariatecorrelations

The correlations between descriptive variables and

domainsofacademicachievementareprovidedinTable3.

K-BIT scoresand SESweresignificantly associated with

reading (r=.40 and r=.30, respectively),spelling (r=.36

andr=.30,respectively),andarithmetic(r=.49andr=.31,

respectively)performance. Gradewassignificantly

asso-ciatedwithreading(r=.29)andspelling(r=.25),butnot

arithmetic(r=.16),performance.Theothercorrelationsfor

age,sex,BMI,Tannerstage,andracewerenotstatistically

significant.

ThecorrelationsbetweenbehavioralandERPvariables

and domains of academic achievement are provided in

Table 3. P3 amplitude to the Go task target condition

wassignificantlyassociatedwithreading(r=.27),butnot

arithmetic(r=.18)andspelling(r=.16),achievement.P3

amplitudetotheNoGonon-targettaskwassignificantly

associatedwithreading(r=.24)andarithmetic(r=.23),but

notspelling(r=.16),achievement.Lastly,theaccuracyof

performancefortheNoGotasknontargetconditionwas

significantlyassociated witharithmetic(r=.31),but not

Table3

Bivariate correlationsbetween academicdomains anddemographic, behavioral,andneuroelectricvariables.

Variable Academicdomain

Reading Spelling Arithmetic

Age(years) .14 .03 −.09

Sex(0=female,1=male) .00 −.12 −.11

Bodymassindex(kg/m2₎

−.06 −.03 −.15

Tannerstage −.04 −.01 −.11

Grade .29* _.25* _.16

Socioeconomicstatus(SES) .30* _.30* _.31* Race(0=white,1=nonwhite) −.03 .11 .04 K-BITcomposite(IQ) .40* _.36* _.49* GotasktargetconditionRT −.01 −.00 .15 NoGotasknon-target

conditionRT

.00 −.16 −.19

Gotasktargetcondition responseaccuracy

.09 .12 .12

NoGotasknon-target conditionresponseaccuracy

.15 .20 .31*

GotasktargetconditionP3 amplitude

.27* _.16 _.18

NoGotasknontarget conditionP3amplitude

.24* _.16 _.23*

GotasktargetconditionP3 latency

−.07 .04 −.08

NoGotasknon-target conditionP3latency

−.14 −.08 .04

*_p_<_.01_with_one-tailed_test.

reading(r=.15)andspelling(r=.20),achievement.There

werenosignificantcorrelationsbetweeneitherreaction

timeorP3latencywithacademicachievement.

Finally,Pearsonproduct-momentcorrelationanalyses

wereconductedonP3amplitudeandlatencywithtask

per-formancemeasuresofRTandresponseaccuracybecauseof

theimportanceofthisrelationshipforstimulusevaluation

andinhibitorycontrol.Responseaccuracywasassociated

withP3amplitude(r=.20)andP3latency(r=−.22)during

infrequenttrialsintheNoGotask.GotargetRTwas

nega-tivelycorrelatedwithGoP3amplitude(r=−.20).Noother

significantcorrelationswereobserved.

3.3. Regressionanalysis

Fig.1illustratesgrand averagewaveformsand

topo-graphicplotsfortheGoandNoGotasks.Fig.2illustratesthe

topographic distributionof partialcorrelations between

P3 amplitudeandacademicachievementcontrollingfor

relateddescriptivevariables.

3.3.1. Readingachievement

The results for the first regression analysis are in

Table4.Thehierarchicalregressionanalysisindicatedthat

Grade (B=4.67, SE B=1.85, ˇ=.23) and K-BIT (B=0.36,

SE B=0.12, ˇ=.31) explained a statistically significant

(F=9.56,p=.001)amountofvarianceinreading

achieve-ment (R2=.22) in Step 1. Only P3 amplitudeto theGo

tasktargetconditionexplained a statisticallysignificant

(F=5.52, p=.005) and incremental amount of variance

in reading achievementbeyond thevariables in Step 1

(R2₌_.08)_in_Step_2._The_scatter_plot_for_the_bivariate

corre-lationbetweenP3amplitudetotheGotasktargetcondition

[image:4.561.281.504.81.312.2]

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[image:5.561.67.485.43.649.2]

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Fig.2. TopographicplotsillustratingthepartialcorrelationsbetweenP3amplitudeinresponsetotheGotasktargetconditionandReadingachievement controllingforK-BITandGrade(left)andP3amplitudeinresponsetotheNoGotasknon-targetconditionandArithmeticachievementcontrollingfor K-BIT(right)asafunctionofscalptopography.

