visual word recognition in competitive Scrabble players as measure

16 Pages·2016·1.61 MB·English

by  Andrea B. Protzner

cortex 75 (2016) 204e219
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This is your brain on Scrabble: Neural correlates
of visual word recognition in competitive Scrabble
players as measured during task and resting-state
Andrea B. Protzner a,b,c,*, Ian S. Hargreaves a,b, James A. Campbell a,
Kaia Myers-Stewart a, Sophia van Hees a,b, Bradley G. Goodyear b,c,d,e,f,
Peter Sargious g,h and Penny M. Pexman a,b,c
aDepartmentofPsychology,UniversityofCalgary,Calgary,Alberta,Canada
bHotchkissBrainInstitute,UniversityofCalgary,Calgary,Alberta,Canada
cSeamanFamilyMRResearchCentre,UniversityofCalgary,FoothillsMedicalCentre,Calgary,Alberta,Canada
dDepartmentofRadiology,UniversityofCalgary,FoothillsMedicalCentre,Calgary,Alberta,Canada
eDepartmentofClinicalNeurosciences,UniversityofCalgary,FoothillsMedicalCentre,Calgary,Alberta,Canada
fDepartmentofPsychiatry,UniversityofCalgary,FoothillsMedicalCentre,Calgary,Alberta,Canada
gDepartmentofMedicine,UniversityofCalgary,FoothillsMedicalCentre,Calgary,Alberta,Canada
hInstituteforPublicHealth,UniversityofCalgary,Calgary,Alberta,Canada
a r t i c l e i n f o a b s t r a c t
Articlehistory: CompetitiveScrabbleplayersdevoteconsiderabletimetostudyingwordsandpracticing
Received9September2014 Scrabble-relatedskills(e.g.,anagramming).Thistrainingisassociatedwithextraordinary
Reviewed18October2014 performance in lexical decision, the standard visual word recognition task (Hargreaves,
Revised16December2014 Pexman, Zdrazilova & Sargious, 2012). In the present study we investigated the neural
Accepted23March2015 consequencesofthislexicalexpertise.Usingbothevent-relatedandresting-statefMRI,we
ActioneditorSonjaKotz compared brain activity and connectivity in 12 competitive Scrabble experts with 12
Publishedonline1April2015 matchednon-expertcontrols.Resultsshowedthatwhenengagedinthelexicaldecision
task (LDT), Scrabble experts made use of brain regions not generally associated with
Keywords: meaning retrieval in visual word recognition, but rather those associated with working
Expertise memoryandvisualperception.Theanalysisofresting-statedataalsoshowedgroupdif-
fMRI ferences,suchthatadifferentnetworkofbrainregionswasassociatedwithhigherlevels
Languagenetworks ofScrabble-relatedskillinexpertsthanincontrols.
Lexicalprocessing ©2015TheAuthors.PublishedbyElsevierLtd.Thisisanopenaccessarticleunderthe
Resting-state CCBY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Abbreviations: BA, Brodmann's area; COWAT, Controlled Oral Word Association Test; LDT, lexical decision task; LIFG, leftinferior
frontalgyrus;LV,latentvariable;NAART,NorthAmericanAdultReadingTest;NASPA,NorthAmericanScrabblePlayersAssociation;
PLS,partialleastsquaresanalysis;RART,RevisedAuthorRecognitionTest;WAIS,WeschlerAdultIntelligenceScale.
* Correspondingauthor.DepartmentofPsychology,UniversityofCalgary,2500UniversityDriveNW,Calgary,T2N1N4,Alberta,Canada.
E-mailaddresses:[email protected](A.B.Protzner),[email protected](I.S.Hargreaves),[email protected](J.A.Campbell),
[email protected](K.Myers-Stewart),[email protected](B.G.Goodyear),[email protected](P.Sar-
gious),[email protected](P.M.Pexman).
http://dx.doi.org/10.1016/j.cortex.2015.03.015
0010-9452/© 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://
creativecommons.org/licenses/by-nc-nd/4.0/).
cortex 75 (2016) 204e219 205
Alargebodyofresearchisdedicatedtoprovidingatheoryfor normallyassociatedwiththeprocessingofspokenlanguage)
the surprising observation that very high levels of achieve- but also changes the organization of the visual cortex (spe-
ment within a domain tend to be domain-specific, and not cifically,theso-calledVisualWordFormAreadevelopsinthe
baseduponthegeneralsuperiorityofexperts(Chase&Simon, fusiformgyrus),andreinforceswhitematter(WM)tractsthat
1973).Thoughdebatecontinuesastotherelativeroleplayed areassociatedwithlefttemporo-parietallanguagenetworks
byinnatefactorsanddedicatedpracticeinthedevelopmentof (i.e., the arcuate fasciculus; Thiebaut de Schotten, Cohen,
expertperformance(Ericsson,2014;Grabner,2014;Hambrick Amemiya,Braga,&Dehaene,2012).
et al., 2014), there is agreement that very high levels of Readingisamultidimensionalskillthatcanbeframedas
achievement are supported by the emergence of unique thedynamicconstructionofinformationinvolvingshape(i.e.,
knowledge structures. Drawing largely from studies con- orthography), sound (i.e., phonology) and meaning (i.e., se-
trastingchessexpertsandnon-experts,theseuniqueknowl- mantics; Seidenberg & McClelland, 1989). Interestingly, the
edge structures can be framed in terms of strategic or relative contribution to reading made by any of these di-
cognitivedifferences(e.g.,quickperceptionofboardpatterns, mensionsvariesasafunctionoftaskdemands(Balota,Paul,&
automatic generation of ‘next move’, etc.) that set experts Spieler, 1999), the information elicited by the stimulus (e.g.,
apart from non-experts (Chase & Simon, 1973; Ferrari, wordsvaryin termsoftheamount ofsemanticinformation
Didierjean, & Marmeche, 2008). The emergence of these theyevoke;Yap,Pexman,Wellsby,Hargreaves,&Huff,2012),
knowledgestructureshasalsobeenassociatedwithchanges andeventherelativeavailabilityofallthreetypesofinforma-
intheneuralsubstratesthatsupportchessexpertversusnon- tion over time (Holcomb & Grainger, 2006). Recent research
expertperformance(Grabner,Neubauer,&Stern,2006). suggests that visual word recognition also is shaped by our
Anotherapproachtothestudyofexpertiseeschewsdirect experience using written words for different purposes. For
comparisonsbetweenexpertsandnon-expertsinfavorofan example, competitive Scrabble players have extraordinary
approachthattrackstheemergenceofdomain-specificability word recognition experience in that they dedicate vast
though extensive training. These studies focus mostly on amountsoftimetostudyingwordliststoimprovetheirgame
traininginthedomainsofperception,attention,andworking performance (Halpern & Wai, 2007; Hargreaves, Pexman,
memory(andnotchess),andshowwithfunctionalmagnetic Zdrazilova,&Sargious,2012;Tuffiash,Roring,&Ericsson,2007).
