mind your language, all right?
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LinköpingUniversitymedicaldissertations,No.1358
Mind your Language, All Right? Performance‐dependentneuralpatternsoflanguage
Helene van Ettinger‐Veenstra
CenterforMedicalImageScienceandVisualization
DivisionofRadiologicalSciencesDepartmentofMedicalandHealthSciences
LinköpingUniversity,Sweden
Linköping2013
©HelenevanEttinger‐Veenstra,2013helene.veenstra@liu.sePublishedpapershavebeenreprintedwithpermissionofthecopyrightholdersCoverdesign:TjeerdVeenstrawww.tjeerdveenstra.nlPrintedinSwedenbyLiUTryck,Linköping,Sweden,2013ISSN0345‐0082ISBN978‐91‐7519‐668‐8
voor mijn lieve Lucas Levi
They say the left side of the brain Dominates the right
And the right side has to labor through The long and speechless night
… Maybe I think too much
‘ThinkTooMuch(b)’‐PaulSimon
I
ABSTRACT
The main aim of this dissertation was to investigate the difference in neural language patterns
related to language ability in healthy adults. The focus lies on unraveling the contributions of the
right‐hemispherichomologuestoBroca’sareaintheinferiorfrontalgyrus(IFG)andWernicke’sarea
intheposteriortemporalandinferiorparietallobes.Thefunctionsoftheseregionsarefarfromfully
understood at present. Two study populations consisting of healthy adults and a small group of
people with generalized epilepsy were investigated. Individual performance scores in tests of
languageabilitywerecorrelatedwithbrainactivationobtainedwithfunctionalmagneticresonance
imagingduringsemanticandwordfluencytasks.Performance‐dependentdifferenceswereexpected
in the left‐hemispheric Broca’s and Wernicke’s area and in their right‐hemispheric counterparts.
PAPER I revealed a shift in laterality towards right‐hemispheric IFG and posterior temporal lobe
activation, related to high semantic performance. The whole‐brain analysis results of PAPER II
revealednumerouscandidateregions for languageabilitymodulation.PAPERIIalsoconfirmedthe
findingofPAPERI,byshowingseveralperformance‐dependentregionsintheright‐hemisphericIFG
andtheposteriortemporallobe.InPAPERIII,anewstudypopulationofhealthyadultswastested.
Again,therightposteriortemporallobewasrelatedtohighsemanticperformance.Adecreaseinleft‐
hemispheric IFG activation couldbe linked tohighword fluency ability. In addition, taskdifficulty
was modulated. Increased task complexity showed to correlate positively with bilateral IFG
activation.Lastly,PAPERIVinvestigatedanti‐correlatedregions.Theseregionsarecommonlyknown
as the default mode network (DMN) and are normally suppressed during cognitive tasks. It was
foundthatpeoplewithgeneralizedepilepsyhadan inadequatesuppressionofregions intheDMN,
andshowedpoorerperformanceinacomplexlanguagetest.Theresultspointtoneuraladaptability
in the IFG and temporal lobe. Decreased left‐lateralization of the IFG and increased right‐
lateralizationoftheposteriortemporallobeareproposedascharacteristicsofindividualswithhigh
languageability.
II
III
SAMMANFATTNING
Somvuxnamänniskorärvi,ävendåviärfriska,väldigtolika,medolikaförmågor.Såärdet
också med språklig förmåga. Det varierar betydligt mellan olika personer hur bra
läsförståelsemanhar,ellerhurlättmanharatthittapåord.Dennaavhandlingbyggerpåatt
dessa mätbara språkliga skillnader också kan synliggöras i hjärnan med hjälp av
hjärnscanning, så kallad funktionell magnetresonanstomografi. Hjärnaktivering vid
språkfunktion är ofta koncentrerad i den vänstra hjärnhalvan; i nedersta delen av
pannloben samt i bakre delen av tinningloben, men även den högra hjärnhalvan kan
aktiverasavfleraolikaspråkfunktioner.Specielltfinnsdefunktionersomfårenpersonatt
förstå komplicerade språkkomponenter, till exempel bildspråk eller andra typer av
underliggande betydelser i språket, i den högra hjärnhalvan. I studierna som ligger till
grundfördennaavhandlingförväntadesatthjärnaktiveringenivanligaspråkområdeniden
vänstra hjärnhalvan skulle varieramed språklig förmåga. Om personer som är bättre på
språkharenhjärnasomfungerarmereffektivt,såskulledetvisasigsommindreaktivering
i vänstersidiga språkområden. Å andra sidan, om personer som presterar bra har bättre
kognitiv förmåga än sämre presterande, skulle det kunna synas sommer aktivering i de
understödjande språkområdena i höger hjärnhalva. Resultaten som framgår i denna
avhandling är framför allt att aktivering i höger tinninglob är involverad i bättre språklig
förmåga. Det finns också antydningar att nedre delen av den högra pannloben är mer
aktiveradnärmanärbrapåspråk.Resultatenvisadesigdockattvarieramedspråkuppgift;
detfinnsbevisförmeraktiveringihögerpannlobisambandmedbättrespråkförståelseoch
förmindre aktivering i vänster pannlob i sambandmed bättre förmåga att generera ord.
Dessutomärdennedredelenavpannlobenmeraktivvidsvårarespråkförståelseuppgifter.
Slutsatsenavdessastudierärattaktiveringidennedrepannlobenärberoendeavkognitiv
kapacitet, men att aktivering i den högersidiga bakre tinningloben är specifik för
språkförståelse.Destudiersomärinkluderadeiavhandlingenvisarattdestobättremanär
påspråk,destomindreanvändermanenbartdenvänstrahjärnhalvannärman läsereller
genererarord.
IV
V
LIST OF PUBLICATIONS
This dissertation is based on the following original papers, which are referred to throughout the text by their Roman numerals:
PAPER I Van Ettinger‐Veenstra HM, Ragnehed M, Hällgren M, Karlsson T, Landtblom A‐M,LundbergP,andEngströmM(2010).Right‐hemisphericbrainactivationcorrelatestolanguageperformance.NeuroImage49(4):3481–3488.
PAPER II VanEttinger‐VeenstraHM,RagnehedM,McAllisterA,LundbergP,andEngströmM(2012). Right‐hemispheric cortical contributions to language ability in healthyadults.BrainandLanguage120(3):395–400.
PAPER III Gauffin H*, Van Ettinger‐Veenstra HM*, Landtblom A‐M, Ulrici D, McAllister A,Karlsson T, and EngströmM. Impaired language function in generalized epilepsy:Inadequate suppression of the default mode network. Accepted in Epilepsy &Behavior,2013.
PAPER IV VanEttinger‐VeenstraHM,KarlssonT,McAllisterA,LundbergP, andEngströmM.Lateralityshifts inneuralactivationcoupledto languageability.SubmittedtoPLoSONE,2013.
* The first two authors contributed equally to this paper
Related Peer‐Reviewed Conference Abstracts
VeenstraHM,RagnehedM,HällgrenM,LundbergP,andEngströmM.Brainlateralizationassessedby
fMRIanddichoticlistening.Paperpresentedatthe15thAnnualMeetingoftheOrganizationforHumanBrainMapping,California,USA,2009.
VeenstraHM,PetterssonJ,NelliC,RagnehedM,McAllisterA,LundbergP,andEngströmM.Influenceof performance‐related language ability on cortical activation. Paper presented at the 15thAnnualMeetingoftheOrganizationforHumanBrainMapping,California,USA,2009.
VanEttinger‐VeenstraH,KarlssonT,UlriciD,GauffinH,LandtblomAM,andEngströmM.Languageability inhealthyandepilepsyparticipants:an fMRI investigation.Paperpresentedat the43rdEuropeanBrainandBehaviourSocietyMeeting,Seville,Spain,2011.
VanEttinger‐VeenstraH,GauffinH,McAllisterA,LundbergP,UlriciD,LandtblomA‐M,andEngströmM.Languagedeficits inEpilepsy,anfMRIstudy.Paperpresentedatthe18thAnnualMeetingoftheOrganizationforHumanBrainMapping,Beijing,China,2012.
VI
AT A GLANCE
PAPER (study)
I (A)
II (A)
III (B)
IV (B)
METHODS
14healthyadults.fMRI:LateralizationIndexfromsentencereading(SENCO)taskwascorrelatedwithRead,BeSS,FAS&BNTperformancescores.Also,DichoticListeninglateralitymeasurementswereinvestigated.
18healthyadults.Whole‐brainanalysesfromsentencereading(SENCO)andwordfluency(WORGE);activationwascorrelatedwithRead,BeSS,FAS&BNTperformancescores.
27healthyadults.LateralizationIndexfromROIanalysesofsentencereading(SEN)andwordfluency(WORD),correlatedwithperformancescoresonBeSSandFAS.Also,taskdifficultyrelatedbrainactivationwasinvestigatedwithmultipleregression.
27healthy&11GeneralizedEpilepsyparticipants.Investigatedfordeactivationinthedefaultmodenetworkduringsentencereading(SEN).Also,languageperformancemeasurementsoftheepilepsygroup.
VII
RESULTS
Activationintheright‐hemisphericROIswasmorepronouncedforhighperformance.Thiscorrelatedwiththedichoticlisteningresults.EspeciallyhighBeSSandReadscorescorrelatedwithincreasedright‐lateralization.
SeveralclustersinrightIFGandtemporallobeshowedtocorrelatewithBeSSandReadonthesentencereadingfMRItask.Nosuchresultsforwordfluency.
Activationinthetemporallobewasmoreright‐lateralizedforhighBeSSperformance.ActivationinleftIFGwaslessleft‐lateralizedforhighFASperformance.ThedifficultincongruentsentencereadingconditionwascharacterizedbybilateralIFGactivation
PeoplewithGeneralizedEpilepsyshowedworseperformanceinBeSSthanhealthycontrols.TheyalsoshoweddiminishedDMNdeactivation,notablewasthedecreasedlefttemporallobedeactivationandincreasedhippocampalactivation.
