Neural Systems for Reading Aloud: A Multiparametric Approach

17 Pages·2016·1.07 MB·English

CerebralCortexAugust2010;20:1799--1815
doi:10.1093/cercor/bhp245
AdvanceAccesspublicationNovember17,2009
Neural Systems for Reading Aloud: A William W.Graves1, Rutvik Desai1,Colin Humphries1,
MarkS. Seidenberg2and JeffreyR. Binder1
Multiparametric Approach
1Department ofNeurology, MedicalCollege of Wisconsin,
Milwaukee, WI53226, USAand 2Department of Psychology,
University of Wisconsin, Madison,WI 53706, USA
Reading aloud involves computing the sound of a word from its readingsystem.Theregressionapproach,incontrast,allowsfor
visual form. This may be accomplished 1) by direct associations thesimultaneousinvestigationofmanyvariablesofinterest,but
between spellings and phonology and 2) by computation from inpractice,thesevariablesareoftencorrelatedwitheachother
orthographytomeaningtophonology.Thesecomponentshavebeen (e.g., word frequency and length tend to be negatively
studied in behavioral experiments examining lexical properties correlated), making it difficult to attribute a unique role to
such as word frequency; length in letters or phonemes; spelling-- anysinglevariable.Theapproachusedherewastoinvestigate
sound consistency; semantic factors such as imageability, the simultaneous influence of multiple reading-related varia-
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measuresoforthographic, or phonological complexity; and others. bles, with the critical difference that the factors were o
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Effects of these lexical properties on specific neural systems, decorrelated from each other by careful stimulus selection. nlo
however, are poorly understood, partially because high intercorre- Thisapproach was used toinvestigate the neural systems that ad
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decorrelating several important lexical properties through careful resonanceimaging (fMRI) data. h
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stimulus selection. Functional magnetic resonance imaging data A major advantage of ensuring that the lexical factors of ://c
revealed distributed neural systems for mapping orthography interest are uncorrelated is that any spatial overlap of brain e
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directlytophonology,involvingleftsupramarginal,posteriormiddle activation across factors is attributable to a shared neural or.o
temporal, and fusiform gyri. Distinct from these were areas substrate, rather than a statistical correlation between factors. x
fo
reflecting semantic processing, including left middle temporal Sixfactorsofparticularrelevancetoorthographic,phonological, rd
gyrus/inferior-temporal sulcus, bilateral angular gyrus, and precu- and semantic processes were decorrelated in this stimulus set: jou
neus/posterior cingulate. Left inferior frontal regions generally word frequency, spelling--sound consistency, imageability, rna
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showed increased activation with greater task load, suggesting bigram frequency, biphone frequency, and length in letters. .o
a more general role in attention, working memory, and executive Below,wedescribeeachfactor,itspossiblerelevancetoreading brg/
processes. These data offer the first clear evidence, in a single aloud, and relevant behavioral and functional neuroimaging y g
study,fortheseparateneuralcorrelatesoforthography--phonology evidence. ue
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mappingand semantic access during readingaloud. t o
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Keywords:language, orthography, phonology, reading, semantics WordFrequency ug
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Reading aloud is strongly influenced by the frequency with st 1
whichwordsareencounteredinthelanguage.Low-frequency 0
, 2
wordselicitlongerprocessingtimesandhighererrorratesthan 0
1
Introduction high-frequencywords.Thispatternobtainsnotonlyforreading 6
Reading single words aloud is usually construed as involving aloud (Monsell 1991) but with an even greater effect size for
the computation of a target phonological code from ortho- lexical decision (Forster and Chambers 1973; Schilling et al.
graphic(visual)input.Thephonologicalcodeistranslatedinto 1998;Balotaetal.2004)andpicturenaming(Huttenlocherand
the sequence of articulatory gestures that underlie overt Kubicek 1983; Hennessey and Kirsner 1999). The generaliza-
pronunciation. Semantic (meaning) information may also tion of this effect across tasks is relevant because lexical
contribute to this computation to some degree, particularly decision does not require a speech response, and picture
in cases where spelling--sound correspondences are unusual naming involves nonverbal input. Thus, although frequency
(e.g., ‘‘yacht’’; Strain et al. 1995; Plaut et al. 1996). Numerous effectsmayalsobepresentatthelevelofovertarticulationor
behavioralstudiesandafewfunctionalneuroimagingstudiesof visual encoding of letters, neither is necessary to elicit these
reading aloud have used factors such as word frequency, effects. The longer response latencies elicited by reading low-
spelling--sound consistency, and imageability to investigate frequencywordsmayarisefrommultiplesources,oneofwhich
components of the reading process. In general, 2 main is the relative difficulty of mapping from orthography to
approaches have been used: 1) a factorial approach in which phonology (fora reviewseeMonsell1991).
1 or 2 of these factors are manipulated while holding a few Several functional neuroimaging studies of single-word
otherrelevantfactorsconstantand2)acorrelationalapproach reading have reported increased activation for low- compared
(e.g., multiple linear regression) in which the influence of with high-frequency words in the inferior frontal gyrus (IFG)
severalvariablesisinvestigatedatonce.Thefactorialapproach andanteriorinsulabilaterally(moreconsistentlyontheleft),in
suffers from the limitation that investigation of only 1 or 2 the supplementary motor area (SMA), and in various left
variables at a time can at best yield a partial picture of the temporal regions (Fiez et al. 1999; Joubert et al. 2004;
(cid:1)TheAuthors2009.PublishedbyOxfordUniversityPress.
ThisisanOpenAccessarticledistributedunderthetermsoftheCreativeCommonsAttributionNon-CommercialLicense(http://creativecommons.org/licenses/by-nc/2.5),whichpermits
unrestrictednon-commercialuse,distribution,andreproductioninanymedium,providedtheoriginalworkisproperlycited.
Kronbichler et al. 2004; Hauk, Davis, and Pulvermu¨ller 2008). itates performance on semantic decision tasks (e.g., deciding if
Someofthelefttemporallobefocihavebeeninorneartheso- a word denotes an object belonging to a particular conceptual
calledvisualword-formarea(VWFA;Cohenetal.2000).Word- category), suggesting that semantic information is more easily
frequencyeffectsintheVWFAhavebeentakenasevidencefor available for high-frequency words (Monsell et al. 1989; Chee
whole-word orthographic processing (i.e., activation of an et al. 2002). In word-association tasks, higher-frequency words
orthographic lexicon) in this region (Joubert et al. 2004; are more likely to be produced as associates, suggesting that
Kronbichler et al. 2004; Hauk, Davis, and Pulvermu¨ller 2008), they have stronger associative connections with other words
whereas frequency effects in the IFG have generally been (NelsonandMcEvoy2000).Althoughsuchstudiesmightleadto
interpreted as evidence of phonological processing in this the expectation of greater activation in semantic processing
region(Bookheimer 2002). areas for high-frequency words, only 2 prior imaging studies
It is important to note, however, that caution is required havereportedsuchapattern(Prabhakaranetal.2006;Carreiras
when interpreting brain activations that are accompanied by et al. 2009). In general, reading studies that directly compared
increases in task difficulty. Functional neuroimaging measure- high- and low-frequency words showed no relative activation
ments are very sensitive to differences in response time (RT), for the high-frequency condition (Fiez et al. 1999; Chee et al.
accuracy, attention, working memory load, and level of effort 2002;Fiebachetal.2002;Joubertetal.2004;Kronbichleretal.
between tasks (see, e.g., Honey et al. 2000; Adler et al. 2001; 2004;Carreirasetal.2006;Hauk,Davis,andPulvermu¨ller2008).