resonance imaging (fMRI) that domain-specific training can Scrabble is a popular board game in which two players
result in both reductions and increases in activation (e.g., alternatestrategicallyformingwordsoutofsevenrandomly
Bassoetal.,2013;Olesen,Westerberg,&Klingberg,2004).For drawn lettered tiles. Tiles are placed within squares on a
example,inastudybyOlesenetal.(2004),workingmemory standard15(cid:3)15squaregameboard.Afterthefirstwordhas
training led to increased activity in areas associated with beenplayed,allsubsequentwordsmustattachtoatleastone
workingmemoryandselectiveattention(lateralfrontaland tilealreadyplayed,andformawordwhenreadlefttorightor
parietalcortices),andsimultaneousdecreasesinareasasso- toptobottom.Ifone'sopponentbelievesthatanewlycreated
ciated with task effort (anterior cingulate cortex). The key wordwouldnotbefoundinadesignateddictionary,heorshe
finding,assummarizedbyJonides(2004),isthataftertraining, maychallengetheplay,andifcorrect,alltilesplayedonthat
the neural substrates that support performance remain un- turn are returned to the offending player and no points are
changed,butshowdifferentlevelsofactivation(increasesor awarded.Conversely,ifachallengedwordisacceptable,the
decreases).Thisstandsincontrasttostudiescomparingex- playerissuingthechallengemaylosehisorherturn.Assuch,
perts to non-experts, which reveal that experts (though word recognition is equally important in responding to an
relyingonsimilarnetworksascontrols)tendtorecruitaddi- opponent'splayasinmakingone'sown.Thepurposeofthe
tional areas when solving domain-specific tasks (e.g., gameistomaximizeyourcumulativescore,ascomparedwith
Gauthier,Skudlarski,Gore,&Anderson,2000).Inareviewof youropponent's,byformingmultiplewords,takingadvantage
numerous studies, Guida and colleagues argued that these ofpremiumsquares,orsecuringabonusforplayingallseven
twoseeminglycontradictoryfindingsactuallyrepresenttwo tiles. Recent research suggests that the degree of Scrabble
stagesinthedevelopmentofexpertise(Guida,Gobet,Tardieu, expertise(ascapturedthroughanofficialratingsystem)can
& Nicolas, 2012). As learners gain experience in a domain, beattributedtotimespentinpracticeandnottootherfactors,
increasing efficiency can lead to increases or decreases in suchas workingmemoryorperceptualprocessing(Tuffiash
activation; but as learners become experts, new knowledge et al., 2007). Hargreaves et al. (2012) demonstrated that this
structures begin to emerge and are supported by functional extended, deliberate practice is associated with exceptional
reorganization. performanceinthestandardwordrecognitiontask,thelexi-
Numerouslinesofevidenceconvergeontheideathatthe caldecisiontask(LDT;i.e.,“isitaword?”).Specifically,Scrabble
emergenceofuniqueknowledgestructuresreliesonacorre- expertsarefasterthannon-expertsinmakingword/nonword
spondingchangeinthefunctionalarchitecturethatunderlies decisions,especiallyforverticallypresentedwords,andshow
behavior.Ourabilitytoreadwords,forinstance,hasbeentied a decreased reliance on word meaning. Accessing word
to the reshaping of a network of regions that are normally meaningisviewedasareliablecuethatastimulusisaword,
recruited in visual pattern recognition (Behrmann & Plaut, and the presence of meaning is thought to facilitate
2013; Dehaene et al. 2010). Dehaene and colleagues used responding in the LDT (Pexman, Lupker, & Hino, 2002).
fMRI to compare cortical activation in illiterate ((cid:1)school, Scrabbleexpertsshowlessofarelianceonmeaning,whichis
(cid:1)literacy),formerly-illiterate((cid:1)school,þliteracy)andliterate congruent with anecdotal reports suggesting that many
adults(þschool,þliteracy).Theyconcludedthatliteracynot Scrabbleplayersdonotlearnthemeaningsofthewordsthey
onlychangeslanguagenetworks(involvingnetworksthatare study (Fatsis, 2002), and that experts were able to judge
206 cortex 75 (2016) 204e219
lexicality by focusing on other forms of information (e.g., writteninformedconsentwasobtainedfromallparticipants
orthographicinformation). priortoparticipation.
OneremainingquestionishowScrabblepracticechanges
theneuralsubstratesthatsupportvisualwordrecognition.In 1.2. Cognitivetasks
the Hargreaves et al. (2012) study Scrabble players and con-
trols were matched in terms of vocabulary, print exposure, Cognitivetestingwasperformedtoestablishthatgroupdif-
age,yearsofeducation;allfactorsthatcaptureourhistoryof ferences between the Scrabble experts and controls were
experience with written words. However, Hargreaves et al. confined to Scrabble-related expertise (Hargreaves et al.,
observed that the dedicated practice of Scrabble experts 2012), and were completed on a separate day, prior to fMRI
clearly set them apart from controls in LDT performance. scanning.Weadministeredtoeachparticipantthefollowing
Giventhechessliteratureshowingfunctionalreorganization, tests: (1) Perceptual speed was assessed with the WAIS III
it seems likely that the expanded behavioral repertoire of Digitesymbolcodingtask(Wechsler,1997),inwhichpartici-
Scrabbleplayersissupportedbydissociablenetworksinthe pantssawninedigitesymbolpairs,andthenalistofdigitsfor
brain. Our particular question is: what is the nature of that which they were asked to provide matching symbols. They
reorganization?Inordertoapproachthisquestion,weused weregiven120sectocompleteasmanytrialsaspossible;(2)
fMRI and investigated the neural underpinnings of Scrabble Category and letter/word fluency were assessed with the
expertisebycomparingbrainactivityincompetitiveScrabble Controlled Oral Word Association Test (COWAT; Spreen &
expertsandmatchedcontrols.Wethenexaminedhowindi- Strauss, 1998). Participants were asked to verbally generate
vidualdifferencesinScrabbleskillarerelatedtobrainactivity. as many exemplars as possible, in 60 sec, from each of the
WeoperationalizedScrabbleskillsintermsofanagramming followingcategories:animal names(servingas a controlfor
skill(unlikeofficialScrabblerankingsthisisameasurethat generationfluency),andwordsbeginningwiththeletter“F”,
can be obtained for both experts and non-experts). Our the letter “A”, the letter “S”, and the prefix “UN”, following
expectation was that within-group skill differences would Tuffiashetal.(2007);(3)Exposuretoprintwasassessedwith
likelyinvolvethekindofefficiency-drivenincreasesandde- the Revised Author Recognition Test (Acheson, Wells, &
creases in activation associated with training studies, while MacDonald, 2008), in which participants were presented
between-group differences would likely involve a break or with a list of 130 names and were asked to identify which
dissociation, as in studies on chess expertise. Finally, we nameswerethoseofrealauthors;(4)Vocabularywasassessed
tested if within- and between-group Scrabble-skill-related withtheshortformoftheNorthAmericanAdultReadingTest
network alterations could be identified even when partici- (NAART35; Uttl, 2002), in which participants were asked to
pants were not engaged in an active language task, during pronounce35Englishwordsofirregularspellingasaccurately
resting-state. To our knowledge the neuralconsequences of as possible; (5) Anagramming skill was assessed by asking
expertisehavenotpreviouslybeenexaminedinthisway. participants to solve 51 computer-presented anagrams