CONCLUSIONS
BothdichoticlisteningandfMRIresultspointtoaright‐hemisphericactivationasacharacteristicforhighlanguageability.
Regionsininferiorfrontalgyrus(BA47)andmiddletemporalgyrus(BA21)arerelatedtohighsemanticlanguageability.
Activationintheinferiorfrontalgyrusismodulatedbysemanticdifficulty,whilerighttemporallobeactivationisspecificforsemanticability.
PeoplewithGeneralizedEpilepsyexperiencelanguagedifficulties.Thiscouldbeexplainedbyaberrantsuppressionofactivationinthedefaultmodenetwork.Afailuretosuppressdefaultmodenetworkactivationisdisturbingforcognitivefunctioning.
VIII
IX
ABBREVIATIONS
BA BrodmannArea
BeSS “BedömningavSubtilaSpråkstörningar”–AssessmentofSubtleLanguageDeficits
BNT BostonNamingTest
BOLD BloodOxygenLevelDependent
DMN DefaultModeNetwork
fMRI functionalMagneticResonanceImaging
FWE Family‐WiseError
GE GeneralizedEpilepsy
GLM GeneralLinearModel
IFG InferiorFrontalGyrus
LI LateralityIndex
MNI MontrealNeurologicalInstitute
MRI MagneticResonanceImaging
P‐FIT Parieto‐FrontalIntegrationTheory
ROI RegionofInterest
SEN sentencereadingfMRItaskusedinPAPERIII&PAPERIV
SENCO sentencecompletionfMRItaskusedinPAPERI&PAPERII
WORD wordgenerationfMRItaskusedinPAPERIII
WORGE wordgenerationfMRItaskusedinPAPERII
CONTENTS
ABSTRACT I
SAMMANFATTNING III
LIST OF PUBLICATIONS V
AT A GLANCE VI
ABBREVIATIONS IX
1 INTRODUCTION 1
1.1 LANGUAGE ABILITY 21.1.1 LanguageAbilities 21.1.2 LanguageDysfunctions 3
1.2 NEURAL CORRELATES TO LANGUAGE 41.2.1 LanguageModels 41.2.2 Semantics 81.2.3 WordFluency 81.2.4 Right‐HemisphericInfluences 81.2.5 Laterality 91.2.6 Anti‐correlatedBrainActivation 10
1.3 INTELLIGENCE MODELS FOR LANGUAGE ABILITY 111.3.1 RelationLanguageAbilityandIntelligence 111.3.2 IntelligenceModels 11
1.4 AIMS 13
2 METHODS 15
2.1 NEUROLINGUISTIC MEASURES 152.1.1 TestsofLanguageAbility 152.1.2 DichoticListening 162.1.3 fMRILanguageParadigms 162.1.4 StudyPopulation 172.1.5 GeneralizedEpilepsy 17
2.2 FUNCTIONAL MRI 182.2.1 PropertiesofFunctionalMRI 18
2.2.2 RegionofInterestAnalysis 192.2.3 LateralityIndexAnalysis 20
3 RESULTS 23
3.1 MULTIPLE REGRESSION ANALYSES 243.2 LATERALITY ANALYSES 273.3 TASK DIFFICULTY MODULATION 283.4 LANGUAGE DYSFUNCTIONS IN EPILEPSY 29
4 DISCUSSION 31
4.1 NEURAL CORRELATES TO PERFORMANCE 314.1.1 MultipleRegressionAnalyses 314.1.2 LateralityAnalyses 334.1.3 TaskDifficultyModulation 344.1.4 LanguageDysfunctionsinEpilepsy 35
4.2 HEALTHY ADULTS 364.3 INTERPRETATION OF ACTIVATION PATTERNS 374.4 FUTURE DIRECTIONS 42
5 CONCLUSIONS 45
ACKNOWLEDGMENTS 46
REFERENCES 49
PAPER I
PAPER II
PAPER III
PAPER IV
Big black cloud On a yellow plain Sure enough it Looks like rain
Packin' up all our Faith and trust
Me and the wanderlust
‘Wanderlust’‐MarkKnopfler
1
1 INTRODUCTION
Mapping of language disability patterns requires a thorough understanding of language ability
patterns.Theneuralpathways forperceivingandgenerating languageare slowlybeingunraveled,
buttheexactcontributionsoftypicalleft‐hemisphericlanguageareas(Broca’sandWernicke’sarea)
are not yet completely clear. Neither is the role of language‐related regions in the – usually non‐
dominant–righthemisphere.Theopinionabouthowright‐hemisphericregionsinfluencelanguage
has changed. In the past, activation in the right hemisphere during language tasks was largely
overlooked;butovertime,researchersgainedanunderstandingoftheemotionalcontentprocessing
aspects.Atpresent,additionalrolesoftherighthemisphereinlanguagearebeingexplored,including
language comprehension aspects. Evidence of these right‐hemispheric comprehensive aspects is
presentedinthisdissertationwithinaframeworkofmanifestationsoflanguageabilityinthebrain.
This dissertation presents four papers that investigated language ability, which was defined as
languageproductionandcomprehensionabilities.Thefirstthreepapersdescribehowhealthyadults
were tested for brain activation evoked by neurolinguistic functionalmagnetic resonance imaging
(fMRI) tasks. These fMRI tasks measured semantic processing and word fluency activations. The
resultswere related to individual performancemeasurements in various tests of language ability,
including reading, word fluency, picture naming and use of complex language. The fourth paper
discusseshowthebrainsofpeoplewithgeneralizedepilepsycanexpressalteredactivationpatterns
inrelationtolowerlanguageability.
1.INTRODUCTION
2
1.1 Language Ability
1.1.1 Language Abilities
Theabilitytoproducelanguageenablesonetocommunicateone’sownthoughtsandexpressoneself.
Comprehensionoflanguagewillenableonetoperceiveinformationthatmightbeneworinteresting.
Asinallskills;individualdifferencesarepresent.Theoriginsofthesedifferencesmightbeattributed
to the amount of exposure to language, or to one’s own interests in reading or verbal expression.
Wheneverpeoplemanifestdifferencesinbehavior,neuroimagerswilllookfortheneuralcorrelates
to these differences. Indeed, the rationale behind the performed experiments that led to this
dissertationwastovisualizelanguageabilitydifferencesinhealthysubjects.Thecurrentsub‐chapter
will present previous research on language ability variation. In the following sub‐chapter, ‘Neural
CorrelatestoLanguage’,amoredetailedframeworkforlanguageabilitywillbeintroduced.
Languagediscussions often refer to the classical language areas ofBroca’s area in the left inferior
frontalgyrus(IFG)andWernicke’sareaintheleftposteriortemporallobe.Itisalsoknownthatother
functionalregionsareinvolvedinlanguageprocesses;thesewillbeexploredinthenextsub‐chapter.
It seems that differences in language performance can be – at least partly – explained by
differentiations in activation in Broca’s and Wernicke’s language areas, although their exact
contributionisnotyetclear.Studiesinvestigatinghighperformanceinwordfluencyhaveshownan
increase of left‐hemispheric IFG activation for high performance (Wood et al., 2001), but also no
difference at all (Dräger et al., 2004). When semantic tasks are studied, increased activation of
posteriortemporalandparietalregionsisshownforhighperformance(Boothetal.,2003;Meyleret
al;2007;Weberetal.,2006).
However, anopposingviewemerges froman increasingnumberofworks revealinga relationship
betweenreadingandsentencecomprehensionanddecreasedactivationinlefthemisphericlanguage
areas (Reichle et al., 2000; Prat et al., 2007; 2011, Prat & Just, 2011). The mechanism behind this
activationreductionisthoughttobeamoreefficientneuralfunctioning.Efficacyinrecruitingneural
regions or pathways enables a person to re‐attribute cognitive resources guided by task demand.
Thus,apersonskilledinlanguagemayusehisorherbraininamoreoptimalwayforthepresented
task.Furthermore,thereisevidenceofaspecificroleoftheright‐hemispherichomologuesofBroca’s
andWernicke’sareainhighlanguageperformance.Manyoftheresultspresentedinthepapersthat
are included in this dissertation point also to a right‐hemispheric contribution to high language
ability.Ifpeoplewithahighlanguageabilityrecruitadditionallanguage‐supportingareas,thismay
indicatethatahighadaptabilityofneuralresourcesisanexplanatorymechanismforlanguageability
differences. Research supporting the theories of neural adaptability and neural efficiency as
1.INTRODUCTION
3
explicatory for high language ability will be presented in the sub‐chapter ‘Intelligencemodels for
LanguageAbility’
1.1.2 Language Dysfunctions
The introduction started out by stating that knowledge of language ability will lead to an
understanding of language disability. PAPER IV presents a group of peoplewith epilepsy showing
subtlelanguagedisabilities,andcomparesthemwithhealthysubjectsperformingonanormallevel.
Thereversestatementtotheoneaboveisalsotrue;uponinvestigatinglanguagedisabilities,amodel
for language abilities canbe created.Muchof our knowledge about the language systemhasbeen
gained from lesion studies notably those on left‐hemispheric lesioned patients showing word
productionproblems,aspresentedalittlelaterinthissection.
Language impairment can have a variety of underlying causes; impaired language functioning,
cognitive ability, or sensory/motoric abilities, or lack of training or exposure to language. A
disruption in any component of language production or comprehension in the language model1
evidentlywillresultinadisruptionoflanguageability.Sincethestudiesincludedinthisdissertation
measurewordgenerationandsentencereading,thissectiondiscussesreadingimpairment(dyslexia)
andproductionproblems.