Braveretal.2001;UllspergerandYvesvonCramon2001;Gould Thus, although it may be reasonable to expect activation for
et al. 2003; Binder et al. 2004; Binder, Medler, et al. 2005; high-frequency words in brain areas that support semantic
Mitchell 2005; Desai etal. 2006; Lehmann etal. 2006; Tregallas processing, support for this from functional neuroimaging is
D
et al. 2006). These differences in task difficulty are thought to scarce. o
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exert effects on brain activity by modulating domain-general n
lo
cognitive processes necessary for completing any task. Likely a
Spelling--SoundConsistency de
examples of such domain-general systems include a sustained d
attention network for maintaining arousal, a selective attention Spelling--sound consistency is another factor that affects the fro
orthography--phonology computation. ‘‘Friends’’ of a word m
systemforfocusingneuralresourcesonaparticularmodalityor h
saenwsoorrkyinogbjmecetmoinrytshyesteemnvifroornmkeeenptin(ge.tga.,skainvsitsruuacltiodnissplaany)d, sahwaroerdthheavesaamreimreimtheatpirsosnpuenllceidattiohne,sawmheerbeuatsis‘‘epnroemnoieusn’’ceodf ttp://ce
task-relevant sensory representations accessible, a response- differently. Ingeneral, words withinconsistent spelling--sound rco
smeelemctoiroyn tmoecahanreissmponfoser, maaprpeisnpgontshee-inchoinbtiteinotns osyfstwemorkifnogr mLwIiaNtphTp,cibnougntssni(soete.gfnr.,itePsnIpdNesTl)lienhlgaic-s-istmoluoannndygemernanepampmiineinsggs(luBactaehrnoacnsieaMsntdIhNaSTnt,rawHwoINsrodTns, r.oxford
preventingprematureorprepotentresponsesfrombeingmade jo
inerror,andanerror-monitoringsystem for adjustingresponse 1976; Glushko 1979; Andrews 1982; Taraban and McClelland urn
ccraistee,riaandanidftRhTedleevaedllionfesacttoivmatiionnimiinzethseuscehseyrsrteomrs.sIdfetpheisnidsstohne 1fr9e8q7u;eJnacryedw1o9r9d7s, 2c0o0m2p)a.rTehdesweitehffehcitgshaerre(gSreeidateenrbfeorrgloewtearl-. als.org
1984). Computational models of reading and associated b/
general task demands, then it follows that activation can never y
behavioralevidencesuggestthatwhenawordisusedrelatively g
beattributedwithcertaintytospecificlinguisticprocesseswhen u
infrequently and the mapping between spelling and sound is es
thisactivationhasresultedfromacontrastinwhichgeneraltask highly atypical, semantic information is used to help achieve t on
demands differ. Specifically, brain areas whose task-related the correct phonological representation (Strain et al. 1995; A
activation is thought to reflect attention and working-memory ug
Plaut et al. 1996; Strain and Herdman 1999; Harm and u
demands (e.g., SMA, anterior cingulate, IFG, anterior insula, Seidenberg 2004; Woollams 2005). Hence, brain activation st 1
precentralsulcus, and dorsal parietallobe;Corbetta etal. 1998; 0
elicited by reading low-frequency, low-consistency words , 2
Carter et al. 1999; LaBar et al. 1999; Duncan and Owen 2000; 0
Derrfuss et al. 2005; Grosbras et al. 2005; Owen et al. 2005) might be interpreted in 2 ways. It may reflect increased use 16
of neural resources for orthography--phonology mapping for
largely overlap those whose activation increases for low-
low-frequency, low-consistency words, or, alternatively, re-
compared with high-frequency words (Fiez et al. 1999; Hauk,
cruitment of the semantic system. Several studies have
Davis,andPulvermu¨ller2008).Moreover,thesesameareasshow
reported activation in language-related prefrontal cortical
activation correlatedwith increases inRTduringreading aloud
regions such as IFG for reading inconsistent compared with
(Binder, Medler, et al. 2005). Hence, neural effects of, for
consistentwords(Herbsteretal.1997;Fiezetal.1999;Binder,
example, decreasing word frequency may be indistinguishable
Medler, et al. 2005; Mechelli et al. 2005), and such results are
fromattentionorworking-memoryprocessestotheextentthat
typically interpreted as reflecting neural systems for orthogra-
theyspatiallyoverlapwitheffectsofRT.
phy--phonology mapping. However, because low-frequency,
Althoughthefocusinneuroimagingstudieshasbeenonthe
low-consistencywordsalsoelicitlongernaminglatencies,such
greater activation associated with decreasing word frequency,
activations may be confounded with attention and executive
increasing word frequency may also be expected to have
processes, as described above (Binder, Medler, et al. 2005).
positive effects on activation, particularly in lexical--semantic
Functional imaging evidence for recruitment of semantic
systems. Word frequency is correlated with the extent of
processing areas in reading low-frequency, low-consistency
repeated exposure to a lexical concept; thus, access to word
words, onthe otherhand,is scarce.
meaning is likely to be more extensive and more automatic in
the case of high-frequency words. Higher-frequency words
appearinmorecontexts(Adelmanetal.2006)andarejudgedto Imageability
be more familiar (Toglia and Battig 1978; Baayen et al. 2006) Imageability,whichreferstotheeasewithwhichawordevokes
compared with lower-frequency words. Word frequency facil- a mental image, is a semantic factor that facilitates word
1800 NeuralSystemsforReadingAloud d Gravesetal.
recognition in the lexical decision task (James 1975; Kroll and Monselletal.1989;Strainetal.1995;Jared1997;Weekes1997;
Merves 1986; Kounios and Holcomb 1994; Binder, Westbury, HinoandLupker2000;Jared2002;O’MalleyandBesner2008).
etal.2005).Highlyimageablewordsarethoughttohavearicher The study of bigram effects in the functional neuroimaging
ormoreeasilyaccessedsemanticrepresentation(Shallice1988; literaturehasbeenmotivatedbythetheorythatfamiliarletter
Paivio1991;Schwanenflugel1991).Althoughsemanticprocess- combinations (e.g., bigrams and trigrams) are represented in
ingisusuallyconsideredtohaveaminimalroleinreadingaloud, the brain, particularly in VWFA, with more frequently
thereisevidencethatitplaysarole,particularlyforlessfamiliar, encountered combinations having stronger representations
more difficult words (Patterson et al. 1985; Patterson and (Dehaene et al. 2005; Binder et al. 2006; Vinckier et al. 2007).
Hodges 1992; Strain et al. 1995; Strain and Herdman 1999; Activationofthesesublexicalorthographiccodesspeedsletter
Woollams 2005). According to connectionist models of word recognition, perhaps through an interactive activation mech-
reading,ifbothwordfrequencyandspelling--soundconsistency anism (McClelland and Rumelhart 1981), and damage to their
are low, the orthography--phonology computation is both less neural representations results in letter-by-letter reading
accurateandlessefficient.Computingthecorrectphonological (Binder and Mohr 1992; Leff et al. 2001; Cohen, Henry, et al.
code requires additional input via the orthography--semantics-- 2004). Relevant functional brain-imaging data for bigram
phonology pathway in such models (Plaut et al. 1996). Input frequencyeffectscomesfrom2recentstudiesusingnonwords,
along this semantically mediated pathway is greater for words bothofwhichfoundincreasedactivitywithincreasingbigram
that are highly imageable. This theory predicts faster latencies frequency in left mid-fusiform gyrus (Binder et al. 2006;
for low-frequency, low-consistency words that are highly Vinckieret al. 2007).