(Tuffiash et al., 2007). The order of these tests was counter-
balanced across participants with the additional stipulation
1. Method that tasks requiring a verbal response (i.e., COWAT and
NAART35)didnotfollowoneanother.Meanscoresforthese
1.1. Participants measuresarepresentedinTable1.
Fourteen competitive Scrabble players and 14 age-matched 1.3. fMRItasks
non-expertcontrolsparticipatedinthisstudy.TwoScrabble
participantsandonecontrolparticipantwereexcludeddueto Resting-statescansusedinthecurrentstudywerecollected
excessivemotionduringscanning.Anadditionalcontrolwas immediately after the anatomical scans (i.e., prior to
excludedtopreservepairwisematching.Thus,datafrom12 completing the LDT). The resting-state scan duration was
competitiveScrabbleplayers(7female)and12age-matched 6min,andparticipantsweresimplyaskedtofixateonacross
non-expert controls (7 female) were used in our analyses. atthecenterofaprojectionscreen,whichwaspositionedat
Competitive Scrabble players were recruited from extensive the back of the MR scanner and viewed by the participant
advertisingovera1-yearperiodatlocalandnationalScrabble throughamirrormountedontheheadcoilabovetheeyes.
competitionsheldintheCalgaryarea.Controlswererecruited FortheLDTtask,wordandnonwordstimuliwerecreated
throughcommunityadvertisingintheCalgaryareaduringthe and presented using Presentation (Neurobehavioral Systems,
sameperiod.Allparticipantswereright-handed.Participants Inc.,Albany,CA)andavideoprojectionsystem(Avotec,Inc.,
wererecruitedtoparticipateinalargerstudyinvolvingboth Stuart, FL). For each LDT trial, participants made a yes/no
fMRI and EEG sessions, but the data presented here are for lexical decision using two buttons on an MR-compatible
those Scrabble and control participants who completed the responsepad(LuminaLU400-PAIR,CedrusCorp.,SanPedro,
fMRI session. All participants underwent comprehensive CA). Three continuous LDT runs (total time was approxi-
screeningtoensurethattheyhadnoneurologicaldisorders, mately 30 min) each included 80 word and nonword trials,
were not experiencing any psychiatric illnesses, were not presentedinrandomorder.Halfofthetrialswerepresentedin
taking any psychotropic medications, and did not have any ahorizontalorientationwhiletheotherhalfwerepresentedin
visionorhearingdeficitsthatmightinterferewithtaskper- a vertical (i.e., marquee) orientation. Orientation varied
formance. Ethics approval was obtained from the Conjoint randomly between trials, but was counterbalanced across
HealthResearchEthicsBoardoftheUniversityofCalgary,and participants. Each trial began with the presentation of a
cortex 75 (2016) 204e219 207
Table1eMeancharacteristicsofparticipantgroups(standarddeviationsinparentheses).
Scrabbleexperts Controls t-valueforgroupdifference
Age 59.2(16.8) 59.1(15.5) 0.0
YearsofEducation 16.2(3.1) 16.7(2.9) 0.4
WAISDigit-SymbolSpeed 78.7(21.5) 68.8(14.9) 1.3
NAARTVocabulary 25.4(5.9) 21.8(8.8) 1.1
RARTPrintExposure 30.9(8.6) 27.9(15.9) 0.5
COWATWordFluencyeF 21.9(6.6) 16.4(5.4) 2.2*
COWATWordFluencyeA 20.0(5.7) 14.1(6.9) 2.2*
COWATWordFluencyeS 21.5(5.1) 17.1(5.8) 1.9~
COWATWordFluencyeUN 12.1(2.9) 9.4(3.6) 2.0~
COWATWordFluencyeAnimals 23.6(5.9) 20.6(7.5) 1.0
AnagramAccuracy(%) 55.2(14.4) 19.3(8.4) 7.4***
NASPARating 1120.3(272.6) n/a n/a
~p<.10,*p<.05;**p<.01;***p<.001.
Note:WAIS ¼ Weschler Adult Intelligence Scale; NAART¼NorthAmericanAdult Reading Test;RART ¼ RevisedAuthor Recognition Test;
COWAT¼ControlledOralWordAssociationTest;NASPA¼NorthAmericanScrabblePlayersAssociation.
fixation point (500 msec), which was then replaced with a WI, U.S.A.). FMRI data were acquired in an interleaved slice
stimulus(wordornonword)for2000msecwitharandomized order(TR¼2000msec;TE¼30msec;37slices,220mmFOV,
inter-trial interval ranging from 3500 to 7500 msec with a 64(cid:3)64matrix,resultinginavoxelsizeof3.75(cid:3)3.75(cid:3)3.40).
meanof5500msec.Avariableinter-trialintervalwasusedto Three-dimensional anatomical scans were acquired with
increasethedetectabilityofhemodynamicresponsestotrials higher spatial resolution T1-weighted sequence (MP-RAGE:
(Birn,Cox,&Bandettini,2002).TheLDTstimuliconsistedof 236slices,256mmFOV,256(cid:3)256matrix,resultinginavoxel
144wordsand96nonwords,similartothoseusedpreviously sizeof1.0(cid:3)1.0(cid:3)1.0mm).