Developmental dyslexia is characterized by various neurological differences throughout the brain,
probably caused by anomalies during the development of language systems in the brain (Catts &
Kamhi, 2005; Démonet et al., 2005). It has been suggested that this type of dyslexia is related to
abnormaldominancepatternsor abnormaldevelopmentof dominance (Heimet al., 2010), but the
causesarethoughprobablymultipleandmorecomplex(Crystal2010).Acquireddyslexiacanoccur
afteralesioninoneoutofvariousbrainregions(Priceetal.,2003).Functionalimagingstudiesonthe
neurological differences between peoplewith dyslexia and normal performers show a diminished
activation in temporal and parietal regions (Salmelin et al., 1996; Shaywitz et al., 1998), and an
increaseininferiorfrontalactivation(Shaywitzetal.,1998).Boththepresenceofexpectedactivation
and the absence of unexpected activation in the right hemisphere have been observed to act as
distinguishersofpeoplewithdyslexiafrompeoplewithoutreadingimpairment(Paulesuetal.,1996;
Simosetal.,2000).
Word production problems are often not development‐related but result from lesions in the
language‐dominanthemisphere.Problemswithwordfluencyareseeninpeoplewithdementiaand
withlefttemporallobeepilepsy(Ruffetal.,1997).Namedafterthelocationofbraindamage,aphasia1e.g.thespacestationmodelpresentedinthefollowingsub‐chapter‘BrainFunctioning’
1.INTRODUCTION
4
can be classified as Broca’s aphasia, Wernicke’s aphasia or global aphasia – the latter being a
combination of Broca’s and Wernicke’s aphasia. It is now known that in Broca’s aphasia, brain
regionsposteriortoBroca’sareaareoftendamaged;andthat inWernicke’saphasiathelocationof
damage can vary (Crystal 2010). Broca’s aphasia results in deficits in expressive abilities and is
characterized by non‐fluent speech which is grammatically incorrect. Wernicke’s aphasia occurs
when receptive systems are damaged and results in both comprehension problems and problems
producing intelligible speech, even though it appears to be fluent. Furthermore, word retrieval
problemsareacommondeficiency(Crystal2010).
Studies on language disabilities can help us to find regions of interest for the investigation of
language abilities. Lesion studies that have led to an understanding of language disabilities have
shown that disruption of language functioning in the language‐dominant hemisphere has a much
higherimpactthanadisruptioninthenon‐dominanthemisphere.Thus,thelanguagefunctionsinthe
non‐dominant hemisphere may not be compulsory for language production, but may support
complexprocessing.
1.2 Neural Correlates to Language
1.2.1 Language Models
There aremany possible theoreticalmodels to describe the complex structure of language. Often,
these models use similar distinctions between word forms, word structure, word meaning and
understanding of text or speech. In other words, many models describe language as a process
defining the range of linguistic information from small building blocks to complex meaningful
communication. To understand language in the context of this dissertation, a useful model is the
spacestationmodelaspresentedbyCrystal(2010),andrepresentedinFigure1.
This model describes an interactive framework integrating the components of language that are
investigated in the papers included in this dissertation. The different components are: phonetics
(pronunciation attributes) and phonology (sounds that convey different meanings), morphology
(word structure) and syntax (sentence structure), semantics (meaningful content) and pragmatics
(discourseinformation).Theconnectionbetweenthesecomponentsisnotuni‐directional,butrather
interconnected as represented in the space station model. This is consistent with the neural
organization of language,where both top‐down and bottom‐up processes can be observed during
languageprocesses(Friederici2012).
1.INTRODUCTION
5
Figure1. Representation of the Space Station Language Model. The linguistic levels presented in the circles are interconnected, indicating free exchange of linguistic information between levels; thus all information is available at once for an external researcher. Figure adapted from Crystal (2010).
Measures of language ability preferably test formany linguistic components, including production
andperceptionoflanguage,andhaveahighenoughdifficultyleveltomeasurevariabilityinlanguage
skills. On the other hand, the total test duration should be kept to aminimum as to impose only
minimallyon theparticipants, especiallyon thosewith cognitivedisabilities.The testsused inour
studies, (see alsoMethods section for their description), show two approaches towards this goal.
First;establishedtestssuchastheBostonNamingTest(Kaplanetal.,1983)orwordfluencytests–
testingwordretrievalandwordproductionskills–areusedinmanyresearchstudiesthatdescribe
theneuralmechanisms that liebehind.Moreover, these tests areeasily translated to themagnetic
resonancescannerenvironmentwithoutmuchadapting.However,bothtasksareveryfocused;they
do not test for the full spectrum of language ability. Other tests, such as comprehensive reading,
investigate language perception and comprehension and could be translated to the scanner
environmentwithsomemodification.Asecondapproachistogathermultiplelanguageabilitytests
inabattery,suchastheAssessmentofSubtleLanguageDeficitsorBeSStest(Laaksoetal.,2000).This
relatively new complex language ability test is not yet established, but can detect subtle language
dysfunctionswithoutshowingaceilingeffect(astheresultsofourpaperswillshow).Moreover,this
isacompacttest,sothatlanguageabilitycanbeassessedquicklywithouttoomuchimposingonthe
1.INTRODUCTION
6
concentration skills of people with language dysfunctions (such as the people with generalized
epilepsyfromourPAPERIV).However,thistestislesspracticalinascannerenvironment.
NeurologicalmodelsareoftenbasedontheclassicalWernicke‐Geschwindmodel(Geschwind1965),
which describes the neurological dissociation between language production/speech attributed to
Broca’sarea,andlanguagesemanticcomprehension(semantics)attributedtoWernicke’sarea.Many
laterstudieshaveshownthat thisdescription is insufficient,as itdoesnot take intoaccountother
functionalareas,nordoesitdescribeaccuratelythepreciseboundariesoflinguisticfunctionalareas
(Price2000;2012;Démonetetal.,2005;Smitsetal.,2006).
Anoverviewofthesegregationinleft‐hemisphericlanguageareasisgiveninFigure2.Forinstance,
Broca’sareacontainsregionsinvolvedinsemanticsaswellas insyntaxprocessing(cf.Price2012).
Interestingly, although language studies often focus on the language‐dominant left hemisphere
(Vigneauetal.,2006),therighthemisphereoftenshowsasimilaractivationpattern(Démonetetal.,
2005).Nevertheless,aspectsofneuralcorrelatestotheWernicke‐Geschwindmodelaresupportedby
recentlesionstudiesinvestigatingaphasia(Yangetal.,2008)andbyfunctionalimagingstudies(Price
2000;Bookheimer2002).Therefore,Broca’s andWernicke’s area areusedas regionsof interest in
severalofouranalyses, in combinationwithother regions thatwere found in relation to semantic
andwordfluencytasks.
When using the labels of Broca’s andWernicke’s areas, it is important to define their extent; the
definition of Wernicke’s area in particular can vary from including only the posterior superior
temporalgyrus to the inclusionof largepartsof theparietaland temporal cortex.Throughout this
dissertation, includingall articles, thedefinitionused is as follows:Broca’s area comprises the left
IFG; specifically Brodmann areas (BA) 44 and 45. Wernicke’s area comprises the left posterior
superiortemporalgyrus(BA22)andtheposteriorpartofBA21,aswellastheposteriorperisylvian2
regionwhichconsistsoftheleftangulargyrusandthesupramarginalgyrus(BA39&inferiorBA40).
The right‐hemispheric counterparts of these areas are referred to as Broca’s andWernicke’s area
homologues. Language production and perception are by no means controlled solely by these
regions3. The regions important for language will be discussed in the following sections which
introduceanoverviewofactivationrelatedtosemanticandwordfluencytasks.Sincethetopicofthis
dissertationislanguageability,neuralprocessesnotdirectlyrelatedtolanguagearenotintroduced
here.
2PerisylvianindicatestheregionaroundtheSylvianfissure.Thisfissuredividesthefrontalandparietallobulesfromthetemporallobe.
3Anexampleisgivenby(Dronkersetal.,2007),whofoundthatthepatientsofPaulBroca–whosebrainsevidencedthetheoryofspeechproductionlocatedinleftIFG–hadlesionsthatwerespreadoverawiderregionthanjustBroca’sarea.
1.INTRODUCTION
7
Figure 2. Finite overview (based on imaging studies by Cathy Price) of the segregation of functional languagerelated areas in the left hemisphere. The colored areas each refer to different tasks, either differing in modality (auditory/visual) or in linguistic component. Figure reprinted with permission. See Price (2012) for details.
1.INTRODUCTION
8
1.2.2 Semantics
Our studies have used semantic sentence reading fMRI tasks, either requiring completion of
sentences or reading of congruent/incongruent sentences. Semantic tasks such as reading (Price
2000), and sentence and story comprehension (Sakai et al., 2001; Kaan & Swaab, 2002) typically
activateBroca’sandWernicke’sareainthelefthemisphere(Priceetal.,2003;overviewinBinderet
al., 2009). In the left IFG, BA 47 plays also a role in semantic processing (Dapretto&Bookheimer,
1999; Bookheimer 2002). Furthermore, the anterior temporal cortex and the fusiform gyrus are
involvedinsemanticprocessing(Priceetal.,2003;overviewinPrice2012).Activationintheparietal
perisylvianregionhasbeenshowntocorrelatewithlinguisticcomplexityinsentences(Carpenteret
al., 1999) and semantic associating (Price 2000). Semantic processing often also activates right‐
hemisphericIFGandtemporallobe(Bookheimer2002),whichwillbediscussedinthesection‘Right‐
HemisphericInfluences’.