imageable compared with those that are less imageable. This
D
pattern has been observed in multiple studies of reading aloud BiphoneFrequency andLetter Length ow
(Strain et al. 1995; Strain and Herdman 1999; Shibahara et al. n
Biphonefrequencyandletterlengthwereincludedprimarilyto lo
2003;Woollams2005). a
ensure that effects of the other variables could not be de
Severalfunctionalneuroimagingstudiesofimageabilityhave d
also been performed. In a single-word reading aloud study attributed to correlations with these factors. Biphone fre- fro
quencyisameasureofphonotacticcomplexityshowntoaffect m
similartotheoneperformedhere,Binder,Medler,etal.(2005) h
faonudndprienccurenaesuesd/paocstitveartioiornciinngbuillaatteeraglyarnigauslawr,osrudpeirmioargefraobniltiatyl, s(pMeaejecrhuspertodaul.c2ti0o0n2;tGasoklsdriscukchandasLanrosonnwo2r0d08p; rGornauvnesciaettioanl. ttp://ce
increased.Activationsforlower-imageabilitywordswerefound 2008) and picture naming (Vitevitch et al. 2004), with low- rco
ilenftbiIlFaGte/raanltaenrtioerrioinrscuilnag,usilmatielacrotrotetxh,eleafcttpivraetcioennstrarelpgoyrrutesd,afnodr bcleoinpmghtpohanre(e-ndfruewmqibutheernhciogyfhw-lbeoitprtedhrsosn)sehc-oforweuiqlndugeinnacpyprrwoincocerisdpssli.enEgfafldesciostasrdeovlfaanlteettatgetoer r.oxford
lower-frequency words in the studies mentioned previously. jo
Similar inferior frontal activations for low- relative to high- phonotactic processing in that longer words may be more urn
ilemxaigcealabialnitdywsoemrdasnhtiacvedbeeceinsiorenpotratsekdsin(Pseervaenrialesttudaile.s1u9si9n9g; dexifpfiecruilmtetontparroenoalulnmceo.nGosiyvlelanbitch,athothweevsetirm, iutliisinretahseonparbelesentot als.org
expect letter-length effects to arise primarily at the level of b/
Friederici et al. 2000; Fiebach and Friederici 2003; Noppeney y
visual encoding, as suggested by functional neuroimaging g
and Price 2004; Binder, Westbury, et al. 2005; Sabsevitz et al. u
studies showing increased activation in primary visual cortex es
2005). Several reading-related studies also reported activation forlonger words (Mechelli et al. 2000;Wydellet al. 2003). t on
for high-imageability words in precuneus/posterior cingulate A
andangulargyrus(Binder,Westbury,etal.2005;Sabsevitzetal. ug
u
2005; Bedny and Thompson-Schill 2006), although exceptions Aimsofthe Study st 1
to this pattern have also been reported (Pexman et al. 2007; Theprincipalaimofthepresentstudywastoexamineinmore 0
, 2
Hauk,Davis,Kherif,andPulvermu¨ller2008).Onbalance,these detail the neural systems supporting reading aloud. One 0
1
findings suggest that precuneus/posterior cingulate and unresolved issue is whether there are regions in the IFG that 6
angular gyrus play a prominent role in processing word are specifically modulated by word frequency, spelling--sound
meaning, a notion further supported by a recent large-scale consistency, or imageability. IFG activation has been reported
meta-analysis of functional neuroimaging studies of word- for low values of all of these variables (i.e., more difficult
relatedsemantics (Binder etal. 2009). conditions), although nostudies have examined all 3 variables
concurrently to assess the degree of overlap of the activated
regions. Similar IFG regions are also modulated by response
BigramFrequency latency, suggesting that at least some of this activation may
A final primary factor of interest, bigram frequency, was represent general executive and attention processes modu-
included as a measure of orthographic familiarity. One of the lated by task difficulty. We predicted that common brain
few behavioral studies to examine the impact of bigram regions would be modulated by task difficulty across all 3
frequency on reading aloud found no effect (Strain and lexicalvariables,aswellasbyRT,andthatthesewouldinclude
Herdman 1999). Bigram frequency has, however, been shown areas previously identified with attention, working memory,
toaffectotherreadingphenomenasuchastachistoscopicword and other general executive processes. In addition, there may
and letter perception (Biederman 1966; Broadbent and be areas of IFG overlap restricted to the word frequency and
Gregory 1968; Rumelhart and Siple 1974; Rice and Robinson consistencyvariables,whichwouldsuggestamorespecificrole
1975; Binder et al. 2006) and lexical decision (Gernsbacher forthese areas inorthography-to-phonology mapping.
1984;WestburyandBuchanan2002),leadingmanyresearchers A second issue concerns activation of the semantic system.
to control for this variable in studies of reading aloud (e.g., Current neuroimaging evidence for engagement of the
Waters and Seidenberg 1985; Taraban and McClelland 1987; semantic system during reading aloud is limited (Binder,
CerebralCortexAugust2010,V20N8 1801
Medler,etal.2005),despitemodelingandbehavioralevidence additional monosyllabic words in the Seidenberg and McClelland
thatsemanticinformationplaysaroleinthistask.Wepredicted (1989)listinordertodecorrelatethesampleintermsofbigramand
2 effects concerning the semantic system. First, increasing biphone frequency. This enlarged the sample to 465 words. Two
correlation matrices are given in Table 2. The upper half presents
values of word frequency and imageability were expected to
correlation valuesamongthe 6variablesofinterestacrossthe1650
produce increasing activation in semantic regions such as the
words in the starting corpus. The lower half presents correlation
angular gyrus, ventral temporal lobe, and precuneus/posterior valuesamongthesamevariablesacrossthefinalsetof465words.A
cingulate, indicating more extensive activation of semantic list of the 465 stimuli and their associated values is given in the
information with increasing concept familiarity and image- supplementalmaterial(TableS1).
ability. Second, we expected increased activation in the
semantic system as spelling--sound consistency decreases.
Participants
Although the predicted effects of frequency and imageability The20participants(13females)wereallhealthy,literateadultswith
could be attributed to incidental processing of semantic normal or corrected-to-normal vision, were right handed on the
information, semantic activation associated with decreasing Edinburgh handedness inventory (Oldfield 1971), and spoke English
consistencywouldbestrongevidenceforadirectcontribution as a first language. Mean age was 23.2 (standard deviation, SD: 3.4),
andmeanyearsofeducationwas16.6(SD:3.1).AverbalIQestimate
fromsemantics inreading aloud.
from the Wechsler Test of Adult Reading (Wechsler 2001) was
availablefor19ofthe20participants,withameanstandardscoreof
Materials and Methods 109.6 (SD: 8.3). Participants provided written informed consent
accordingtolocalInstitutionalReviewBoardprotocolsandwerepaid
anhourlystipend.