(Binder, Westbury, McKiernan, Possing, & Medler, 2005;
Hargreavesetal.,2012).Wordlength,meanLevenshteindis- 1.5. fMRIdatapreprocessing
tance to the nearest 20 orthographic neighbors (OLD20;
Yarkoni,Balota,&Yap,2008),ageofacquisition(Kuperman, Weperformeda number of preprocessingstepsintendedto
Stadthagen-Gonzalez, & Brysbaert, 2012), imageability reduce data artifacts (see Garrett, Kovacevic, McIntosh, &
(Cortese & Fugett, 2004), print frequency and contextual Grady,2010;Protzner,Kovacevic,Cohn,&McAndrews,2013;
dispersion(bothfromBrysbaert&New,2009)arepresentedin Protzner, Mandzia, Black, & McAndrews, 2011). Using SPM8
Table 2. As illustrated in Table 2, words were matched to (http://www.fil.ion.ucl.ac.uk/spm/, Friston et al., 1995), time
nonwordsonorthographic(visual)characteristics.Trialswere series data were spatially coregistered to correct for head
presented in a different random order to each participant. motionbyusinga3DFouriertransforminterpolation.Func-
Becauseourgoalinthepresentanalyseswastoexaminethe tional data were corrected for artifacts via independent
neuralcorrelatesoftypicalLDTtrialsforScrabbleexpertsand component analysis (ICA) within separate runs, as imple-
controls, we restricted our analyses to the trials in which mented in FSL/Melodic (Beckmann & Smith, 2004). Probabi-
words or nonwords were presented in the horizontal orien- listicICAassumesthatartifactspresentinfMRIdatafollowa
tation.Thesearethetrialsonwhich,inthepreviousbehav- non-Gaussian distribution. It is a blind source separation
ioral study (Hargreaves et al., 2012), the performance of technique that decomposes a two-dimensional data matrix
Scrabbleexpertsandcontrolswasmostsimilar.Verticalpre- (time by voxels) into a set of time courses with associated
sentation is not typical in the LDT. As such, the data from spatialmaps,whichjointlydescribethetemporalandspatial
verticaltrialswillbeusedtoaddressfuturequestionsthatare characteristics of statistically independent latent variables
notthefocushere. (LVs)(sourcesignals).Artifactswereidentified andremoved
following the guidelines outlined by Beckmann and Smith
1.4. MRIdataacquisition (2004). Specifically, the ICA denoising procedure was per-
formedbyoneoftheauthors(K.M.S),whoidentifiedartifac-
Anatomicalandfunctionaldatawereacquiredona3Twhole- tualcomponentsforeachparticipantandeachrunbasedon
body MR scanner (Discovery 750; GE Healthcare, Waukesha, combined information from the spatial distribution, time
Table2eMeancharacteristicsforwordandnonwordstimuli(standarddeviationsinparentheses).
OLD Length AoA IMG LgWF LgCD
Words 1.87(.45) 5.22(1.12) 4.61(.82) 4.58(1.62) 2.43(.87) 2.35(.64)
Nonwords 1.97(.50) 5.26(1.08)
Note:OLD¼OrthographicLevensteinDistance;Length¼lengthinletters;AoA¼AgeofAcquisition;IMG¼Imageability;LgWF¼Logfrequency
fromSUBTLEXusnorms;LgCD¼Logcontextualdispersion.
208 cortex 75 (2016) 204e219
series, and spectral power distribution of ICA components. experience in having excellent registration of these struc-
Themostcommoncharacteristicsofartifactswerefocalityof tures.ImageswerethenregisteredtotheMNIEPItemplateas
the spatial distribution, ratio of weights within ventricles implemented in SPM8 (http://www.fil.ion.ucl.ac.uk/spm/,
versusbrain,ratioofweightsalongtheouteredgeofthebrain Fristonetal.,1995),andvoxelsignalwasspatiallysmoothed
versustherestofthebrain,relativespectralpowerdistribu- usingan8-mmGaussiankernel.
tion within low-, medium- and high-frequency ranges, and
presence of spikes within the time course. Identified noise 1.6. fMRIanalyses
componentsweresubsequentlysubtractedfromthedataset
(usingthefsl_regfiltfunctionfromFSL). Weaddressedthreequestionsinourimageanalyses.First,we
Becauseweusedaconservativeapproachduringidentifi- assessed whetherthere weredifferences between groups in
cationofartifacts,voxeltimeserieswerefurtheradjustedby condition-dependentbrainactivity.Thisanalysisallowedus
regressingoutmotioncorrectionparameters,WM,andcere- alsotoidentifyaregionofinterest(ROI;i.e.,seedvoxel)that
brospinalfluid(CSF)timeseries.ForWMandCSFregression, could serve as the reference region for our functional con-
oneoftheresearchers(K.M.S)extractedtimeseriesfromun- nectivity analysis. The choice of region was based on two
smootheddatawithinsmallregionsofinterest(ROIs)inthe criteria:(1)locationintheleftinferiorfrontalgyrus(LIFG),and
corpuscallosumandventriclesofeachparticipantusingFSL (2)commonmodulationofactivityacrossgroups.Second,we
view.ROIswereselectedsuchthattheyweredeepwithineach assessedwhetherthereweregroup-dependentdifferencesin
structureofinterest(corpuscallosumandventricles)toavoid thecorticalregionsthatcorrelatedwithindividualdifferences
signal contamination from externaltissues dueto misregis- inanagramming(Scrabble)skill.Forthisanalysis,wetested
tration and partial volume effects. The rationale for using the hypothesis that the pattern of activation that supports
smallROIsandunsmootheddatawastoensurethattheROIs betteranagramming(Scrabble)skilldiffersbetweenScrabble
would not contain any signal of interest (i.e., gray matter expertsandcontrols.Third,weassessedwhethertherewere
signal)foranyofthesubjects.Thechoiceofasingle4mm3 group-dependent differences in resting-state LIFG networks
voxel within the corpus callosum for WM and a same-size that were correlated, as a whole, with anagramming
voxel within one lateral ventricle for CSF was based on our (Scrabble)skill.
Fig.1eBrainimagesandbrainscoresbargraphforLV1fromthetwo-group,nonrotatedtask-PLSanalysis.Onthebrain
images,weillustrateregionswithmaximaldifferentiationbetweenwordandnonwordtrialsforbothcontrolandScrabble
expertgroups.Thebrainisdisplayedin3-planeviewaccordingtoneurologicalconvention(L¼L).Yellowregionsrepresent
increasedword-relatedactivity,andblueregionsrepresentincreasednonword-relatedactivity.Thebrainscoresbargraph
capturesthemeanbrainscoreforeachconditionineachgroup.Theerrorbarsindicatethe95%confidenceintervalsderived
frombootstrapestimation.
cortex 75 (2016) 204e219 209
Becauseourquestionsarebasedontheassumptionthat p<.05],andwereavailableforcontrolsaswellasScrabble
language is the result of the integrated activity of dynamic experts. We performed PLS on a correlation matrix,
brainnetworksratherthantheindependentactivityofany comprised of the covariance between voxel signal and
single brain region (Behrmann & Plaut, 2013; Fedorenko & measures of behavior (anagram scores) across participants
Thompson-Schill,2014),ourapproachtofMRIanalysiswas ineachgroup.BehaviorPLSresultsareverysimilartothose
designedto reveallanguagenetworksthroughmultivariate from task PLS, except LVs show similarities or differences
techniques.Tothisend,allanalyseswere performedusing between groups and experimental conditions in terms of
partial least squares (PLS; http://www.rotman-baycrest.on. brain-behaviorcorrelations.
ca/index.php?section¼345), which is a multivariate anal-
ysis technique that identifies groups of brain regions Table3eLocalmaximaforthetwo-group,nonrotatedtask
distributed over the entire brain that together covary with PLSLV1,taskmaineffect.