1.2.3 Word Fluency
Wordgeneration(or:word fluency) tasksare frequentlyused todetermine language lateralization
byfMRI(Cuenodetal.,1995;Hertz‐Pannieretal.,1997).Thegenerationofwordsevokesactivationin
theleftmiddleandinferiorfrontalgyrus(Fuetal.,2002;Costafredaetal.,2006),withaparticularly
important role for the pars opercularis (Price 2000). Furthermore is activation observed in the
inferiortemporalcortexandintheadjacentfusiformarea(Price2000),andintheanteriorcingulate
cortex (Fu et al., 2002)The sub‐regions in the IFGhave specific roles and the activationpattern is
dependentonthenatureofthefluencytask(Heimetal.,2009).
1.2.4 Right‐Hemispheric Influences
Mostlanguagetasksevokeactivationinbilateralfrontal,temporalorparietalareas;thespecificrole
ofright‐hemispheric languageareasisofteninterpretedasabstract linguistic functioning.Although
lesionstudiesoftenindicatethattheright‐hemisphereisnotindispensableforlanguageproduction,
neuroimaging studies show that the right hemisphere plays an important and often distinct role,
somethingwefoundevidenceofinourstudiesaswell.Vigneauandcolleagues(2011)discussintheir
meta‐analysistherighthemisphereinrelationtolanguageprocessing.Theyconcludethattheright‐
hemisphericIFGseemstohavenoaccesstophonemicrepresentations,unliketheleftIFG.Activation
in the right IFG is observed during processing of metaphors (Schmidt & Seger, 2009) and the
perceptionofprosody(Buchananetal.,2000).Furthermore,therightIFGisactivewheninformation
is conflicting during complex language tasks; this is related to figurative language and increasing
1.INTRODUCTION
9
ambiguity(Bookheimer2002;Snijdersetal.,2009).BookheimersuggeststhattheroleoftherightIFG
mightbetohelpmakingdecisionsbasedonlinguisticinformation.
The right hemisphere is also important for understanding and integrating spoken and written
information(Bookheimer2002).Inparticular,theunderstandingofcontextprocessingorpragmatics
–whichisnecessaryforinterpretingforexampleambiguousoremotionallyloadedinformation–is
attributedtotherighttemporallobe(Vigneauetal.,2011).Examplesofrighttemporallobeactivation
areseeninstudiesinvestigatingtheinterpretationofprosody(Vigneauetal.,2011),theintegration
of semantic information (Caplan&Dapretto, 2001), or the processing ofmetaphors (Bottini et al.,
1994;Mashaletal.,2005;Ahrensetal.,2007).Theneuralactivationresultingfromtheprocessingof
metaphors ispossiblyrelatedtothemetaphorsbeingperceivedasnonsensicalorcontainingnovel
semantic information (Mashal et al., 2009). The right hemisphere is thus involved in pragmatic
processingonameta‐syntacticlevel(Mitchell&Crow,2005).
1.2.5 Laterality
The dominance of a hemisphere in language processing can be quantified as the degree of
lateralization. A non‐typical degree of lateralization has been attributed to both language abilities
and disabilities (cf. the first section ‘Language Abilities’). Knecht and colleagues (2000) tested 188
healthyright‐handedadultsforlanguagelateralizationinthebrainwithawordgenerationfMRItask.
Thistaskhasbeenwidelyreportedtobeapowerfulandeffectiveparadigmforgeneratinglanguage
production (Neils‐Strunjas1998).Language lateralization study resultshave indicated that there is
no difference in language lateralization ratios betweenmales and females. Furthermore, a left‐ to
right‐hemispheric dominance ratio of 13 to 1 was established (Knecht et al., 2000). Besides fMRI,
dichotic listening is an alternative and feasible non‐invasive method to test for language
lateralization (Hugdahl 2011). The dichotic listening method is based on the notion that bi‐aural
auditory stimuli travelmore easily to the contralateral rather than ipsilateral hemisphere, due to
more extensive contralateral than ipsilateral pathways from the ear to the auditory cortex. Also,
there is a blocking of ipsilateral pathways during conflicting input. After travelling to the
contralateralcortex,theauditivesignalsareprocessedmoreautomaticallyinthehemispherethatis
dominantforlanguage.Ergo,thelanguage‐dominanthemispherepresumablyresidescontralateralto
theearthatprocessesmorestimuliduringbi‐auralstimulation(Kimura,2011).
1.INTRODUCTION
10
Differences between methods to test for laterality are discussed by Abou‐Khalil (2007), who
concluded that fMRIwasoneof themost realizable techniques4.The clearadvantageof fMRIover
dichotic listening is that fMRI can localize activation. Nonetheless, dichotic listening is superior in
practicality,bothintermsofcostsandofconvenience.Itisalsoimportanttorealizethatthelaterality
measurementsobtainedby fMRIareverymuchdependentonwhich language task ischosen.Both
word fluency and sentence comprehension seem to be indicative of determining language
lateralization(Niskanenetal.,2012).
Besideseardominance,handdominanceisalsoseentohaveadirectconnectiontothecontralateral
hemispheric.Right‐handednessishighlycorrelatedwithleft‐hemisphericlanguagedominance(in94
– 96 % of right‐handers). In left‐handers, it is slightly more common to have right‐hemispheric
dominance,yet78%oftheleft‐handedpopulationisalsoleftdominantforlanguage(Szaflarskietal.,
2002).
Languagelateralizationisthoughttocorrelatewithdifferencesingraymatterbetweenhemispheres,
and when the cortex is damaged, language lateralization for expressive language functions can
change(Leeetal.,2008).Josseandcolleagues(2009)investigatedhowgraymatterdifferencescould
predictlanguagelateralization,andshowedthatwhengraymatterisanalyzedwithavoxel‐by‐voxel
method, structural asymmetry correlated well with language lateralization. However, these
correlations were lost when global lateralization was compared with regional gray matter
asymmetries.Nowadays,locallateralizationisofinterestandmanyresearchersprefertoinvestigate
the lateralizationofseparateregions(Seghieretal.,2011b).Astrong lateralizationofcognitionhas
beenlinkedtohighcognitiveperformance(Güntürkünetal.,2000).Recently,anopposingviewhas
emerged,namelythattheoptimaldegreeoflateralizationforhighcognitiveperformancewassmall.
Inotherwords;ahigherdegreeofbilateralitymightbemorefavorableforperformance(Hirnsteinet
al.,2010).
1.2.6 Anti‐correlated Brain Activation
In PAPER IVwe examine activation that is correlated negatively with language tasks; this can be
labeledasdeactivation.Deactivationisthedecreaseofsignalinregionsthatareactivatedduringrest
butnotduringtaskcondition,thusfunctionsintheseregionsarethoughttobesuppressed.Someof
theseregionsformanetworkthatisconsistentlyactivatedduringrestanddeactivatedduringtasks;
this is called the Default Mode Network (DMN). DMN activation is associated with ‘free thinking’
4cf.(Medinaetal.,2007),whopresentsanoverviewofthereliabilityoffMRI‐obtainedlateralitymeasurement.
1.INTRODUCTION
11
processes – often referred to as thinking about the day, shopping lists, and what’s for dinner –
therefore the suppressionofDMNactivationenablesaperson toallocatemorecognitivepower to
thetask.Heterogeneityoftheanti‐correlationduringasemantictaskinthedifferentregionsofthe
DMNistobeexpected(Seghier&Price,2012).AdifferenceinsuppressionoftheDMNbetweenthe
taskandcontrolconditioncanalsobeexpected,dependingonhowengagingthecontrolconditionis.
Deactivationpatternsmightbe justasnecessaryasactivationpatternstoexplainbrainfunctioning
(Binder2012).
1.3 Intelligence models for Language Ability
1.3.1 Relation Language Ability and Intelligence
There is an, although limited, correlation between language ability and intelligence (e.g. word
fluency:Haier et al., 1992;Roca et al., 2010; semantics: Prat et al., 2007). Some intelligencemodels
describe processes that can be applied to language ability as well, and help to understand the
differences in language performance observed in previous and our current work. Intelligence is
attributedtoaparieto‐frontalnetworkthatincludesseveralregionsandconnectionsthatareshared
with language processing functions. This network is described in the Parieto‐Frontal Integration
Theory of intelligence (Jung & Haier, 2007). A second intelligence theory is the neural efficiency
hypothesisofintelligence(Haieretal.,1992).Thistheorydescribeshowwell‐developedskillscanbe
characterizedbyamoreeffectivemannerofprocessing in thebrain.Thus;high‐skilled individuals
willshowadecreasedbrainactivationcomparedwithlower‐skilledpersons.Thisreasoningcanbe
applied to language skills as well, as will be put forward in the next section. Lastly, neural
adaptabilityisdiscussed;thisisatraitobservedinhigh‐skilledindividuals.Thesetheoriestogether
mayexplainthefunctionalactivationpatternsobservedinhighperformers(e.g.Prat2011;Langeret
al.,2012).
1.3.2 Intelligence Models
TheParietoFrontal Integration Theory (PFIT) of intelligenceisasummationofregionsinanetwork
foundtoshowactivationdependentonintelligencelevel(Jung&Haier,2007).Ithasbeenknownthat
neuralcorrelatestohighintelligencearelocatedintheprefrontalcortex(Thompsonetal.,2001),and
thatincreasedgrayandwhitematterisobservedinbothfrontalandparietalregionsincorrelation
1.INTRODUCTION
12
with high intelligence (Neubauer & Fink, 2009). The P‐FIT of intelligence states that it takes a
network of interactive regions to provide high abilities. The functions are divided within this
networkfromcaudallylocatedrulegeneratingprocesses,torostralfunctionssuchlikeselecting,and
testingofanswers.Thenetworkincludesthelanguageprocessingareasintheposteriorperisylvian
region.