Table4

Summaryofhierarchicalregressionanalysisforreadingachievement.

Variable B SEB ˇ

Step1

Grade 4.67 1.85 .23*

Socioeconomicstatus(SES) 1.49 1.45 .11 K-BITcomposite(IQ) 0.36 0.12 .31* Step2

Grade 4.63 1.78 .23*

Socioeconomicstatus(SES) 1.59 1.42 .11 K-BITcomposite(IQ) 0.35 0.12 .30* GotasktargetconditionP3amplitude 0.31 0.15 .21* NoGotasknontargetconditionP3amplitude 0.18 0.18 .10

Note:R2₌_.22_for_Step_1;_R2₌_.08_for_Step₂₍_p_<_.05). * _p_<_.05_with_two-tailed_test.

40 30 20 10 0 -10

Go Target P3 Amplitude

(μV) 80

100 120 140 160

Reading Achievement

(standard score)

Fig.3.Scatterplotwithlineofbestfitand95%confidenceintervalsfor thebivariateassociationsbetweenP3amplitudefortheGotasktarget conditionwithReadingachievement.

3.3.2. Spellingachievement

Wedidnotundertakeregressionanalysisforspelling

achievementastherewerenobehavioralorERPvariables

thatcorrelatedwiththisdomainofacademicachievement

inthebivariateanalysis.

3.3.3. Arithmeticachievement

The resultsfor thesecond regression analysisare in

Table5.Thehierarchicalregressionanalysisindicatedthat

K-BIT (B=0.62, SE B=0.14, ˇ=.44) explained a

statisti-callysignificant(F=16.58,p=.001)amountofvariancein

arithmeticachievement(R2=.25)inStep1.Bothresponse

accuracy (B=0.29, SE B=0.09, ˇ=.27) and P3

ampli-tude to the NoGo task non-target condition (B=0.52,

SE B=0.16, ˇ=.26) explained a statistically significant

(F=10.36,p=.001)and incremental amount of variance

inarithmeticachievementbeyondthevariablesinStep1

(R2₌_.13)_in_Step_2._The_scatter_plots_for_the_bivariate

cor-relationsbetweenaccuracyandP3amplitudetotheNoGo

tasknon-targetconditionwitharithmeticachievementare

inFig.4.

Table5

Summaryofhierarchicalregressionanalysisforarithmeticachievement.

Variable B SEB ˇ

Step1

Socioeconomicstatus(SES) 1.68 1.70 .10

K-BITcomposite(IQ) 0.62 0.14 .44*

Step2

Socioeconomicstatus(SES) 0.70 1.58 .04 K-BITcomposite(IQ) 0.63 0.13 .45* NoGotasknon-targetcondition

responseaccuracy

0.29 0.09 .27*

NoGotasknon-targetcondition P3amplitude

0.52 0.16 .26*

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100 90 80 70 60 50 40 30 70 90 110 130 150

a

b

A

rit

hm

et

ic A

c

hie

v

eme

nt

(s ta ndar d scor e )

NoGo No

n-Tar

get

Response

Accuracy

(% correct) 35 30 25 20 15 10 5 0 -5 70 90 110 130 150

A

rit

hm

et

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c

hie

v

em

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(s tand ar d scor e )

NoGo No

n-Tar

get

P3 Ampl

itud

e

(μV)

Fig.4. Scatterplotwithlineofbestfitand95%confidenceintervalsfor thebivariateassociationsbetweenaccuracy(a)andP3amplitude(b)for theNoGotasknon-targetconditionwithArithmeticachievement.

4. Discussion

Thepurposeofthepresentstudywastoprovideearly

evidence tosuggest that neuroelectric indices of

atten-tionandinhibitionmayserveasabiomarkerofacademic

achievementinpreadolescentchildren.Indeed,theresults

indicated that P3 amplitude accountedfor unique

vari-anceinreadingandarithmeticperformanceontheWRAT3,

beyond the variance explained by IQ and task

perfor-mance.Interestingly,theP3componentcollectedduring

twocognitivetasks(i.e.,Go/NoGo),eachtappingdifferent

aspectsofcognition,displayedadifferentialrelationship

withreadingandmathematicsachievement,indicatingthe

uniquenessof thispotentialinreflecting theunderlying

executivecontrolrequirementsofeachacademicsubject.