some aspect of the experimental design (McIntosh,
Bookstein, Haxby, & Grady, 1996; McIntosh, Chau, & Region BA x y z BSR
Protzner, 2004). This is in contrast to the more typically LeftLateralizedPositiveSaliences
used univariate analysis that assesses the significance of LeftSuperiorFrontalGyrus 8 (cid:1)33 36 45 4.59
LeftAnteriorCingulate 32 (cid:1)9 51 0 4.62
eachregionindependently.Toallowcomparisonwithwork
LeftMiddleCingulate 31 (cid:1)6 (cid:1)33 45 4.72
published using univariate analyses, in addition to our
LeftAngularGyrus 39 (cid:1)48 (cid:1)69 27 3.69
nonrotated task PLS (the first analysis described in detail LeftMiddleTemporalGyrus 39 (cid:1)45 (cid:1)57 15 7.12
below),weanalyzedthemaineffectsoflexicalityandgroup, LeftMiddleTemporalGyrus 21 (cid:1)51 3 (cid:1)27 3.70
and the lexicality by group interaction with SPM8 (http:// LeftPrecuneus 7 (cid:1)15 (cid:1)30 39 6.19
www.fil.ion.ucl.ac.uk/spm/,Fristonetal.,1995). LeftCuneus 19 (cid:1)3 (cid:1)72 24 3.82
LeftLingualGyrus 19 27 (cid:1)57 (cid:1)6 5.23
RightLateralizedPositiveSaliences
1.6.1. NonrotatedtaskPLS
RightSuperiorFrontalGyrus 10 18 63 (cid:1)3 4.13
Task PLS identifies LVs that highlight similarities or differ- RightPrecentralGyrus 4 24 (cid:1)24 69 4.79
ences between participant groups and/or experimental con- RightPostCentralGyrus 2 66 (cid:1)15 18 4.15
ditions. The most commonly used version of task PLS is RightPutamen 33 (cid:1)9 (cid:1)6 4.01
similar to other multivariate techniques, such as principal RightInsula 45 6 (cid:1)3 4.91
component analysis, in that contrasts across conditions or RightAnteriorCingulateCortex 32 6 51 (cid:1)3 4.66
RightMiddleCingulateCortex 31 12 (cid:1)21 45 4.30
groups typically are not specifiedin advance; rather, the al-
RightMiddleTemporalGyrus 21 60 3 (cid:1)21 4.77
gorithm extracts LVs explaining the covariance between
RightSupraMarginalGyrus 40 60 (cid:1)27 30 5.25
conditions and brain activity in order of the amount of RightPrecuneus 7 9 (cid:1)57 21 4.96
covariance explained (with the LV accounting for the most RightLingualGyrus 18 12 (cid:1)69 (cid:1)6 6.07
covariance extracted first). We used a nonrotated version of LeftLateralizedNegativeSaliences
task PLS, in which a priori contrasts restrict the patterns LeftMedialFrontalGyrus 8 0 33 48 (cid:1)6.92
derivedfromtaskPLS(McIntosh&Lobaugh,2004).Theeffects LeftMiddleFrontalGyrus 46 (cid:1)51 39 18 (cid:1)3.78
LeftMiddleFrontalGyrus 6 (cid:1)36 12 57 (cid:1)5.94
of interest were a main effect of lexicality (word versus
LeftInferiorFrontalGyrus 45 (cid:1)45 36 (cid:1)3 (cid:1)7.86
nonword activity), a main effect of group (Scrabble experts
LeftInferiorFrontalGyrus 44 (cid:1)45 15 18 (cid:1)7.35
versuscontrols),andalexicalitybygroupinteraction. LeftSupplementaryMotorArea 6 (cid:1)9 6 63 (cid:1)7.41
PLSresultsareexpressedintermsofLV's,eachofwhich LeftPrecentralGyrus 4 (cid:1)51 0 48 (cid:1)7.42
contains three vectors. The first vector contains a singular LeftInsula (cid:1)24 15 (cid:1)9 (cid:1)3.99
value, which indicates the strength of the effect expressed LeftMiddleTemporalGyrus 37 (cid:1)48 (cid:1)57 (cid:1)3 (cid:1)3.86
by the LV. The remaining two vectors relate experimental LeftMiddleTemporalGyrus 21 (cid:1)63 (cid:1)30 3 (cid:1)4.26
LeftInferiorTemporalGyrus 37 (cid:1)48 (cid:1)63 (cid:1)6 (cid:1)5.73
design and brain activity. The experimental design vector
LeftSuperiorPartietalLobule 7 (cid:1)30 (cid:1)63 48 (cid:1)5.57
contains task saliences, which indicate the degree to which LeftInferiorParietalLobule 40 (cid:1)27 (cid:1)60 42 (cid:1)5.10
each task within each group is related to the brain signal RightLateralizedNegativeSaliences
pattern identified in the LV. These task saliences can be RightMiddleFrontalGyrus 46 45 33 18 (cid:1)5.14
interpretedasthecontrastthatcodestheeffectdepictedin RightMiddleFrontalGyrus 8 51 24 39 (cid:1)4.58
the LV. The brain signal vector contains voxel saliences. RightMiddleFrontalGyrus 6 30 3 57 (cid:1)4.27
RightInferiorFrontalGyrus 47 33 33 (cid:1)9 (cid:1)5.52
Theseare numerical voxel weights thatidentifythecollec-
RightInferiorFrontalGyrus 44 54 21 24 (cid:1)5.12
tion of voxels that, as a whole, are most related to the ef-
RightSupplementaryMotorArea 6 6 21 60 (cid:1)6.48
fectsexpressedintheLV.NotethatforeachLV,thereisone RightInferiorTemporalGyrus 37 51 (cid:1)54 (cid:1)15 (cid:1)6.06
saliencepervoxelthatappliesfor allgroupsand allexper- RightInferiorParietalLobe 40 45 (cid:1)36 51 (cid:1)6.39
imentalconditions. RightFusiformGyrus 37 39 (cid:1)48 (cid:1)18 (cid:1)4.13
Note: BA¼Brodmann's area. Regions indicate the gyral locations
1.6.2. BehaviorPLS and BA of the cluster peak. Gyral locations and BA were then
We used behavior PLS to examine group- and task- determinedbyreferencetoTalairachandTournoux(1988).Only
dependent correlations between anagramming skill and voxelsinsupratentorialregionsarereported.x,y,andzindicate
voxel signal. We operationalized Scrabble skill with voxelcoordinatesinMNIspace.BSR¼bootstrapratio,andrepre-
sentseachvoxel'sPLSparameterestimatedividedbyitsstandard
anagramming scores, which showed a strong positive cor-
error.