TheNeural efficiency hypothesis of intelligencestatesthatnetworksforcognitivefunctionsworkina
moreefficientmannerinintelligentbrains.Therefore, intelligentbrainswillshowlessactivationin
task‐specificnetworksduringimagingstudies.Haierandcolleagues(1992)statethatthemechanism
behind neural efficiencymight be deactivation of irrelevant brain areas, or amore specific use of
task‐related areas. Theneural efficiencyhypothesis of intelligence appears to be limited to frontal
regions, and conditional on task aswell as task‐difficulty (Neubauer& Fink, 2009). Predominantly
frontal activation patterns in high performers show efficient behavior during easy to moderately
difficult tasks. Activation in the frontal region has previously been shown to decrease upon
automationofprocesses(Ramseyetal.,2004).Whendemandsgethigh, this isno longertrue;high
performersthenrecruitmorebrainregionstosolvethetask.Thehighintelligentindividualsmight
havemoreadaptivestrategiesthanlowperformersandcan–dependingontaskdemand–eitheruse
theirbrainefficientlyorcallinthehelpofsupportingbrainregions(Doppelmayretal.,2005).Neural
efficiency patterns have been observed in high capacity readers during sentence comprehension
(Maxwelletal.,1974;Pratetal.,2007;Prat&Just,2011).
The additional recruitment of supporting neural resources whenever a task is difficult may be
described as Neural adaptability (Prat et al., 2007). It is hypothesized that individuals highly
proficientinlanguageshowmoreneuraladaptabilitycomparedwithpeoplewithlowerproficiency.
Thiscanbeobservedasactivationinlanguage‐relatedregions,eitherinmainlanguageregionsorin
additionalsupportiveregions.
Evidently,thetheoriesaboveoutlineavariedpatternoftherelationbetweenhighperformanceand
neural activation or deactivation. This pattern is dependent on task, task demands and functional
region.IntheDiscussiontheconsiderationsconcerningtheinterpretationofbrainactivationwillbe
furtherexplored.
1.INTRODUCTION
13
1.4 Aims
Language ability in healthy adults was expected to be visualized as amodulation of activation in
language‐relatedregions,withrespecttothelevelofactivation,butalsothedegreeoflateralization
betweenhemispheres.
PAPER I aimed to determine regional lateralization of semantic language functions in relation to
performance in tests of language ability. It was expected to find laterality differences related to
performance in the IFG and posterior temporal lobe, for both fMRI‐obtained laterality and for
dichoticlistening.
PAPER II aimed to find the neural correlates to language ability throughout thewhole brain. The
expectationwastofindspecificregionsintherightIFGandposteriortemporallobeactivatedduring
fromasemantictaskthatwererelatedtohighperformanceintestsoflanguageability.Furthermore,
brainactivationduringwordfluencywasinvestigatedandcomparedwithsemanticresults,inorder
tofindwhetherthereweresimilaritiesinactivationpatternsrelatedtohighlanguageability.
PAPERIIIaimedtoreproducethefindingsofPAPERIandPAPERIIinanewstudypopulation.Thus,
activation during semantic and word fluency tasks that emerged in the right‐hemispheric
homologues of Broca’s and Wernicke’s area were investigated for their correlation with high
performance in tests of language ability. In addition, activation related to task demand was
investigated. Brain activation patterns related to high performancewere expected to show neural
efficiency for low‐demand tasks in the IFG. Furthermore, high language abilitywas expected tobe
characterizedbyneuraladaptability;i.e.increasedright‐hemisphericcontributions.
PAPERIVaimedtoinvestigatelanguagedeficitsinpeoplewithgeneralizedepilepsy.Thisgroupwas
alsoexpectedtoshowaninadequatesuppressionofthedefaultmodenetworkthatisnormally
highlyanti‐correlatedwiththetask.
14
Strength and courage overrides The privileged and weary eyes Of river poet search naiveté
Pick up here and chase the ride The river empties to the tide All of this is coming your way
‘FindtheRiver’–BillBerry,MichaelStipe,PeterBuck,MichaelMills
15
2 METHODS
2.1 Neurolinguistic Measures
2.1.1 Tests of Language Ability
InPAPERIandPAPERII,fourteststomeasurelanguageabilitywereused:FASandBNTmeasured
wordretrievalabilities,andBeSSandReadmeasuredlanguagecomprehensionabilities.InPAPERIII
andIV,onlyBeSSandFASwereused.
FAS is a phonemicword generation test inwhichparticipants are cuedwith a letter (F,A, S), and
havetogenerateasmanywordsaspossible,startingwiththecueletter.Totalscoreisthenumberof
generatedwordsforallthreeletters.BNTistheestablishedBostonNamingTest.Duringthetest,the
participantispresentedwith60picturesthathavetobenamed.
BeSS(“BedömningavSubtilaSpråkstörningar”orAssessmentofSubtleLanguageDeficits)testsfor
theuseofcomplexlanguagebymeansofsevensubtasks(Laaksoetal.,2000).Thosesubtasksare:
REP repetitionoflongsentences(9‐16words)
CON sentenceconstruction(fromthreewords,withgivencontext,undertimepressure)
INF inferentialreasoning(basedonareadtext)
COM comprehensionofcomplexembeddedsentences
GAR comprehensionofgarden‐pathorambiguoussentences
MET comprehensionofmetaphors
VOC vocabulary–worddefinition
2.METHODS
16
Maximumscorewas210points.
TheReadtestisselectedfromaSwedishexamforuniversitystudents.Participantshadtoreadthree
textsandanswerfourquestionsoneachtext.Thetotalscorewasthenumberofcorrectlyanswered
questions.
2.1.2 Dichotic Listening
DichoticListeningscoreswereacquiredinPAPERIwiththeuseofaversionoftheBergenDichotic
Listening Test (Hugdahl 1995),which is a consonant‐vowel test. Auditive stimuli created from the
combinationofastopconsonantandthevowel‘a’(e.g.ba–ga–pa)werepresentedbi‐aurallytothe
participants.Dependingontheinstructions,theparticipantshadtoreportthestimuli;eitherheardin
the leftortherightear; inbothears;orthemostsalientstimulus.Theresultswerecalculatedasa
rightearadvantage;subtractingcorrectresponsesperceivedbytheleftearfromthoseheardinthe
right ear, then dividing this figure by the number of total correct responses. A high right ear
advantagemeantthatthesubjectwasbetteratreproducingstimuliheardintherightear,compared
with the left ear. This was interpreted as a lateralization index for language; a high right ear
advantagemeantstrongleft‐hemisphericlateralization.
2.1.3 fMRI Language Paradigms
ThewordgenerationtaskWORGEfromPAPERIIwasasdescribedin(Engströmetal.,2010)butwith
moderationofthecontrolcondition.TheparticipantswerecuedwithalettertakenfromtheSwedish
alphabet,excludingC,Q,W,X,Y,Z,Å,Ä,andÖ.Theywereinstructedtogeneratewordswiththecued
letter,asmanyaspossiblewithinthegiventimeof5s.Thecueletterswerevariedandpresentedin
blocks containing three to five letters, pseudorandomly ordered. The baseline or control task
consistedofpresentationofanasteriskalternatedwitharowofasterisks.
Theword generation taskWORD is described in PAPER III. Similarly toWORGE, a cue letterwas
presented,but this timethecue lettersweredivided into twodifficultycategories; ‘easy’ (frequent
starting letter in a Swedish word list) and ‘hard’ (infrequent starting letter). The letters were
presentedpercategoryinablockofsevenletters,alternatingwithcontrolblocks.Thecontrolblock
differedfromWORGEinthesensethatonlyoneasteriskwaspresentedeachtrial.
ThesentencecompletiontaskSENCOisdescribedinPAPERI.Thiswasaclozetask;theparticipant
hadtosilentlygeneratethemissinglastwordofasentence.Thesentenceswerepresentedinblocks,
2.METHODS
17
thepresentationdurationofasentencewas3sfollowedbydisplayofanasteriskfor2s.Thecontrol
conditionconsistedofasterisksmimickingashortsentence.
The congruent/incongruent sentence reading task SEN is described in PAPER III. The participants
were presented with blocks differing in difficulty level; either congruent (‘easy’ condition) or
incongruent(‘hard’condition)sentences,orcontrolblockscontainingarowofasterisksandarrows.
Theparticipantshad to judgewhether thesituationdescribed in thesentence tookplace insideor
outside.Duringthecontrolcondition,theparticipantshadtoreportinwhichdirectionthearrowwas
pointing.
2.1.4 Study Population
StudyAinvestigatedahealthyadultpopulationof18participants:ninefemalesandninemalesaged
21‐64 (mean age: 40). ForPAPER1, a subset of 14participants (seven females, sevenmales)were
investigated,aged21‐55(meanage:36.9).
StudyBinvestigatedtwogroups.First,ahealthyadultpopulationof27participants:14femalesand
13malesaged18‐35(meanage:25.5)wasinvestigated.TheanalysesfromPAPERIIIwereperformed
ondatafromthisgroup.ForPAPERIV;thehealthycontrolgroupwascomparedwithagroupof11
peoplewithgeneralizedepilepsy:sixfemalesandfivemales,withanagerangeof20‐35years(mean
age: 26.5). In both the healthy control group and in the groupof peoplewith generalized epilepsy
therewasaleft‐handedindividual.
AllparticipantshadSwedishastheirfirstlanguageandwerescreenedbymeansofaquestionnaire
on the absence of neurological, cognitive or psychiatric disorders andmagnetic resonance contra‐
indications.
2.1.5 Generalized Epilepsy
Thedifferent types of epilepsy can be classified according to etiology. This results in a distinction
between generalized epilepsies with genetically inherited origin, and focal epilepsies (Berg et al.,
2010;Poduri&Lowenstein,2011).Peoplewithgeneralizedepilepsy(GE)showawidespreadatypical
corticalactivity(Marinietal.,2003)andmayexperiencelanguageproblems(Chaixetal.,2006;Caplan
etal.,2009).GEisalsorelatedtoanabnormalconnectivityinthedefaultmodenetwork(McGilletal.,
2012).