StimulusMaterial D
Thestimuliwere465monosyllabicEnglishwords,whichwereselected ow
toensurethatthefollowing6factorswereuncorrelated:letterlength, TaskandImaging nlo
word frequency, spelling--sound consistency, imageability, bigram ThefMRIexperimentusedafastevent-relateddesignwithcontinuous ad
fWreoqrude-fnrceyq,uaenndcybivpahluoensewfreerqeuoebntcayin(esdeefrToamblCeE1LEfoXr(eBxatareyemneeetxaalm.1p9le9s5)). arecpqluaicseitdiown.itOhnaefiaxcahtiotnriacl,roassw. Aorpdprwoxasimdaitseplhayoeridzofnotral1v0i0e0wimngs,atnhgelne ed fro
in terms of occurrences per million and log transformed. Consistency subtendedlessthan7(cid:2).Participantswereinstructedto‘‘readeachword hm
wasdefinedasthenumberoffriendsminusthenumberof‘‘enemies.’’ aloudasquicklyandaccuratelyaspossible.’’Participantsspokeintoan ttp
Comparisons were based on phonetic transcriptions from CELEX that MRI-compatiblemicrophoneplacednearthemouthandsecuredtothe ://c
were transformed, when necessary, into standard American English e
head coil. The fMRI session included 5 runs of single-word reading rc
pstrroaninuendc.iaFtoiornesa.chBi2g-rlaemtterfrceoqmuebnincaietisonwienreawleonrgdt,htheanfdreqpuoesnitcioiensocfoanl-l aloud.Eachrunlasted8minandconsistedof93readingtrials;these or.o
trials were randomly intermixed with 139 baseline (fixation) trials, x
wpoosridtisonofwtehreessuammmeeldenagntdhlcoognttraainnsinfogrmtheed.sAafmteercbaiglcruamlatiningtthhiesvsaamluee r4e.9su,SltDin:g3.i7n2)a.Fvaorllioabwleinignttheristrwiaelrient5errvuanlsroanfgpisnegudfroowmor2dtroea3d4insg(amloeuand:. fordjo
for each bigram in the word, these figures were then summed and The pseudoword data were not included in the current analyses and urn
dividedbythetotalnumberofbigramsinthewordtogiveameanlog- willnotbediscussedfurther. als
tpb(rcieapfrn.hfVsoofriontmeremveifdtercedhqfouaprneondsbcitLiyipuo.hcnCoeaonl2me0bsp0iga4rtr)oae,mdthywiisferilmetdhqeutumehnnoeccdaoynni.ssTmtlorhaogeir-nteersadpanmrsbefediopirchmptorievnodeeceofdpfrueoreqrseiautcieotwninocaanysl HfrreeefMqealruRteheInnccacderyaeti,mareaWwcgeeaeuisrvekweeesahcrceoaq,iual.ciWrqeHuId)iigrehuwdsiiantrhsegsaoaaslnuett3io.8o0n-f-c,T1h3aT4Gn1nE-cweolneEitxgaicgrhriuttaeoeydusshyaaesnxtaeaidatmlosmrlai(icdGceiaoEsl by gue.org/
triamtIimengainsgecaaonbmialiuptdyilietvdoarlfyuroepsmsewu6desrooewuoorrcbdetasrien(pPeedaitviftiriooonmettaaaslk.d1a(9tGa6rb8aav;seeTsooegftliaaiml.aa2ng0de0aB8b)ai.tltitigy (F0u.n9c3t8io3na0l.9s3c8an3s 1w.0e0re0macmq)uiuresidnguasinspgoialedg-rgardaideinetn-et-cehcohoescehqoupelanncaer. st on A
imaging (EPI) sequence with the following parameters: 25-ms time u
1C9o7rt8e;sGeilhanodolyFuangdetLto2g0ie041)9,80th;eBirfidrsetta3l.a2v0a0il1a;bClelartkhraonudghPaitvhioe2M00R4C; ienc-hpola,n2e-svtoixmeeldreimpeetnitsiioonn,s139.02-3mm3.0fimeldm,oafnvdieswli,c6e4t-h3ick6n4e-pssixoefl2m.5atmrimx, gust 1
PsySctihmoulilnugsusisetlieccDtioatnabbaesgea(nWwilistohna1c9o8r8p).us of1650 nonhomographic, wanidtheaac0h.5o-mftmheg5apf.uTnhctiriotyn-atwlrouninstceorlnesaivseteddaoxfia2l4s0licweshowlee-rberaaicnqiumiraegde, 0, 201
monosyllabic words containing 4--6 letters, a subset of the mono- 6
volumes.
syllabic words used by Seidenberg and McClelland (1989). This
corpuswasdividedinto8orthogonalcellsbyfullycrossinghighand
lowlevelsofwordfrequency,consistency,andimageability.Thecell
with the smallestnumberofitems, the low-frequency/inconsistent/ Table2
high-imageability cell, contained 38 words. Next, 38 items were Correlationmatrix(rvalues)forfactorsofinterestacrosstheinitialsetof1650candidatewords
forwhichdataonallfactorswereavailable(upperhalf)andforthe465stimuluswords(lower
selectedatrandomfromtheother7cells,yieldinganucleusof304
half)
words for which frequency, consistency, and imageability were
uncorrelated. Finally, words were selected from a list of 895 Length Frequency Consistency Imageability Bigrams Biphones
Correlationsacrossnearlytheentiresourcecorpus
Length 1
Table1 Frequency (cid:1)0.074 1
Examplewordsfromextremeendsofthedistribution,alongwithoverallrangeandmeanvalues Consistency (cid:1)0.166 (cid:1)0.106 1
foreachstimuluspropertyofinterest Imageability (cid:1)0.019 (cid:1)0.023 0.087 1
Bigrams (cid:1)0.178 0.407 0.031 (cid:1)0.053 1
Property High Low Max Min Mean Biphones 0.156 0.127 0.110 (cid:1)0.024 0.195 1
Correlationsacrossthestimulusset
Length(letters) Straight(8) Fix(3) 8 3 4.42 Length 1
Wordfrequency(log[count/million]) Might(4.12) Wilt(0.00) 4.72 0 2.35 Frequency 0.057 1
Consistency(friends--enemies) Chill(27) Wash((cid:1)20) 29 (cid:1)20 7.35 Consistency (cid:1)0.069 (cid:1)0.088 1
Imageability(ratingon1--7scale) Beach(6.59) Moot(1.40) 6.59 1.4 4.39 Imageability (cid:1)0.032 0.086 0.043 1
Bigramfrequency(log[count/million]) Thing(5.01) Gym(1.85) 5.01 1.84 4.15 Bigrams (cid:1)0.072 0.090 0.078 (cid:1)0.087 1
Biphonefrequency(log[count/million]) Cyst(34.47) Apt(0.95) 34.47 0 9.05 Biphones 0.072 0.037 0.090 (cid:1)0.025 (cid:1)0.003 1
Note:Numbersinparenthesesaftereachexampleitemrepresentthevariablevalueforthatitem. Note:Allnonsignificantcorrelations(P[0.05)areinbold.
1802 NeuralSystemsforReadingAloud d Gravesetal.
DataProcessingandAnalysis were very infrequent (2.6% overall) and not analyzed further.
Image analysis was performed using AFNI (http://afni.nimh.nih.gov/ Using simultaneous multiple linear regression analysis for
afni)(Cox1996).Foreachsubject,thefirst6imagesineachtimeseries which the dependent measure was each subject’s mean-
were discarded prior to regression analysis to avoid initial saturation
centered RT to each word, we examined effects of the 6
effects.Imageswereslicetimingcorrectedandspatiallycoregistered.
variables of interest, as well as interactions of word frequency
Estimatesofthe3translationand3rotationmovementsateachtime
point, computed during registration, were saved for use as noise with letter length, consistency, bigram frequency, and image-
covariates. Image volumes containing artifacts were identified using ability,foreffectsonRT.TheoverallmeanRTwas588ms(SD:
AFNI’s 3dToutcount program and subsequently removed from the 123). Unique variance wasexplained by letter length (b= 7.3,
analysis. A local Pearson correlation algorithm (Saad et al. 2009) was P < 0.0001), frequency (b = –22.6, P < 0.05), and consistency
used to align each T1-weighted structural volume to the same EPI
(b=–0.4,P <0.05).Asexpected,thedirectionsoftheseeffects
referencevolumethatwasusedtoalignthefunctionalscans.