relationwithNASPArankintheScrabblegroup[r(10)¼.67,
210 cortex 75 (2016) 204e219
1.6.3. Resting-StateSeed/BehaviorPLS (McIntoshetal.,1996).Thiswasaccomplishedusingsampling
Seed/behaviorPLSexaminesgroup-andtask-dependentcor- without replacement to reassign the order of conditions for
relationsbetweenaseedROI,abehaviormeasureandtherest eachsubject.PLSwasrecalculatedforeachsample,andthe
ofthebrain.Forthecurrentpaper,weusedourrestingstate numberoftimesthepermutedsingularvaluesexceededthe
datainthisanalysisbecausewewereinterested,particularly, observed singular values was calculated. Exact probabilities
in whether Scrabble-specific network alterations could be arepresentedforallLVs.
identifiedevenwhenparticipantswerenotactivelyengaged The standard error estimates of the voxel weights/sa-
in a language task. Therefore, our two-group/seed/behavior liencesfromthebootstraptests(i.e.,bootstrapratios)areused
PLSs identified LVs that captured group dependent changes toassessthereliabilityofthenonzerovoxelsaliencesinsig-
in cortical regions that were functionally connected with a nificant LVs. Bootstrap tests were generated using sampling
seedvoxelduringresting-state,andalsowerelinkedtobetter with replacement, keeping the assignment of experimental
anagramming skill (i.e., brain-seed-behavior correlations). conditionsfixedforallsubjects.PLSwasrecalculatedforeach
Resting-State Seed/Behavior PLS wascarried outon a corre- bootstrap test. A salience whose value depends greatly on
lation matrix, comprised of the covariance between our whichsubjectsareinthesampleislessprecisethanonethat
behaviormeasure,voxelsignalinourseedregionandvoxel remains stable regardless of the sample chosen (Sampson,
signalintherestofthebrainacrossparticipantsineachgroup. Streissguth,Barr,&Bookstein,1989).Nocorrectionsformul-
LVs showed similarities or differences between groups and tiplecomparisonsarenecessarybecausethevoxelsaliences
experimentalconditionsinbehavior-brain-seedcorrelations. are calculated in a single mathematical step on the whole
brain. The bootstrap ratio is proportional to a z-score, but
1.6.4. Statisticalassessment shouldbeinterpretedasaconfidenceinterval.Forthecurrent
StatisticalassessmentforPLSisdoneusingpermutationtests paper,wedesignatedathresholdof2.8correspondingroughly
fortheLVsandbootstrapestimationofstandarderrorsforthe toa99.5%confidenceinterval,orapvaluelessthan.005.We
voxel saliences. The permutation test assesses whether the useddifferentbootstrapthresholdstocapturevisuallyallthe
effect represented in a given LV, captured by the singular stable voxel clusters, but keep these clusters small enough
value,issufficientlystrongtobedifferentfromrandomnoise thattheyareeasytodifferentiate.Ourminimumclustersize
Fig.2eBrainimagesandbrainscoresbargraphforLV2fromthetwo-group,nonrotatedtask-PLSanalysis.Onthebrain
imagesweillustrateregionswithmaximaldifferentiationbetweencontrolandScrabblegroupsforbothwordandnonword
trials.Thebrainisdisplayedin3-planeviewaccordingtoneurologicalconvention(L¼L).Yellowregionsrepresent
increasedactivityforthecontrolgroup,andblueregionsrepresentincreasedactivityfortheScrabbleexpertgroup.The
brainscoresbargraphcapturesthemeanbrainscoreforeachconditionineachgroup.Theerrorbarsindicatethe95%
confidenceintervalsderivedfrombootstrapestimation.
cortex 75 (2016) 204e219 211
was10 voxels.We localized gyrallocationsand Brodmann's Table4eLocalmaximaforthetwo-group,nonrotatedtask
areas by reference to Talairach and Tournoux (1988) after PLSLV2,groupmaineffect.
transforming MNI coordinates to Talairach space with the
Region BA x y z BSR
Nonlinear Yale MNI to Talairach Conversion Algorithm
(Lacadie, Fulbright, Rajeevan, Constable, & Papademetris, LeftLateralizedPositiveSaliences
2008)andassociatedonlineJava-basedapplet. LeftMiddleFrontalGyrus 10 (cid:1)39 48 (cid:1)6 4.18
LeftMiddleFrontalGyrus 9 (cid:1)48 27 36 3.77
LeftMiddleFrontalGyrus 8 (cid:1)24 30 36 3.68
LeftAmygdala (cid:1)30 (cid:1)3 (cid:1)24 4.06
2. Results
LeftMiddleTemporalGyrus 39 (cid:1)48 (cid:1)66 18 4.20
LeftParahippocampalGyrus 30 (cid:1)24 (cid:1)39 (cid:1)6 4.20
2.1. Behavioralresults LeftPrecuneus 7 (cid:1)6 (cid:1)48 42 3.69
RightLateralizedPositiveSaliences
BehavioralanalyseswereperformedoncorrectLDTtrialsfor RightMiddleTemporalGyrus 21 63 (cid:1)9 (cid:1)21 5.23
whichreactiontimesfellwithin±2.5SDsofeachparticipant's RightHippocampalGyrus 35 24 (cid:1)15 (cid:1)18 4.26
LeftLateralizedNegativeSaliences
mean,whichexcluded3.96%ofalltrials.Anyitemwithless
LeftSuperiorOrbitalGyrus 25 (cid:1)15 21 (cid:1)18 (cid:1)4.70
than 70% accuracy (for either Scrabble expert or control LeftSupplementaryMotorArea 6 (cid:1)9 15 51 (cid:1)5.59
groups) was also excluded from analysis (n ¼ 12). Given the LeftParacentralLobule 4 (cid:1)6 (cid:1)30 78 (cid:1)4.88
low number of response errors (2% of all trials), error data LeftPrecentralGyrus 6 (cid:1)57 3 24 (cid:1)4.58
werenotanalyzedfurther. LeftPostcentralGyrus 2 (cid:1)63 (cid:1)21 39 (cid:1)4.67
MeanLDTreactiontimeswereenteredintoa2(expertise: LeftCaudateNucleus (cid:1)6 6 3 (cid:1)4.35
Scrabble experts vs. controls) (cid:3) 2 (lexicality: word vs. LeftInsula (cid:1)36 9 12 (cid:1)4.42
LeftSuperiorTemporalGyrus 22 (cid:1)60 (cid:1)18 0 (cid:1)5.01
nonword)mixedmodelANOVA.Weobservedamaineffectof LeftParahippocampalGyrus 30 (cid:1)39 (cid:1)6 18 (cid:1)3.73
lexicality [F(1,22) ¼ 26.99, p < .001, ƞ2 ¼ .55], with faster re- LeftSuperiorParietalLobule 7 (cid:1)27 (cid:1)63 54 (cid:1)5.05