2.METHODS
18
2.2 Functional MRI
2.2.1 Properties of Functional MRI
FunctionalMRI candetect susceptibility changes in theblood that arisedependingon the amount
oxygen that is present. Neurons that are activated exchange neurotransmitters, and this exchange
process consumes oxygen. This is overcompensated by transport of an abundance of oxygenated
blood5totheactivatedarea,theoxygenatedblooddiffersfromthesurroundingdeoxygenatedblood
inmagneticproperties.Thisprocessiscalledthebloodoxygenleveldependent(BOLD)responseand
ismeasured using susceptibility sensitivemagnetic resonance sequences6. Since changes in blood
flowareslow,thefMRIsignalhasalowtemporalaspect.Furthermore,themagnetizationdifference
isverysubtle,withalowsignal‐to‐noiseratio.Therefore,acommonapproachistorepeattheaction
orstimulusthatevokesthepatternofinterestmanytimes,andcalculatetheaverageoftheresponse.
The highest power is obtainedwhen stimuli are presented in blocks, and the blocks for different
conditions and the baseline are presented in an alternating sequence. To get ameasure of neural
activationperconditionineachspatialunit(i.e. voxel),astandardapproachistomodeltheexpected
BOLDresponsewiththegeneral linearmodel(GLM),whichisthenfittedtothedata.Thismodel is
time‐variant.AnequationfortheGLMisgivenasY=Xβ+ε,inwhichYisthedatarepresentedby
the design matrix X (the design matrix models aspects of the experiment such as conditions or
performance covariates) times the parameter estimates β (estimates for the data that explain as
much as possible). The ε is the residual error term. In our studies,we used statistical parametric
mapping(SPM)7tomodeltheGLMonourdata.AllourstudieswerecollectedwithaPhilipsAchieva
1.5 tesla scanner, using gradient‐echo planar imaging sequences. The obtained images were all
normalizedtoastandardbrainwithcoordinatesinMontrealNeurologicalInstitute(MNI)space.
Theactivationpattern foreachconditioncanbequantifiedbysubtracting thenumberofactivated
voxels in one condition from another. Most often are task conditions compared to a baseline
condition.Subsequently,thesignificanceofthefirst‐levelanalysisresults(testingindividuals)canbe
testedby,forexample,t‐tests.Thus,testingforactivationrelatedtoacertainconditioncanbedone
bysubtractingbaselineactivationfromactivationduringthecondition.Testingfordeactivationcan
5Tobeprecise;itisthehemoglobinproteinthattransportsoxygenintheblood.Hencetheterm‘hemodynamicresponsefunction’thatisusedtodescribetheovercompensationofoxygentransporttoactiveneurons.
6Paramagneticdeoxygenatedblooddisturbsthemagneticresonancesignal,byhasteningthedephasingofprotonsthatemitthissignal.Iftheamountofoxygenatedbloodincreases,themeasuredsignalincreasesaswell.
7www.fil.ion.ucl.ac.uk/spm/software
2.METHODS
19
bedonebysubtractingconditionactivation frombaselineactivation.Theresultingstatisticalmaps
canbeenteredintoasecond‐levelanalysistotestongrouplevel.Twogroupscanbecomparedwith
a two‐sample t‐test, or if data fluctuation depending on individual performance scores is
investigated,amultipleregressionapproachcanbetaken.Forourmultipleregressionanalysis,we
correctedforagebymodelingageasacovariateandtestedforindividualperformancedifferencesby
modelingperformancescoreasacovariateofinterest.
2.2.2 Region of Interest Analysis
Ifthelocationofexpectedactivationisreasonablycertain,andananalysisofthewholebrainisnot
required, the analysis can be restricted to regions of interest (ROIs). In our studies, ROIs were
obtained indifferentways,a posteriorianda priori, toanswerdifferentquestions. InPAPERII, the
whole‐brain analysis results were used to guide placement of small spherical ROIs at significant
peaksof activation.Parameter estimateswere calculated fromanROI analysis and then tested for
their correlation strength with performance. To report the strength of these correlations as a
measure of significancewould give an inflatedmeasurement, since this is a second correlation of
fMRI datawith performance scores. Therefore, ourposthoc resultsweremerely used to filter out
low‐significantcorrelationsfromtheregionsthatweresignificantinthemultipleregressionanalysis
with a p‐value threshold of 0.01, corrected for multiple measurements by means of the false
discoveryrate
In StudyB that led toPAPER III andPAPER IV,wehad an expectationofwhich regionswouldbe
active. Therefore, we were able to restrict our statistical tests to include only the voxels in the
predicted regionsand thus correct the significance calculation for the small volumesused.For the
unpublished results related to the healthy population in Study B that are discussed in this
dissertation,weusedthefollowingROIs:theIFGparsopercularis(BA44),IFGparstriangularis(BA
45), IFGparsorbitalis (BA47), themiddleandsuperior temporalgyri–describedas the ‘posterior
temporallobe’,andtheangulargyrus(BA39).Here,onlyresultssignificantatp<0.05werereported,
andthefamily‐wiseerror(FWE)ratewasusedtocorrectformultiplemeasurements.
InPAPERIandPAPERIII,weusedROIsforthelateralityindexanalysisaswell.Intheseanalyses,the
bilateralROIswerecreatedtobemirror‐symmetricalsothattheywereequalinnumberofvoxels.In
PAPER I, the used ROIs were: the IFG including the pars opercularis and pars triangularis, the
temporal lobe including the middle and superior temporal gyrus – this ROI was divided into the
anteriortemporallobeandposteriortemporallobe–,theanteriorcingulatecortex,andthesuperior
parietallobe.TheROIsusedinthelateralityindexanalysisPAPERIIIwerebasedonresultsofPAPER
IandPAPERII; IFG including theparsopercularis,pars triangularisandparsorbitalis; theangular
2.METHODS
20
gyrus;andtheposterior temporal lobe including themiddleandsuperior temporalgyri (excluding
thetemporalpole).ThislastROIislessrestrictivethanthe‘posteriortemporallobe’ROIfromPAPER
I.
TheROIsusedforanalysisofthedefaultmodenetworkinPAPERIVwerealsobilateral:themedial
prefrontal cortex, anterior cingulate cortex, posterior cingulate cortex, precuneus, inferior parietal
lobe,middletemporalgyrus,superiortemporalgyrus,hippocampus,andparahippocampus.
2.2.3 Laterality Index Analysis
Often, a laterality index (LI) is defined as the result of a subtraction of activated voxels in the left
hemisphere of the brain from the activated voxels in the right hemisphere. In our studies, the
laterality index analysis is calculated not for thewhole brain but for separate regions. Also, since
calculation by this simple subtraction makes an LI sensitive to choice of threshold, we used a
weightedLIthatwasderivedfromvaryingthresholds(seePAPERIfordetails).
21
22
Half of the time we’re gone but we don’t know where And we don’t know where
Here I am
‘OnlyLivingBoyinNewYork’–PaulSimon
23
3 RESULTS
Performancedifferencesinhealthysubjectswereexploredinourfirststudy;StudyA.Wetestedthe
fMRI tasks sentence completion SENCO and word generation WORGE in relation to performance
measurements in tests of language ability. This led to the publication of PAPER I and PAPER II.
Guidedbyourfindings,weexaminedanewstudypopulationinStudyBforperformancedifferences,
andfurthermorefordifficulty‐relatedactivation.ThefMRIacquisitioninStudyBwasdoneontasks
investigating sentence reading of congruent and incongruent sentences (SEN) and, again, word
generation (WORD); this is presented in PAPER III and PAPER IV. All performance scores were
obtainedfromtestsoflanguageabilityperformedoff‐line,i.e. notduringthefMRIscanningsession.
The ‘Results’ chapter is divided into four sections. First, the multiple regression analysis relating
performancetobrainactivationduringtasksoflanguageabilityfromPAPERIwillbedescribed.The
secondsub‐chapterpresentshowlanguageabilityischaracterizedbylateralitydifferencesbetween
regionsofinterestinbothhemispheres,aspresentedinPAPERIIandPAPERIII.Then,resultsfrom
PAPER IIIon theneuraldifferences related to taskdifficultyaredescribed.Lastly,our researchon
patternsinthedefaultmodenetworkthatareanti‐correlatedwithsentencereadingfromPAPERIV
is reported. The DMN deactivation is investigated both for healthy adults and people with
generalizedepilepsy,inrelationtoperformancedifferencesandtaskdifficulty.
3.RESULTS
24
3.1 Multiple Regression Analyses
PriortoPAPERIandPAPERII,theSwedishtestforcomplexlanguagefunctioningBeSShadnotbeen
usedtotestneuralcorrelatesrelatedtolanguageperformancedifferences.Moreover,mostliterature
onlanguageperformanceandbrainactivationwasbasedonnon‐Swedishpopulations.InPAPERII,
we therefore adapted anunconstrained,whole‐brain analysis approach.Wemeasuredhowneural
activation, related to sentence completion and word generation varied in relation to the off‐line
performancemeasures(FASandBNTforWORGE,BeSSandReadforSENCO).Thetypicalactivation
patternsforsentencereadingandwordfluencyinthewholegroupcanbeseeninFigure3(SENCO)
andFigure4(WORGE).
In PAPER II, we observed a mainly right‐hemispheric contribution to high language performance
duringourmultipleregressionanalysis(overviewinTableIofPAPERII).Thiscontributionwasmost
evidentfortheSENCOtaskwiththeBeSSperformancescoreasacovariateofinterest.Weobserved
increasedactivationintherightIFGparsorbitalis(BA47)andtherightmiddletemporalgyrus(BA
21) to correlatewith high performance in BeSS and Read. High Read performancewas related to
activation in several regions in the right lateral frontal lobe (dorsolateral prefrontal cortex) and
middletemporalgyrus;aclusterofactivationintheleftmiddletemporalgyruswasalsoobserved.In
addition, the right fusiform gyrus was increasingly activated in participants with high Read
performance.