weresuchthatwordswithmoreletters,lowerfrequency,and
Audio recordings of the reading responses were processed using
moreenemieswereassociatedwithlongerlatencies.Noother
acombinationofafreelyavailablecorrelation-basednoisesubtraction
algorithm (Cusack et al. 2005) and custom software developed in- main effects or interactions were significant. In addition to
house. This approach suppressed scanner noise while leaving the includingallvariablesofinterestinthesameregressionanalysis
speech signal intact and automatically paired reading responses with to determine the unique effects of each variable, it is also
stimulus onset markers. RTs were calculated from stimulus onset to informativetoexamineseparatepairwisecorrelationsbetween
responseonset.Valuesmorethan2SDsfromeachsubject’sownmean
eachvariableandRT.Thismethodbroadlyagreedwiththefull
werecheckedand,whennecessary,manuallydeterminedbyvisualand
regression model, with letter length, word frequency, and
auditoryinspectionoftheaudiofile.Responseswereconsiderederrors
if the subject stuttered, produced a mispronunciation, failed to consistency showing reliable correlations with RT. They
D
respond, or responded with an RT more than 3SDs from the group differed only in that imageability showed a reliable pairwise o
w
mean.TheseRTs,calculatedforeachitemrespondedtoindividuallyfor correlationwithRTbutdidnotexplainuniquevarianceinthe n
eachsubject,wereusedasacovariableinthefMRIregressionanalysis. fullmodel.Pairwisecorrelationswereasfollows:letterlength, loa
d
Voxelwise multiple linear regression was performed using 3dDe- e
r = 0.174, P < 0.001; word frequency, r = –0.193, P < 0.0001; d
convolve(Ward2006).Thisanalysisincludedthefollowingcovariables consistency, r = –0.092, P < 0.05; imageability, r = –0.097, P < fro
of no interest: a fourth-order polynomial to model low-frequency m
tswrigeennreadlsm,intohdtehe6leedpvreuensvtiirnoicgulsealsygucaasmelcdmulataotveamdriomadtoeetlieonsntoimipseaar.taeCmooevftaetrrhisae,balhenesdmoaoftdeiynrntmearmefoiscrt P0.0>5;0b.0ig5r.ams,r=–0.0036,P >0.05;andbiphones,r=–0.0254, http://ce
response function and consisted of the following 14 terms: binary rco
variablesfor1)successfulreadingaloudtrialsand2)trialsinwhichthe Imaging r.o
x
svualbujeesctfomr 3ad)eRTa,n4)erlerottneeroluesngtrhes,p5o)nwseo;rdcofrnetqinuueonucsy,, 6m)ecaonn-cseisntteenrceyd, The general contrast of all successful reading responses ford
7) imageability, 8) bigram frequency, and 9) biphone frequency; and compared with fixation baseline (left side of Fig. 1) revealed jou
10--14)interactiontermsofinterest.Interactiontermsincludedinthe activation in the standard overt reading network as seen in rna
modelwerethosethatwepredictedtohaveaneffectonbrainactivity numerous prior studies (e.g., Fiez and Petersen 1998; Turkel- ls.o
(interactionsofwordfrequencywithletter-length,consistency,bigram taub et al. 2002). Activation was observed bilaterally in peri- rg
frequency, and imageability). Detailed consideration of these inter- Rolandiccortices(preandpostcentralgyri),inferiorfrontaland by/
actions,however,isbeyondthescopeofthecurrentreportandwillbe g
insularcortex,superiortemporalgyri,SMA,anddorsalanterior u
presentedinasubsequentarticle. es
The resulting coefficient maps for each participant were linearly cingulatecortex,intraparietalsulci(IPS),occipitalandinferior t o
n
resampledinstandardstereotaxicspacetoavoxelsizeof1mm3and occipito-temporalcortices,aswellassubcorticalnucleisuchas A
spatially smoothed with a 6-mm full-width-half-maximum (FWHM) thethalamus.Therewasnoobviouslateralizationofactivation. ug
u
Gaaruanssdioanmkeefrfneeclt.sTahneasleyssimscooomthpeadricnogeftfihceiecnotemffiacpiesnwtevraelutehsenwpitahssaednutoll Arersepaosnssheoswinincgludgeredatseervearcatlivaaretiaosnoffoternfirxeaptioorntedthtaonsshuocwcetsassfku-l st 10
hypothesis mean of zero across participants. The resulting group , 2
induceddeactivation,suchasbilateralprecuneusandposterior 0
activationmapswerethresholdedatavoxelwiseP <0.01,uncorrected. cingulate gyri, bilateral ventromedial prefrontal cortex, left 16
A cluster-extent threshold was then calculated using AlphaSim to
performMonteCarlosimulationsestimatingtheprobabilityofspatially angular gyrus, and right parahippocampus. Table 3 gives
contiguous voxels for a range of alpha values. Input arguments to a complete list of coordinates for activation maxima, where
AlphaSiminclude1)thevoxelwisethreshold(P <0.01inthiscase),2) positive z-scores represent areas activated for reading aloud
aclusterconnectionradiusspecifyingtheminimumdistanceforwhich compared with fixation and negative z-scores indicate areas
clustersareconsidereddistinct(herer=4.24mm,thediagonallength
activated for viewing fixation compared with reading aloud.
along the face of a single voxel), and 3) the level of smoothing.
Coordinates are listed for extreme maxima (in the case of
ConsideringthefactthatrawMRIdatacontainadegreeofsmoothness
positive values) or extreme minima (for negative values) that
introduced, for example, during image reconstruction from k-space
(Friedman et al. 2006), the actual smoothness of the images was areatleast30mmapartandappearwithinsignificantclusters.
calculatedfromerrorresidualsusingtheAFNIprogram3dFWHMx.The With the exception of the contrast between successful
resultingFWHMvalues(inmm)in3directionsofx=9.2,y=9.1,and readingaloudandfixation,allotherresultsarefromanalysesof
z=7.7wereinputtoAlphaSim.Thisresultedintheremovalofclusters continuouscovariables.Resultsoftheseanalysesaredescribed
smaller than 2052 lL (76 contiguous voxels in the original image
in terms of correlations between each regressor and blood
space),forawhole-braincorrectedprobabilitythresholdofP <0.05.