sponses to words than to nonwords [M ¼ 975.72 msec, LeftFusiformGyrus 37 (cid:1)36 (cid:1)45 (cid:1)21 (cid:1)5.32
SD¼57.43andM¼1333.57msec,SD¼63.48respectively].We LeftLingualGyrus 19 (cid:1)30 (cid:1)69 (cid:1)9 (cid:1)4.77
alsoobservedasignificanteffectofexpertise[F(1,22)¼5.18, LeftMiddleOccipitalGyrus 18 (cid:1)30 (cid:1)93 3 (cid:1)5.13
p<.05,ƞ2¼.19],asScrabbleexpertsweresignificantlyfaster RightLateralizedNegativeSaliences
than controls [M ¼ 1041.25 msec, SD ¼ 70.39 and RightSuperiorFrontalGyrus 6 9 21 69 (cid:1)4.48
RightSupplementaryMotorArea 6 6 0 54 (cid:1)3.90
M ¼ 1268.04 msec, SD ¼ 70.39 respectively]. There was no RightInferiorFrontalGyrus 45 57 18 15 (cid:1)3.75
significantinteraction(F<1). RightInferiorTemporalGyrus 37 45 (cid:1)60 (cid:1)12 (cid:1)4.04
RightInferiorTemporalGyrus 20 45 (cid:1)9 (cid:1)36 (cid:1)3.91
2.2. Two-groupnonrotatedtaskPLSresults RightSuperiorParietalLobule 7 15 (cid:1)57 66 (cid:1)4.28
RightInferiorParietalLobule 40 45 (cid:1)33 48 (cid:1)4.68
RightFusiformGyrus 37 33 (cid:1)57 (cid:1)18 (cid:1)4.88
Ourtwo-group,nonrotatedtaskPLS,performedonLDTdata,
RightFusiformGyrus 19 33 (cid:1)57 (cid:1)15 (cid:1)5.01
identifiedsignificantmaineffectsoflexicality(p¼.002)and RightSuperiorOccipitalGyrus 19 21 (cid:1)75 39 (cid:1)4.84
group (p ¼ .014), but no significant lexicalityby group inter- RightMiddleOccipitalGyrus 18 33 (cid:1)84 6 (cid:1)5.85
action. The first LV (lexicality main effect; p ¼ .002; Fig. 1; RightCuneus 17 12 (cid:1)99 (cid:1)3 (cid:1)3.84
representativeareasarelistednextandforacompletelistof Note: BA¼Brodmann's area. Regions indicate the gyral locations
local maxima for regions of activation, see Table 3) showed
and BA of the cluster peak. Gyral locations and BA were then
word/nonword activity differences common to both groups. determinedbyreferencetoTalairachandTournoux(1988).Only
Dominant positive saliences (related to increased activity voxelsinsupratentorialregionsarereported.x,y,andzindicate
duringwordtrialsforbothgroups)includedbilateralsuperior voxelcoordinatesinMNIspace.BSR¼bootstrapratio,andrepre-
frontalgyrus(BA8and10),bilateralanteriorcingulate(BA32), sentseachvoxel'sPLSparameterestimatedividedbyitsstandard
error.
rightsupramarginalgyrus(BA40),bilateralmiddletemporal
gyrus (BA 21), and bilateral lingual gyrus (BA 18). Dominant
negative saliences (related to increased activity during
nonword trials for both groups) included bilateral inferior duringwordandnonwordtrialsforScrabbleexperts)included
frontalgyrus(BA47,45,and44),bilateralmiddlefrontalgyrus right inferior frontal gyrus (BA 45), right inferior temporal
(BA46),bilateralmedialfrontalgyrus(BA8),bilateralinferior gyrus(BA20),rightinferiorparietallobe(BA40),bilateralsu-
temporalgyrus(BA37),bilateralsuperiorparietallobe(BA7), periorparietallobe(BA7),leftinsula,bilateralfusiformgyrus
bilateralsupplementarymotorarea(BA6),andrightfusiform (BA19and37),andbilateralmiddleoccipitalgyrus(BA18).
gyrus(BA37). Additionally,ourtwo-group,nonrotatedtaskPLSallowed
The second LV (group main effect; p ¼ .014; Fig. 2; for a ustoidentifyaregionofinterest(ROI;i.e.,seedvoxel)froma
complete list of local maxima for regions of activation, see canonical language regiondthe LIFGdthat was commonly
Table4)showedcontrol-Scrabbledifferencesthatwerecom- activatedforbothgroups.WechosethisROIfromLIFGvoxels
monacrosswordandnonwordtrials.Dominantpositivesa- identifiedinthemaineffect oflexicality(LV1),as activation
liences (related to increased activity during word and identifiedinthisLVwascommontobothgroups.Accordingto
nonwordtrialsforcontrols)includedleftmiddlefrontalgyrus ourPLSanalysis,theLIFGingeneral(andthisROI)wasmore
(BA 8, 9 and 10), and right middle temporal gyrus (BA 21). activeduring nonworddecisions. This findingwas expected
Dominant negative saliences (related to increased activity becauseLIFGactivationtendstoincreasewithlexicaldecision
212 cortex 75 (2016) 204e219
Fig.3eAandB:BrainimagesandcorrelationbargraphforLV1fromthetwo-group,anagrammingscore,behavior-PLS
analysis.Onthebrainimagesweillustratebrain-behaviorcorrelationsforwordandnonwordtrials.Thebrainisdisplayed
in3-planeviewaccordingtoneurologicalconvention(L¼L).Inboth3Aand3B,regionshighlightedinyellowindicatea
positivecorrelationbetweenhigheranagrammingscoresandincreasedactivationduringwordandnonworddecisionsin
controls,andduringnonworddecisionsinScrabbleexperts.Regionshighlightedinblueindicateapositivecorrelation
betweenhigheranagrammingscoresandincreasedactivationspecificallyduringworddecisionsinScrabbleexperts.The
correlationbargraphin3Acapturesthetask-dependentcorrelationsbetweenourbehaviormeasure(anagrammingscores)
andtheregionsidentifiedinthebrainimages.Theerrorbarsshowthe95%confidenceintervalderivedfrombootstrap
estimation.
cortex 75 (2016) 204e219 213
difficulty (Edwards, Pexman, Goodyear, & Chambers, 2005), Finally,SPMidentifiedonesignificantcluster inthe right
andnonworddecisionsaretypicallymoredifficultthanword inferiorparietallobe(BA40)forthelexicalitybygroupinter-
decisions.ThemostreliableLIFGvoxel(i.e.,thevoxelwiththe action.Giventhattherewasonlyoneclusterassociatedwith
highest bootstrap ratio) was located in Brodmann's area 45 theinteraction,itisnotremarkablethatthisdifferencewas
(MNIcoordinates(cid:1)4536(cid:1)3).Weusedthisseedco-ordinatein non-significantwhentestedoverthewholebraininPLS.
our resting-state behavior/seed PLS to examine if Scrabble-
specific network alterations could be identified even when
2.4. Two-groupbehaviorPLSresults
participantswerenotactivelyengagedinalanguagetask.