The increased activation characterizing high performance was also observed for WORGE, where
word generation activation in the right IFG increased for participants with high BNT scores.
However,highFASscoresonlycorrelatedwithleftmedialfrontalgyrusactivation,andnotwithany
right‐hemisphericclustersorwithactivationinBroca’sorWernicke’sareas.
3.RESULTS
25
Figure3.Neural activation (redyellow) and deactivation (blue) during sentence reading on the SENCO fMRI task in a healthy participant group. The scale indicates the Zvalue of activation strength, the numbers indicate the z coordinate of each slice in the MNI coordinate system. L = left hemisphere, R = right hemisphere.
3.RESULTS
26
Figure4.Neural activation (redyellow) and deactivation (blue) during word fluency on the WORGE fMRI task in a healthy participant group. The scales indicate the Zvalue of activation strength, the numbers indicate the z coordinate of each slice in the MNI coordinate system. L = left hemisphere, R = right hemisphere.
3.RESULTS
27
The findings of performance‐dependent right‐hemispheric IFG, dorsolateral prefrontal cortex and
temporallobeactivation,regionsofinterestwerecreatedintheseareastotestagainwithamultiple
regressionanalysisofperformanceinfluencesonbrainactivationpatternsinanewstudypopulation
(Study B). Here, some unpublished results are discussed first. A multiple regression analysis of
activation in thepredefinedROIsshowedcorrelationsbetweenhighperformanceandactivation in
theleft,ratherthanintherighthemisphere.Activationintheleftposteriortemporallobeduringthe
hardconditionofSENcorrelatedwithhighBeSSperformance(PeakZ:4.89;p<0.05FWEcorrected;
MNIcoordinates: ‐40, ‐56,14)(Figure5, left).DuringthehardconditionofWORD,activation in the
leftangulargyruscorrelatedwithhighFASperformance(PeakZ:4.11;p<0.05FWEcorrected;MNI
coordinates:‐54,‐66,28)(Figure5,right).
Figure5. Brain rendering showing locus of activation (with peakvalue of activation in red) in the left hemisphere. Left: posterior temporal lobe activation during difficult sentence reading (SEN task) correlated with high BeSS performance. Right: angular gyrus activation during word fluency (WORD task) correlated with high FAS performance.
3.2 Laterality Analyses
Wetestedhowlateralityinregionsofinterestvariedwithperformancescores.Therefore,weuseda
threshold‐independentapproachtocalculatealateralityindexinROIsinbothstudypopulations;in
PAPER I fromStudyAandPAPER III fromStudyB.TheROIs inBroca’sandWernicke’sarea from
PAPERIwerere‐usedinPAPERIII,withtheadditionofanROIdefiningtheangulargyrus.
PAPER I investigatedonly sentence completion, and showed that the rightposterior temporalROI
was more active than the left when high Read scores were achieved. High BeSS scores were
3.RESULTS
28
correlatedwithmoreactivationintherightthanintheleftIFG.Theseresultswereconfirmedbythe
resultsofthedichoticlisteninginvestigation.Thedichoticlisteningtestelicitedadecreasedrightear
advantageduringbi‐auralstimulusperceptionincorrelationwithhighscoresontheRead,BeSS,FAS
and BNT tests. This high language performance correlation was found for free‐report (stimuli
reported fromeitherorbothears) and fordirected‐report‐left (stimuli reported from the left ear)
conditions. The directed‐report‐left condition also correlated with the fMRI LI in the posterior
temporal lobe; participants that showed a right‐hemispheric or bilateral language activation also
couldattendbetterto,andgivemoreresponsesheardwiththeleftear.
LI analysis of the sentence reading task in PAPER III reproduced this result in a new study
population. InPAPERIII,we foundthat therightposterior temporalROIwasmoreactive thanthe
left in correlationwith highBeSS performance scores.We also applied an LI analysis to theword
generation data in PAPER III.We now observed that the LI in the IFG correlated negatively with
performanceinFAS.Thisnegativecorrelationwascharacterizedasadecreasedleft‐hemisphericIFG
activation in relationwith high fluency performance rather than an increase in right‐hemispheric
activation(seeFigure2AinPAPERIII).
3.3 Task Difficulty Modulation
InPAPERIII,wemodified fMRItaskdifficulty; thiswasdonebytakingthecontrastof thecomplex
versusthesimplecondition(Hard>Easycontrasts).Wewishedtoinvestigateif,andhow,difficulty‐
related activation would differ from performance‐related modulations of activation patterns. We
showed that the activation patterns related to the increased complexity of incongruent sentence
readingwerelocatedinthebilateralIFG.Anincreaseindifficultyofwordgenerationdidnotrelateto
achangeinbrainactivationpatterns.Nointeractionsbetweentaskdifficultyandperformancewere
observed.
TheanalysisofhealthyadultsinPAPERIVshowedthatthedeactivationpatternsintheDMNrelated
to the complex incongruent sentence reading conditionwereaugmented in thepregenual anterior
cingulatecortexborderingthemedialfrontalcortex.
3.RESULTS
29
3.4 Language Dysfunctions in Epilepsy
Agroupofpeoplewithgeneralizedepilepsywere testedwith theBeSSandFAS tests for language
ability.ThepeoplewithGEperformedworsethanhealthycontrolsintheBeSStest;performancewas
lower in all subtests of BeSS, except in the inference subtest (INF). The correlation of lower
performance inFASforpeoplewithGEtested justabovesignificance.Thereactiontimesofpeople
withGEinallconditionsoftheSENfMRItaskweresignificantlylongerthaninhealthycontrols.
The people with GE did not show similar suppression patterns in DMN regions as the healthy
controls had. In a direct comparison between brain deactivation patterns of people with GE and
healthycontrols, thepeoplewithGEshowedlesssuppressionof theposteriorcingulatecortexand
the left anterior temporal cortexduring readingof congruent sentences.Furthermore,peoplewith
GE showed activation rather than deactivation in the right parahippocampal gyrus. – The healthy
controlsdidnotshowanyactivationordeactivationatallinthatregion.
30
It is important in life to measure yourself at least once …
with nothing to help you but your own hands and your own head
paraphrasedafterPrimoLeviimmortalizedbyAlexanderSupertramp
31
4 DISCUSSION
4.1 Neural Correlates to Performance
4.1.1 Multiple Regression Analyses
From the multiple regression analyses no performance‐dependent similarities between the study
populations from PAPER II (Study A) and the unpublished results related to PAPER III (Study B)
emerged.Thismightnot comeasa surprise, since therewere severalkeydifferencesbetween the
word fluency and semantic tasks used in the two studies. The word generation task was slightly
differentineachstudy,butthesentencereadingtasksdifferedsubstantiallyfromeachother.SENCO
(PAPERI&PAPERII)wasaclozetest,presentingincompletecongruentsentencesthatlackedalast
word. In SEN (PAPER III & PAPER IV); the sentences were complete and congruent in the easy
condition, and complete but incongruent in de difficult condition. The subtraction of baseline
activation fromsentencereadingonSENdidnotyieldsignificantresults.The implicationsof these
divergentresultsaretwofold.First; thesemantic languageabilitycorrelatesvarydependingonthe
choiceoftask.This indicatesthattheidentifiedregionsfromPAPERII ine.g.BA47andBA22may
not be representative of semantic ability per se. This is not to say thatwe could not relate brain
activationtolanguageability;thiswillbediscussedinthenextsection‘LateralityAnalyses’.Second,
asdiscussedbyNewmanandcolleagues(2001)andBinder(2012),thechoiceofbaselinecondition–
often a formof rest – is pivotal for the activationpattern resulting fromsubtractingdesigns in an
fMRI analysis. A clear example is seen in the SEN results of PAPER III when we subtracted the
difficult condition, incongruent sentence reading, from congruent sentence reading. We obtained
very different results compared with subtraction of baseline activation from congruent sentence
reading–thiswillbediscussedinmoredetailinthenextsection.Thechoiceofcontrolconditionis
veryimportantbecause,asisnowwell‐known,abaselineconditionthatisnotengagingisnotequal
4.DISCUSSION
32
to a resting state of thebrain.Rather, the opportunity of letting themindwander evokes a highly
interconnected network supporting cognitive processes; this is described as the default mode
network.Thisnetworkwill bediscussed later in connectionwith languageability resultsobtained
frompeoplewithepilepsy.
Thebaselineconditionsinoursentencereadingexperimentsdidcontrolforthevisualaspectsofthe
sentencebypresentingclustersofsymbols.Inaddition,inthebaselineconditionofSENtherewasa
judgment aspect similar to the task condition, in which a button press from the participant was
required.Thebaselineconditionswerekeptsimpleandmightnothaveengagedtheparticipantsina
high degree as our intentionwas to image all aspects of language processing related to the tasks
insteadoffilteringoutsomeoftheseprocesses.However,accordingtoBinder(2012)thiscouldhave
theconsequencethatconceptualprocesses–sharedbetweentherestingnetworkandthelanguage
network –weremasked because the participants’ attentionwas not occupied during the baseline
condition. Since the baseline conditions differed between the semantic tasks, this could, together
withthetaskdifferences,accountforthedifferencesintheresultsbetweenstudies.