oxygen level--dependent (BOLD) signal, not activation in
comparison with a baseline. In Figures 1 and 2, hot colors
Results indicateareaswhereBOLDsignalcorrelatedpositivelywiththe
covariable, and cool colors indicate areas where BOLD signal
Performance correlated negatively with the covariable (i.e., greater BOLD
Errors in reading aloud (mispronunciations, false starts, signal for decreasing values of the covariable). For RT (right
omissions, and latencies greater than 3SDs from the mean) side of Fig. 1), the only significant effects were increases in
CerebralCortexAugust2010,V20N8 1803
Figure1. Areasofsignificantactivationforsuccessfulreadingaloudresponsescomparedwithfixationbaseline(leftsideoffigure)andareasofactivationpositivelycorrelated
D
withreactiontime(rightsideoffigure).Noareaswerenegativelycorrelatedwithreactiontime. o
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Effects were obtained for each of the 6 stimulus properties d
TPeaabklepo3ints(positiveornegativeextremes)withinsignificantlyactivatedclustersshowing of interest. Correlations for the 4 primary factors (word from
asignificantmaineffectofeithersuccessfulreadingaloudtrialscomparedwithfixation(upper frequency, spelling--sound consistency, imageability, and h
rLoowcast)ioonrsaparametriceffectofRT(lowerrowxs) y z Z-score bcBliOugrsLatDemrsimgfrneaaqxluiamennadcliyes)ttienarreTleansbhglotehw4wn.ePirnoesoFitbiigvsueerrveceod2r,rienclabotimiloaptnelsertabelemtliwesdteieaonlf, ttp://cerco
SucLcPersescfuelntrreaaldginygruasloud[fixation (cid:1)44 (cid:1)14 35 7.18 ventral, and polar occipital cortices. The signal in left para- r.ox
RLIPnrfeecrieonrtoraclcgipyirtuos-temporal (cid:1)4333 (cid:1)(cid:1)6100 (cid:1)3232 66..8936 hsuippppolecmamenptuasrywfiagsurneegfoatrivaemlyacpoorrfetlhaetesdecwoirtrhellaetniognths.. See the fordjo
RAnteriorinsula 42 5 (cid:1)2 6.67 u
RLateraloccipital 33 (cid:1)87 (cid:1)9 6.28 Positive correlations for word frequency occurred in bi- rna
RLTThhaallaammuuss (cid:1)1134 (cid:1)(cid:1)2186 (cid:1)165 66..1222 lsautlecruasl,aanngduplarregcyurni;ebuisla;taenrdallepfotsstueprieorriocrinfrgounlattaelsguylrciu,ssu.Nbpeagraiteitvael ls.org
LAnteriorsuperiortemporalgyrus (cid:1)46 4 (cid:1)6 5.83 b/
LCerebellum (cid:1)13 (cid:1)29 (cid:1)26 5.77 correlations for word frequency (i.e., increasing BOLD signal y
LAnteriorCingulate (cid:1)13 6 40 5.70 intensity for lower-frequency words) were found in left IFJ, gu
LSuperiortemporalgyrus (cid:1)61 (cid:1)28 5 5.53 es
LSupramarginalgyrus (cid:1)30 (cid:1)43 25 5.02 IFG,anteriorinsula,IPS,andsubgenualcingulate,andbilaterally t o
RIntraparietalsulcus 30 (cid:1)58 41 4.94 inSMA,thalamus,medialoccipitalcortex,andventraloccipito- n A
RSuperiortemporalsulcus 36 (cid:1)53 2 4.46 temporal cortex(left >right). ug
LPlanumpolare (cid:1)32 27 (cid:1)22 4.41 u
RCuneus 2 (cid:1)90 19 4.28 Correlations with spelling-to-sound consistency (number of st 1
RInferiorfrontalsulcus 25 31 20 4.22 friends minus number of enemies) were all in the negative 0
RIFG,parstriangularis 55 25 19 3.85 , 2
direction, indicating increasing neural activity for words with 0
Llateraloccipitalcortex (cid:1)29 (cid:1)92 12 3.80 1
LMTG (cid:1)60 (cid:1)61 8 3.26 more enemies than friends. These areas were all in the left 6
LMiddlefrontalgyrus (cid:1)47 41 21 2.99 hemisphere and included IFJ, IFG/anterior insula and cortex
Fixation[successfulreadingaloud
RAnteriorcingulate 2 42 (cid:1)1 (cid:1)5.10 along the inferior temporal sulcus (ITS) and middle temporal
RSubgenualcingulate 1 7 (cid:1)1 (cid:1)5.02 gyrus (MTG).
RPosteriorcingulate 3 (cid:1)52 32 (cid:1)5.16 Imageabilitywasassociatedwithcorrelatedactivitychanges
LAngulargyrus (cid:1)40 (cid:1)72 30 (cid:1)3.70
broadly similar to those of word frequency, though the areas
Note:CoordinatescorrespondtotheatlasspaceofTalairachandTournoux(1988).L5leftand modulated by imageability were less extensive. Activity
R5right. positively correlated with imageability occurred in bilateral
angular gyri and bilateral precuneus. Areas negatively corre-
lated with imageability included left IFJ and left lateral and
activity with increasing RT (i.e., positive correlations). These ventral occipital cortex, spreading to the posterior inferior
includedbroadlysimilarpatternsinleftandrighthemispheres, temporal gyrus.
withsomewhatgreateractivationontheleft.Thispatternwas Bigramfrequencyelicitedonlynegativelycorrelatedactivity
seenintheIFGextendingbothtothemiddlefrontalgyrusand (greater activity for words with lower bigram frequency),
anteriorinsula,theinferiorfrontaljunction(IFJ,thejunctionof which occurred in bilateral posterior MTG and left supra-
theprecentralandinferiorfrontalsulci),peri-Rolandiccortices, marginal gyrus. Biphone frequency was not significantly
SMA, thalamus, and posterior superior temporal sulci. Exclu- correlated with activity in anybrain region.
sivelyleft-sidedactivationappearedinIPS,supramarginalgyrus, We also reran the analysis with a model that included all
andtemporo-occipitalsulcus.SeeTable4foracompletelistof variables exceptRTtoexaminethepossibility, asdiscussedin
clusters alongwith their activation maxima andcoordinates. Wilson et al. (2009), that inclusion of an RT regressor might
1804 NeuralSystemsforReadingAloud d Gravesetal.
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Figure2. Brainareasshowingasignificantmaineffectofthevariouswordpropertiesofinterest.Hotcolorsrepresentpositivecorrelationsbetweenneuralactivityandthe by/
regressor(e.g.,increasingactivitywithincreasingvaluesofwordfrequency),andcoolcolorsrepresentnegativecorrelations(e.g.,decreasingactivitywithincreasingvaluesof gu
wordfrequency). es
t o
n
A
have distorted effects of the psycholinguistic variables with aspect of the pars orbitalis and the more dorsal in pars ug
u
which it was correlated. Results of this analysis were nearly triangularis. Several areas outside the frontal lobe also showed st 1
identical tothat of thefull model. extensiveoverlapbetweenpositiveRTandnegativefrequency 0
, 2
There was widespread spatial overlap of areas exhibiting effects.TheseincludedtheleftIPS,bilateralanteriorcingulate 0
1
amaineffectofsuccessfulnamingandthoseshowingincreased gyrus,bilateral calcarine sulcus, andbilateral thalamus. 6
activation with increasing RT. Positive effects of RT also Effectsofdecreasingwordfrequency,consistency(toasmall
overlapped with negative effects of word frequency, consis- extent),andincreasingRT,butnotimageability,alsooverlapin
tency,andimageability,primarilyinleftIFJ.RToverlappedwith theleftmid-fusiformgyrus(ventralsurfaceintheupperpartof
negative consistency and frequency effects in left IFG and Fig.3). Thisarea haspreviously been implicatedin processing
anterior insula. In the upper part of Figure 3 are composite ofvisualwordformsbuthasnottypicallybeenassociatedwith
maps showing effects of lexical variables that overlapped general performance effects (although RT effects in this area
extensivelywitheffectsofRT,raisingthepossibilitythatsome for reading aloudwerereported previously byBinder, Medler,
of these effects could be related to general performance et al.2005).
processes (e.g., attention, cognitive control, and working Acombinationofeffectsthatmayinvolvelexicalprocesses
memory). As mentioned in the Introduction, specific lexical morespecificallyisshowninthelowerpartofFigure3.Areas
andgeneraltask processes aredifficulttodisentanglebecause showingincreasingactivityforwordsofincreasingfrequency
both are related to time on task. Areas of the left IFG and IFJ overlap mainly with areas showing increasing activity for
havebeenimplicatedinbothtypesofprocesses,andbothareas words of increasing imageability. This overlap is seen
show increased activity for reading words with decreasing primarily in bilateral angular gyri and left precuneus (light
imageability,decreasingconsistency,decreasingfrequency,and green in the lower part of Fig. 3). Neither of these regions
longerRT.This4-partoverlapisshowninthetoppartofFigure shows any RT effects. Similarly, posterior temporal and
3. In contrast, there were 2 regions in left IFG that showed inferior parietal areas showing increasing activity with
isolated effects of decreasing spelling--sound consistency (red decreasing bigram frequency show no overlap with areas
areas in Fig. 3). The more ventral of these is in the anterior modulated by RT. Finally, inferior temporal regions showing
CerebralCortexAugust2010,V20N8 1805
Table4 Table4
Peakpoints(positiveornegativeextremes)withinclustersshowingsignificantcorrelationswith Continued
BOLDsignalforeachoftheparametricfactorsofinterest
Location Cluster x y z Z-score
Location Cluster x y z Z-score of size
of size extremepoint (lL)
extremepoint (lL)
LIFJ (cid:1)46 3 30 (cid:1)4.65
PositiveRTcorrelations Occipito-temporal 3169
Fronto-parietal 36437 LLateraloccipitalcortex (cid:1)35 (cid:1)82 (cid:1)10 (cid:1)4.16
LPrecentralgyrus (cid:1)38 (cid:1)5 37 5.29 Negativebigramfrequencycorrelations
LAnteriorinsula (cid:1)33 10 (cid:1)2 4.11 RPosteriortemporal 3029
LIntraparietalsulcus (cid:1)42 (cid:1)42 47 3.89 RPosteriorMTG 64 (cid:1)62 11 (cid:1)4.17
LMiddlefrontalgyrus (cid:1)30 46 27 3.69 LPosteriortemporal 2368
Precentralandprefrontal 17382 LPosteriorMTG (cid:1)53 (cid:1)51 11 (cid:1)4.42
RIFG,parsorbitalis 43 19 (cid:1)8 4.37 Temporo-parietaljunction 2090
RPrecentralgyrus 48 (cid:1)15 36 4.37 LSupramarginalgyrus (cid:1)57 (cid:1)31 28 (cid:1)3.61
Medialfronto-parietal 12613
LSMA (cid:1)2 7 50 4.69
RCallosalsulcus 7 14 21 3.75
LParacentrallobule (cid:1)7 (cid:1)42 52 3.15
increasingactivityforlessconsistentwordsalsoshowlittleor
LSuperiortemporal 5312
LPosteriorsuperiortemporalsulcus (cid:1)49 (cid:1)38 3 3.98 no overlap with areas modulated by RT.