Weperformedatwo-groupbehaviorPLSonLDTdatatoassess
whether there were group-dependent differences in the
2.3. Univariate(SPM)resultsforcomparisontothe
cortical regions that are related to offline variability in
nonrotatedtaskPLSresults
anagramming scores (i.e., brain-behavior correlations). We
identifiedasignificantLV(p¼.004;Fig.3AandB;foracom-
Although univariate (SPM) and multivariate (PLS) analyses
plete list of local maxima, see Table 5). Dominant positive
highlight different aspects of neuroimaging data (i.e., inde-
pendentactivityinsingleregionsversusdistributedpatterns),
thePLSandSPMresultsinthepresentstudyaresimilar,with Table5eLocalmaximaforthetwo-group,anagramming
the primary difference being fewer activations with smaller score,behaviorPLS.
spatialextentidentifiedinSPM.Therearemanydifferences
Region BA X Y Z BSR
betweenthecalculationsinvolvedinSPMandPLSanalyses,
thus one would expect to find some variation in results. LeftLateralizedPositiveSaliences
Indeed, different outcomes have been identified in the neu- LeftMiddleFrontalGyrus 9 (cid:1)39 36 30 5.824
LeftInferiorFrontalGyrus 45 (cid:1)42 24 9 5.4265
roimagingliteratureeveninthecontextofmuchmoresimilar
LeftPrecentralGyrus 6 (cid:1)60 0 6 10.6509
calculations [e.g., differences in motion correction results LeftInsula (cid:1)30 21 6 5.3049
whencarriedoutwithdifferentsoftwaretools,includingAFNI LeftRolandicOperculum 43 (cid:1)48 (cid:1)15 15 5.7617
and SPM (Oakes et al., 2005; Morgan, Dawant, Li, & Pickens, LeftSuperiorTemporalGyrus 42 (cid:1)45 (cid:1)30 21 5.7396
2007); differences in automatic intracranial volume estima- LeftAmygdala (cid:1)27 0 (cid:1)12 7.1074
tion when carried out with different software tools, again LeftHippocampus (cid:1)18 (cid:1)15 (cid:1)18 7.1885
LeftInferiorParietalLobule 40 (cid:1)39 (cid:1)48 48 5.7684
includingAFNIandSPM(Sargolzaeietal.,2014)].Foranevent-
LeftPosteriorCingulateGyrus 31 (cid:1)12 (cid:1)60 9 5.3784
related design such as ours, we expect PLS to identifymore
LeftPrecuneus 7 (cid:1)12 (cid:1)63 66 5.8634
regionsthanSPMbecauseitmakesnoassumptionsaboutthe LeftFusiformGyrus 19 (cid:1)27 (cid:1)60 (cid:1)15 8.6615
shape of the hemodynamic response functions (HRFs), and LeftSuperiorOccipitalGyrus 19 (cid:1)33 (cid:1)69 36 5.8481
corrections for multiple comparisons are not necessary LeftCuneus 17 (cid:1)12 (cid:1)84 3 7.1159
because reliability of voxel signal change is calculated in a LeftLingualGyrus 18 (cid:1)12 (cid:1)48 0 6.6741
singlemathematicalsteponthewholebrain(McIntosh,Chau, LeftLingualGyrus 17 (cid:1)15 (cid:1)87 (cid:1)9 9.3587
&Protzner,2004). RightLateralizedPositiveSaliences
RightInferiorFrontalGyrus 45 54 27 18 6.722
FortheSPManalyses,statisticalimageswerethresholded
RightPrecentralGyrus 6 57 (cid:1)6 36 9.6961
atp¼.005withaclustersizeofatleast10contiguousvoxels RightPostcentralGyrus 2 48 (cid:1)15 21 5.7951
(thesethresholdsalsowereusedforourPLSanalyses).Based RightPutamen 30 9 6 5.7969
on the assumption that a true signal will stimulate signal RightPosteriorCingulateGyrus 31 6 (cid:1)60 3 5.1472
changesoveragroupofcontiguousvoxels,theresultingcor- RightPosteriorCingulateGyrus 23 12 (cid:1)51 3 8.1524
rected p value is .0001 for the SPM analyses (Forman et al., RightFusiformGyrus 19 21 (cid:1)48 (cid:1)15 5.3346
RightLingualGyrus 18 15 (cid:1)81 (cid:1)12 7.9378
1995).
RightCuneus 17 9 (cid:1)75 9 5.9334
Forthemaineffectoflexicality,representativeregionsthat
RightInferiorFrontalGyrus 45 54 27 18 6.722
were more active for word trials included right superior LeftLateralizedNegativeSaliences
frontalgyrus(BA8),andrightmiddletemporalgyrus(BA21). LeftMedialFrontalGyrus 11 (cid:1)6 45 (cid:1)15 (cid:1)4.2992
Representative regions that were more active for nonword LeftMedialFrontalGyrus 10 (cid:1)9 45 (cid:1)12 (cid:1)4.1748
trials included bilateral middle frontal gyrus (BA 46), left LeftAnteriorCingulateGyrus 32 (cid:1)3 39 (cid:1)12 (cid:1)4.9178
LeftAnteriorCingulateGyrus 25 (cid:1)9 9 (cid:1)18 (cid:1)4.4157
medialfrontalgyrus(BA8),andleftinferiorparietallobe(BA
LeftSuperiorOccipitalGyrus 19 (cid:1)27 (cid:1)90 30 (cid:1)4.7118
40).
LeftCuneus 18 (cid:1)9 (cid:1)102 9 (cid:1)5.6895
For the group main effect, no regions were significantly
RightLateralizedNegativeSaliences
moreactiveforcontrolsascomparedtoScrabbleexperts.An RightMedialFrontalGyrus 11 12 48 (cid:1)21 (cid:1)5.3252
examinationofthePLSresultssuggeststhatincreasedactivity RightMiddleOccipitalGyrus 19 27 (cid:1)87 21 (cid:1)4.1327
for controls happens relatively late after trial onset (e.g., Note: BA¼Brodmann's area. Regions indicate the gyral locations
8e12sec),thusitisnotsurprisingthatananalysistechnique and BA of the cluster peak. Gyral locations and BA were then
that relies on the canonical HRF would not identify these determinedbyreferencetoTalairachandTournoux(1988).Only
activationdifferences.Representativeregionsthatweremore voxelsinsupratentorialregionsarereported.x,y,andzindicate
activeforScrabbleexpertsincludedLIFG(BA44),rightinferior voxelcoordinatesinMNIspace.BSR¼bootstrapratioandrepre-
sentseachvoxel'sPLSparameterestimatedividedbyitsstandard
temporal gyrus (BA 20), left insula, right fusiform gyrus (BA
error.
37),andbilateralmiddleoccipitalgyrus(BA18).