Specifically,P3amplitudeduringtheGotarget

condi-tionexhibitedasignificantrelationshiponlywithreading

achievement.TheoriessurroundingP3toa Gotask(i.e.,

also knownas theoddballtask) suggest that it reflects

neuronal activityassociated withrevisionof themental

representationofthepreviouseventwithinthestimulus

environment(Donchin,1981).P3amplitudeisdetermined

by the allocation of attentional resources when

work-ingmemoryisupdated(DonchinandColes,1988),such

thatP3issensitivetotheamountofattentionalresources

allocatedtoastimulus,withlargeramplitudereflecting

greater amounts of attention (Polich, 1987; Polich and

Heine,1996).Accordingly,thedatareportedhereinsuggest

thattheP3representsaneuroelectricindexofattention

allocationintheserviceofupdatingduringreading

com-prehension,withlargeramplitude(i.e.,greaterallocationof

attentionalresources)reflectingbetterupdatingcapability,

whichin turnmightrelatetosuperiorreading

achieve-ment.

Relative to arithmetic achievement, a relationship

wasobservedforinhibition,withincreasedachievement

related to better performance on the NoGo non-target

condition.BeyondtherelationshipwithNoGo task

per-formance, NoGo-P3 amplitude exhibited a significant

relationshipwitharithmeticachievement.Empirical

evi-denceforNoGo-P3indexingthecontrolofinhibitionexists

(Kamarajan et al., 2005), providing support for a

neu-roelectric markerreflecting theinhibitory requirements

underlyingsuperiormathematicsachievement.This

asser-tion is consonant with other research suggesting that

neural inhibition underlies the P3, with its amplitude

reflectingthesuppressionofextraneousneuronalactivity

(Polich,2007).Assuch,thecurrentfindingssuggestthat

neuroelectric measures of inhibitory control contribute

to the variance explained in mathematics achievement

beyondthatoftaskperformanceindicesofinhibition.

Todate,onlyoneotherreporthasdescribeda

relation-shipbetweenacademicachievementand aspectsof the

neuroelectricsystem.HirshandInzlicht(2009)observed

individual differences in error-related negativity (ERN)

componentamplitudetoaStroopcolor-namingtaskand

scholasticperformance of college-agestudents, as

mea-suredviagradepointaverage. Theyreportedthatlarger

ERNamplitudefollowingerrorswasrelatedtobetter

aca-demicperformance,andsuggestedthatgreateramplitude

ofthiscomponentreflectedanincreasedabilitytomonitor

performanceandactivateexecutivecontrolmechanisms

insupportofscholasticperformance(HirshandInzlicht,

2009).

Althoughtherewereaninsufficientnumberoferrors

ofcommission toreliablyassess theERNcomponentin

responsetothetasksusedwithinthecurrent

investiga-tion, the present findings further extend the literature

demonstrating unique relationships between working

memory and inhibitory aspects of executive control

withreadingandmathematicsachievement.Specifically,

the current findings are consonant with those of St.

Clair-Thompson and Gathercole (2006), who identified

relationships between working memory and inhibition

withacademicachievement.Suchapatternofresultswas

replicatedhereinwithtaskperformancemeasuresof

exec-utivecontrol,andextendedtoincludeneuroelectricindices

supportingtheseaspectsofcognition.Thesedataalso

sup-porttherelationshipbetweenintelligenceandacademic

achievement(Jensen,1998),butindicatethatintelligence

[image:7.561.54.245.57.435.2]

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performance and neuroelectric variables continued to

increasetheamountofvarianceaccountingforacademic

achievement.

Incontrast,taskperformancemeasuresoftheGo/NoGo

tasklargelydidnotrelatetoacademicachievement.That

is,onlyNoGonontargetaccuracywasrelatedtoarithmetic

achievement,whileRTacrossbothconditionswas

unre-latedtoacademicachievement.Thus,althoughresponse

accuracyduringtaskconditionsrequiringinhibitionmay

indexachievementinmathematics,suchafindingmight

alsosuggestthat theP3component is amore sensitive

marker of the various aspects of cognition underlying

academicachievement.Alternatively,thedemandsofthe

Go/NoGo task are such that behavioral measures

sim-plymay not reflect therelationship betweeninhibition

andworkingmemorywithacademicachievement.That

is, due to the relative ease of this task, little variance

existed in Go task performance. However, task

perfor-mancewasrelativelylowintheNoGotask,withnon-target

response accuracy being the only measures associated

witharithmeticachievement.Thus, it is possiblethat a

lackofvarianceincertaintaskconditionsmayhave

pro-hibitedsucharelationshipfrombeingobserved.Clearly,

furtherresearchisnecessarytodeterminetherelationship

betweenbehavioral measuresofinhibitionand working

memorywithacademicachievement.