Subcortical 4444
LThalamus (cid:1)9 (cid:1)15 10 3.62
RSuperiortemporal 3456 D
RSuperiortemporalgyrus 60 (cid:1)16 (cid:1)2 3.53 Discussion ow
Medialoccipital 2745 n
RCalcarinesulcus 12 (cid:1)71 8 3.48 Bothseparateandoverlappingpatternsofneuralactivitywere loa
Ventraloccipito-temporal 2091 detected for the 6 uncorrelated factors of interest. The data de
PositivLeTleemtteprorloe-nogctchipcitoarlreslualtciounss (cid:1)47 (cid:1)40 (cid:1)17 3.91 suggest a neural architecture in which distinct orthography-- d fro
Medialoccipital 24259 phonologyandsemanticpathwaysareengagedduringreading m
NegatRLivLeLiinnleggtuutaealrlggleyynrruugssthcorrelation (cid:1)1138 (cid:1)(cid:1)8872 (cid:1)(cid:1)142 55..1286 afrloonutda.lTrehgeiornessuinltsreaalsdoincglaarliofyudt.he role of several left inferior http://c
e
Medialtemporo-cerebellar 3565 rc
PositivLeCweroerbdefllruemquencycorrelations (cid:1)11 (cid:1)41 (cid:1)13 (cid:1)4.11 Overlapping EffectsofIncreasing TaskLoad or.ox
MeRdiaPlosptaerrieiotralcingulate 17991 1 (cid:1)55 25 5.93 As illustrated in the upper part of Figure 3, effects in the ford
LPosteriorcingulate (cid:1)6 (cid:1)29 40 4.23 negativedirection(relativelygreateractivityforlowerstimulus jou
RLateralparietal 14722 property values) for word frequency, consistency, and image- rn
RRASunpgrualamragrgyirnuaslgyrus 4415 (cid:1)(cid:1)6239 3297 53..4225 ability all overlapped with positive RT effects in left IFJ, and als.o
LLLatAernagluplaarriegtyaruls 13556 (cid:1)36 (cid:1)80 25 4.67 nReTgaitniveleeftffeIcFtGs.ofPfrreevqiouuenscystuanddiescoonfsisrteeandciyngovesurlgagpepseteddwiitnh- byrg/
LSupramarginalgyrus (cid:1)62 (cid:1)41 31 4.10 g
Lateralprefrontal 2097 volvementoftheseareasinphonologicalprocessing(De´monet ue
s
LMiddlefrontalgyrus (cid:1)30 22 43 5.11 etal.1992;FiezandPetersen1998;Fiezetal.1999,2006;Price t o
Negativewordfrequencycorrelations n
Ventraloccipito-temporal 47069 2000; Bookheimer 2002; Fiebach et al. 2002; Price, Gorno- A
RFusiformgyrus 39 (cid:1)44 (cid:1)20 (cid:1)5.02 Tempini, et al. 2003; Joubert et al. 2004; Mechelli et al. 2005), ug
u
RLFCuaslcifaorrimnegsyurulcsus (cid:1)1328 (cid:1)(cid:1)6359 (cid:1)187 (cid:1)(cid:1)44..7154 warheaesrewasithotmheorrestguednieesralhafuvencatisosnosciasutecdh easssecnotginaliltyivethceonsatrmoel, st 10
LLateraloccipitalcortex (cid:1)37 (cid:1)78 (cid:1)20 (cid:1)4.08 , 2
Lateralfronto-parietal 29239 attention, and working memory (LaBar et al. 1999; Derrfuss 0
1
LIFJ (cid:1)47 5 28 (cid:1)5.07 et al. 2005; Owen et al. 2005). Of the major computational 6
LIntraparietalsulcus (cid:1)24 (cid:1)56 41 (cid:1)3.85
LMiddlefrontalgyrus (cid:1)42 (cid:1)4 60 (cid:1)3.51 modelsofreading(e.g.,Plautetal.1996;Coltheartetal.2001;
Infero-medialandsubcortical 12000 HarmandSeidenberg2004;Perryetal.2007),weareawareof
LSubgenualcingulate (cid:1)4 20 (cid:1)1 (cid:1)5.56 none that attempt to disentangle reading-specific effects from
LThalamus (cid:1)11 (cid:1)19 8 (cid:1)5.11
RThalamus 16 (cid:1)30 (cid:1)1 (cid:1)4.15 more general performance effects. Our data suggest the
Medialprefrontal 6045 possibility that the areas shown in white and those in orange
LSMA (cid:1)7 7 47 (cid:1)5.23
within the RT outline in the upper part of Figure 3 may be
RAnteriorcingulate 9 22 26 (cid:1)3.38
Negativespelling--sound engaged in general task-performance processes such as
consistencycorrelations cognitive control, attention, or working memory, which are
Lateralprefrontal 10738
LIFJ (cid:1)42 6 30 (cid:1)5.25 sensitivetoanyincreaseintaskloadregardlessofthesourceof
Middleandinferiortemporal 3162 the increased demand.
LITS (cid:1)53 (cid:1)51 (cid:1)3 (cid:1)3.62 Incontrasttotheseleftinferiorfrontalregions,theleftmid-
LFusiformgyrus (cid:1)40 (cid:1)24 (cid:1)10 (cid:1)3.56
Positiveimageabilitycorrelations fusiform gyrus shows areas of overlap between positive RT
LLateralparietal 4181 effects and negative effects of word frequency and to some
LAngulargyrus (cid:1)57 (cid:1)64 18 3.67
extentconsistencybutnotimageability.Weretheseactivations
Medialparietal 2762
LPosteriorcingulatecortex (cid:1)4 (cid:1)43 38 3.80 purely related to general processing demands, activity nega-
RLateralparietal 2531 tively correlated with imageability would be expected as
RAngulargyrus 43 (cid:1)68 41 3.31
Negativeimageabilitycorrelations well (as is the case in left inferior frontal regions). This left
Lateralprefrontal 9035 mid-fusiform gyrus area has been referred to as the ‘‘visual
word-formarea’’(VWFA)becauseofitspreferentialresponseto
1806 NeuralSystemsforReadingAloud d Gravesetal.
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Figure3. Upperpartshowscompositeimagesoffactorsreflectingeitherlexicalorperformanceeffects.Notetheoverlapofformandsemanticvariableswith RTinleft
prefrontalareasandthepresenceofwordfrequency,consistency,andRTbutnoimageabilityeffectsintheventraltemporal/fusiformarea.Thelowerpartshowscomposite
imagesoffactorsreflectingadditionalactivationsandoverlapsthatmayindicatecontributionsfromsemantics,particularlyinbilateralprecuneusandangulargryiwherepositive
word-frequencyandimageabilityeffectsoverlap.ColorcodesreflectareaswhereactivationforeachconditionreachedacorrectedmapwisesignificancethresholdofP\0.05.
well-formedletterstrings(Cohenetal.2002;McCandlissetal. whereas a review that transformed coordinates to Montreal
2003; Cohen, Jobert, et al. 2004; Dehaene et al. 2005). Two NeurologicalInstitute(MNI)space(foradiscussionofMNIand
reviews place the center coordinate for this area in Talairach Talairach spaces see http://imaging.mrc-cbu.cam.ac.uk/imag-
and Tournoux (1988) space at x, y, and z = –43, –54, and –12 ing/MniTalairach) gives it as –44, –58, and –15 (Jobard et al.