Itisimportanttonotethatthesefindingsmaynot

sim-plyreflectamodelinwhichworkingmemorysolelyrelates

toreading achievementand inhibition solely relates to

mathematicsachievement.Infact,thereisawealthof

lit-eraturedemonstrating thatinhibition relatestoreading

and workingmemory relatesto mathematics(Bull and

Scerif,2001;Gernsbacher,1993;St.Clair-Thompsonand Gathercole,2006).Forinstance,inhibitionisnecessaryto

suppresstheautomaticactivationofinappropriateor

irrel-evant information for successful comprehension during

reading (Gernsbacher, 1993) and problem solving

dur-ingmathematics(PassolunghiandSiegel,2001).Further,

relevantinformationmustbeheldinthecontentsof

work-ingmemoryforefficientandeffectivecomprehensionand

problemsolvingduringtheseaspectsofachievement(Bull

andScerif,2001;St.Clair-ThompsonandGathercole,2006).

Assuch, itis highlyprobablythatthefindings reported

herein do not reflect a selective relationship between

specificcognitiveprocesses andspecificacademicskills.

Rather,thedatalikelyindicatethattheP3derived from

specific cognitive tasks reflect components of

achieve-mentthataredifferentiallyreflectedintheserelationships.

Someevidence exists todemonstrate that visuo-spatial

working memory, relative to inhibition, accounts for a

largerportionofthevariancewhenexplainingthe

relation-shipbetweencognitivecontrolandEnglishachievement

(St.Clair-ThompsonandGathercole,2006).Insupportof

this relationship,thecurrent data observedthat theP3

derivedfromataskrequiringvisuo-spatialattentionand

workingmemorywasrelatedtoreadingachievement.As

such,futureeffortsshouldbedirectedtowarddetermining

whethertheP3derivedduringothercognitivetasksmay

reflectthesesameareasofachievement(i.e.,aglobal

rela-tionship)andthusmayalsoserveasageneralbiomarkerfor

scholasticsuccess,orwhethertherelationshipsobserved

hereinareselectivetothecognitiveandacademic

achieve-ment tests.Through suchresearch,wemaynotonlybe

abletounpackaspectsofscholasticachievementbutwe

mayalsobeabletodeterminewhichunderlyingprocesses

accountfortheobservedvarianceinscholasticsuccess(i.e.,

workingmemory,inhibition,attention,longtermmemory,

relationalmemory,etc.).

Finally,itisinterestingtonotethatnorelationshipwas

observedfortheP3componentandspellingachievement.

Such a pattern of resultsindicates that theP3 maybe

an indicatorof performance forselect academicsubject

matter,ratherthanageneralindexofoverallscholastic

per-formance.However,thefactthattheP3fromtwodifferent

tasks(i.e.,GoandNoGo)reflecting differentialcognitive

functions wasobserved suggeststhat this neuroelectric

component might provide a novel approach to

assess-ingspecificaspectsofacademicachievementinchildren.

Overall,thefindingssupporttherelationshipofworking

memoryandinhibitoryaspectsofexecutivecontrolwith

academicperformance,andsuggestthatP3might

repre-senta uniquebiomarkerofachievement.Giventhatthe

child participantsinthis studywerecognitivelyhealthy

and withoutindividualeducationplans,suchameasure

mayhaveimportantimplicationsforeducationalpractice,

asitmayassistintheidentificationofsubclinical

cogni-tivedeficits,andalloweducatorstotailortheirindividual

lessonplanstoenhancelearning.

Authordisclosurestatement

Theauthorsdeclarenocompetingorconflicting

inter-ests.

Acknowledgements

Supportfor ourresearchand thepreparation of this

manuscript was provided by a grant from theNational

InstituteofChildHealthandHumanDevelopment(NICHD)

to Charles Hillman (RO1 HD055352) and a fellowship

awardedtoMatthewPontifexthroughtheNICHD

Devel-opmentalPsychobiologyandNeurobiologyTrainingGrant

attheUniversityofIllinois(2T32HD007333).

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