(Cohen et al. 2002) and –42, –55, and –12 (Bolger et al. 2005), 2003). All report an SD of approximately 5 mm, placing these
CerebralCortexAugust2010,V20N8 1807
coordinates within 1SD of each other. Although the nearest relation to uncommon words. Word frequency is highly
localminimumforwordfrequencyandlocalmaximumforRT correlated with concept familiarity (Toglia and Battig 1978;
aresomewhatanteriortothislocation,bothclustersextendto Baayenetal.2006),contextualdiversity(i.e.,theproportionof
clearly include the VWFA coordinate. Not only has this area documents that contain the word; Adelman et al. 2006), and
been shown to be positively correlated with graphotactic probability of word association (Nelson and McEvoy 2000).
probability in functional brain-imaging studies of healthy Word frequency facilitates performance on semantic decision
readers (Binder et al. 2006; Vinckier et al. 2007), but it is also tasks, suggesting that semantic information is more easily
one of the major areas that, when damaged, leads to a type of available for high-frequency words (Monsell et al. 1989; Chee
acquired dyslexia known as pure alexia (i.e., alexia without et al. 2002). Consistent with these observations, increasing
agraphia;BinderandMohr1992;Leffetal.2001;Cohen,Henry, wordfrequencyproducedcorrelatedincreasesinBOLDsignal
et al. 2004). There has been debate, however, about whether in essentially the same brain regions that were modulated by
thisregionsupportsorthographicprocessingperseoramore increasing imageability and over an even larger spatial extent
generalprocess(PriceandDevlin2003),perhapsrelatedtothe withintheseregionsthantheareasmodulatedbyimageability.
mapping between visual input and phonology (Price, Winter- Surprisingly,however,positiveeffectsofwordfrequencyhave
burn, et al. 2003; Sandak et al. 2004; Hillis et al. 2005). Our only rarely been reported in previous neuroimaging studies. In
results, showing activation of this area with longer RT and one study, higher-frequency words activated left temporal and
lower values of word frequency and spelling--sound consis- parietal regions during reading and semantic decision tasks
tency but not imageability, suggest that it may support when compared with a low-level baseline task, whereas lower-
a relatively specific yet integrative function such as the frequency words did not (Chee et al. 2002). However, these
D
mapping between orthography andphonology. activations did not survive a direct contrast between high- and o
w
Analternatepossibilitythatcannotberuledoutinthisstudy low-frequency words. The left angular gyrus was activated in n
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is that top-down attention systems amplify processing of anotherstudycomparingsilentreadingofhigh-frequencywords a
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orthographic codes in order to help complete the mapping with consonant strings (Joubert et al. 2004), but again, this d
to phonology. This interpretation, however, rests on the activationdidnotsurviveadirectcomparisonbetweenhigh-and fro
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assumption that attention systems can selectively modulate low-frequencywords.Toourknowledge,only2previousstudies h
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frequency and consistency, but not imageability, effects in observed activation in the precuneus in a direct comparison rco
the putative VWFA suggests that this region supports in- between high- and low-frequency words, which they inter- r.ox
tegration of orthographic and phonological information. preted as reflecting ‘‘more pronounced semantic associations’’ ford
Additionally, although this discussion of VWFA has focused forthoseitems.Similarly,usinganauditorylexicaldecisiontask, jo
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on properties of the area surrounding its center coordinate, Prabhakaranetal.(2006)observedactivationintheprecuneus, rn
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thereisalsoevidenceofgradedfunctionalongtheleftfusiform along with left middle temporal and angular gyri, in a direct ls.o
gyrus, particularly in the posterior--anterior direction. For comparison between high- and low-frequency words. Other rg
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example, along the left fusiform gyrus Vinckier et al. (2007) studies that examined frequency effects,however, reported no y
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reported posterior activity modulated by letter frequency, activations related to increasing frequency (Fiez et al. 1999; u
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somewhat more anterior activity for bigram frequency, and Fiebachetal.2002;Kronbichleretal.2004;Carreirasetal.2006; t o
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more anterior still for quadrigram frequency. Functional Nakicetal.2006;Hauk,Davis,andPulvermu¨ller2008).Threeof A
heterogeneity within the left fusiform gyrus can also be seen these studies restricted their word frequency analyses to areas ug
u
intheworkofHauk,Davis,Kherif,andPulvermu¨ller(2008)and that were more active for words compared with a resting st 1
Hauk,Davis,andPulvermu¨ller(2008),whoreportactivationfor baseline(Fiezetal.1999;Kronbichleretal.2004;Carreirasetal. 0
, 2
words compared with baseline (viewing length-matched hash 2006). As can be seen by comparing the successful reading 0
1
marks) within 1 cm anterior to the McCandliss et al. (2003) conditioninFigure1withtheword-frequencyresultinFigure2, 6
coordinate, activity modulated by word frequency 2 cm if the word frequency analysis had been restricted to areas
anterior, and activity modulated by imageability 1 cm medial showingactivationforwordscomparedwiththerestingbaseline,
to the VWFA coordinate. Further study will no doubt help the areas more active for higher-frequency words would have
clarify thefunctional heterogeneity inthis region. beenexcluded.Asdiscussedelsewhere(Binderetal.2009),the
semantic system appears to be active during resting and other
passivestates.Oneimplicationofthisisthatactivityinthesetof
Effectsof Increasing Word Frequency andImageability areas sometimes referred to as the default mode network
Anothersetofoverlapsinvolvespositivecorrelations between (Gusnard and Raichle 2001), which includes bilateral posterior
neuralactivation and increasing values of word frequency and cingulate/precuneus,dorsomedialprefrontalcortex,andangular
imageability (lower part of Fig. 3). These regions, which gyri, may at least partially reflect semantic processes. Thus,
include the angular gyrus and precuneus/posterior cingulate contraststhatusearestingbaselinearelikelytomisstheseregions.
cortex bilaterally, have been strongly implicated in semantic Other studies that did not exclude brain regions from the
processes(Binderetal.2009)andhaveshownactivationwith frequency contrast may have been less sensitive because
increasing word imageability in previous imaging studies frequency was treated as a categorical variable (Fiebach et al.
(Jessen et al. 2000; Binder, Medler, et al. 2005; Binder, 2002; Nakic et al. 2006) or because of smaller stimulus and
Westbury, et al. 2005; Sabsevitz et al. 2005; Bedny and subject sample sizes. The reason for the lack of activation for
Thompson-Schill 2006). One can also intuit that higher- high-frequency words in the Hauk, Davis, and Pulvermu¨ller
frequency words are more likely to elicit automatic activation (2008) study is less clear but may relate to the fact that their
in a semantic network due to their extensive exposure in stimuliwerepresentedmorerapidly.Stimuliweredisplayedfor
1808 NeuralSystemsforReadingAloud d Gravesetal.