Theword generation taskswere rather similar. A possible explanation for the different results is
simplythatthestudypopulationsdifferedfromeachother.First,therewasasubstantialdifferencein
theagerangeoftheincludedparticipants.Adultsupto65yearsofagewereallowedtoparticipatein
thefirststudythatcomprisedPAPERIandPAPERII,asourinterestinlanguageabilityincludedthe
wholehealthy adult population.However, since our study sampleswere rather small, for thenext
studywe reduced the age range to 18‐35. Thiswould help to obtainmore power in our study, by
diminishingintra‐subjectvariability.Thevariationbetweenthewordgenerationtasksalsoneedsto
be addressed. The WORGE task used in PAPER II presented letters for 5 s each, the order was
randomizedwithin the blocks. TheWORD task, used in PAPER III was divided into high and low
frequencyletterblocks,withapresentationtimeofonly2sperletter.Thishastheimplicationthat
the WORD task, especially in the difficult condition which contained only infrequent letters, was
moredifficult thanWORGE.When investigating thisdifficultWORDcondition, theactivation in the
left angular gyrus showed to be related to high FAS performance. Activation in the left posterior
temporallobeinthedifficultSENconditionwasrelatedtohighBeSSperformance.Theseregionsare
concurrentwiththeP‐FITtheoryandtheactivationmightbelinkedtohigherintelligence.Increased
activationintheseregionsmaybeanindicationofneuraladaptabilityinhighperformingindividuals.
According to the neural adaptability theory (e.g. Prat et al., 2007), it can be expected that high
performers change their strategy depending on task difficulty, and thus show different brain
activation patterns for easy compared with difficult conditions. This adaptable activation may be
absentinlowperformersbecausetheydonothavethepossibilitytoadapttheirneuralactivation,or
because they simply stopped participating while high performers might continue. The results of
neuraladaptabilityevokingright‐hemisphericactivationforhighperformers,asseeninPAPERIand
4.DISCUSSION
33
PAPER II, did not emerge from themultiple regression analysis ofWORD; however the laterality
analysisdidshowthiscorrelation,aswillbediscussednext.
4.1.2 Laterality Analyses
Although we could not confirm the specific focalization of correlates to language ability, the
observationofsemanticperformance‐dependentactivityincreaseintheright‐hemisphericposterior
temporallobehasrepeatedlybeenmadeinourstudies.Wereproducedtheseresultswithdifferent
fMRI activation measures (multiple regression on activation in the whole brain in PAPER II, and
laterality index calculation on regions of interest in PAPER I and PAPER III), and with different
lateralitymeasures(LIinPAPERIandPAPERIII,anddichoticlisteninginPAPERI).SincePAPERIII
wasbasedonadifferentstudypopulationfromPAPERIandPAPERII,thisalsomeantareproduction
inanewstudypopulation.ActivationintherighttemporallobehasbeendiscussedbyBookheimer
(2002)torepresentvisual imagery,relatedtoearlier findingsthatwereclosetotheregionthatwe
foundtodrivethislateralizationdifference(Bookheimeretal.,1995;Keihletal.,1999).
Nexttothisrighttemporallobeinvolvementinlanguageability,wefoundsomeevidenceinPAPERII
thatactivationintherightIFGduringsentencecompletionwasindicativeofhighperformance.Inour
subsequentPAPERIII,wehoweverobservedthatadecreaseindominanceoftheleftIFGduringword
generationwasrelatedtohighperformance.It istemptingtospeculatethatthelevelofdominance
has a relation to language ability; a reasoning that has beenpostulatedbefore. The argument that
highlateralizationisindicativeofhighperformancehasbeenmaderepeatedlybyAnnett(1998),who
proposed the right‐shift theory in relation to language performance; and stated that language
dysfunctions in several disorders are linked to atypical (i.e. not left‐hemispheric) language
dominance.Thishasbeenobservedforschizophrenia(Crow2000;Ocklenburgetal.,2013),epilepsy
(Springeretal.,1999)anddyslexia(Crystal2010).Also, it isknownthatduringthedevelopmentof
language in children, lateralization increases with age (Szaflarski et al., 2006) and the degree of
lateralization in children seems tobe related toperformance (Groenetal., 2012).Nonetheless,our
resultsarenot the firstcontra‐indications forcognitiveadvantagesofadecreased left‐hemispheric
lateralization. Hirnstein and colleagues (2010) suggest that a high degree of lateralization is not
favorableforhighperformance;thishasbeenobservedmoreofteninadults(Lustetal.,2011).Our
studies indicate that indeed forwordgeneration, left lateralization correlatesnegativelywithhigh
performance in the IFG. However, our results from PAPER II do not show any performance‐
dependentactivationmodulationinBroca’sandWernicke’sareainthelefthemisphere,andthemost
consistent result is that the activation level of the right hemisphere drives the performance‐
dependentresults.Thiscouldbeinterpretedasneuraladaptabilityinthehighperformingbrain.The
adaptability seen in the IFG isobserved forbothword fluencyandsentencereading,butnot inall
4.DISCUSSION
34
studies.Inthenextparagraph,theadaptabilityoftheIFGinrelationtoincreasedsentencedifficulty
will be discussed in relation to the observed performance‐dependent laterality differences. The
adaptability of the right‐temporal lobe, however, is consistent for semantic tasks. Previously, the
right‐temporal involvment in pragmatics (Mitchell & Crow, 2005; Vigneau et al., 2011) and visual
imagery (Bookheimeret al., 1995;Keihl et al., 1999)werediscussed, andaprobable explanation is
thatthesefunctionsarebemoreevolvedintheparticipantsthatscorehighontheBeSStest.
The right‐lateralized semantic activation pattern for high language ability does not seem to be
dependentontaskdifficulty,unlikewouldbeexpectedaccordingtotheneuralefficiencyhypothesis
(Neubauer&Fink,2009).Thismightbeexplainedbytheverynatureofthesemantictasks.Peelleand
colleagues (2004) concluded that a semantic task is per definition complex. Participants therefore
may already in the easy condition experience considerable task demands, and already manifest
language ability‐related activation patterns. In conclusion; there appears to be evidence that
languageabilityisconnectedwiththedegreeoflanguagelateralization.Itcouldalsobethatlaterality
is not a static but a dynamic property of the brain. The flow of laterality could be regulated by
external inputand interhemispheric interactions (Seghieretal., 2011a). If so, individualswithhigh
languageabilitymightmodulatethisregulationtowardsanoptimalinteraction.
4.1.3 Task Difficulty Modulation
BeforediscussingtheresultsofourtaskdifficultymodulationfromPAPERIII,itisinterestingtotake
acloserlookatthedichoticlisteningresultsfromPAPERIinlightofanarticleoncognitivecontrol
and dichotic listening byHugdahl and colleagues (2009). In PAPER I, the dichotic listening results
show a correlation between right‐hemispheric processing and high language performance, this
correlation was in concordance with our fMRI laterality results. In particular, this correlation
appeared for our directed‐report‐left condition, which is similar to the forced left condition from
Hugdahl and colleagues. Whenever a person is forced to attend to the non‐dominant left ear, a
successfulreportofthisearcanonlybeachievedbymeansoftop‐downcognitivecontrol(Hugdahl
et al., 2009). This implies that increased cognitive control, and not increased language ability in
specific,couldunderlietheobserveddecreasedleft‐hemisphericlateralizationoflanguage.Thetask
difficulty modulation in our language ability investigation of PAPER III would therefore help to
understandwhethertheobservedright‐hemisphericinfluencesonperformancemightbemodulated
bycognitivecontrolratherthanlanguageability.
Increased difficulty of the semantic task evoked bilateral IFG activation. This result met our
expectations that were based on similar difficulty‐dependent findings (Just et al., 1996), possibly
4.DISCUSSION
35
related to increased working memory demands which activate the inferior and prefrontal gyrus
bilaterally (Cabeza&Nyberg, 2000).Better cognitive control duringword retrievalwouldhelp the
participant suppressing unwanted answers like already generated words, and thus favor high
performance. During the more difficult word fluency task condition with less frequent starting
letters,morecognitivecontrolisrequiredtoproperlygeneratewords,sincelesswordsareavailable.
Alternativelytolanguageabilitydrivingright‐hemisphericIFGactivation,theIFGactivationcouldbe
modulatedbycognitivecontrol.Unlike Justandcolleagues (1996) found in theirstudy,wedidnot
observe a difficulty‐dependent increase in the temporal lobe.We also found no interaction effect
betweentaskdifficultyandperformance.Therefore,inregardtosemanticdifficultymodulation,we
find no grounds for an alternative explanation that the increased right‐hemispheric temporal lobe
activationwouldbedrivenbytaskdemand.Wecanthereforedefendourhypothesis that language
ability, or at least semantic ability, is influenced by the degree of lateralization of the posterior
temporallobe.
TaskdifficultymodulationofthedeactivationpatternoftheDMNduringthesentencereadingtask
wasalsoinvestigatedforthehealthyadultsinPAPERIII.WhentheSENtaskbecamemoredifficult;
thesuppressionofactivationoftheanteriorcingulatecortexandadjacentmedialfrontalcortexwas
evenstronger.ThisisinlinewithastudyfromMcKiernanandcolleagues(2006),thatshowedthatan
increaseintaskdemandswouldresultinanincreaseofdeactivationintheDMN.Themedialfrontal
gyrus deactivation seems to be in the same region as the region described as the anterior‐ventral
medial prefrontal gyrus by Seghier and Price (2012). In their study, themedial frontal gyrus was
deactivatedduring semanticprocessing; thisdeactivationcouldnotbeexplainedbyan increase in
demands alone. The authors hypothesized that this deactivationwas a further suppression of the
‘freethinking’functionoftheDMN,inorderto“focusthesemanticsystemtowardtheexternalsalient
information” (Seghier & Price, 2012, pp 11). The augmentation of deactivation in the pregenual
anterior cingulate cortex was bordering the medial frontal cortex. This pregenual activation is
presumablyrelatedto taskswitching, inwhichtheanteriorcingulatecortexplaysanessentialrole
(Botvinicketal.,1999).
4.1.4 Language Dysfunctions in Epilepsy
InPAPERIV,wepresentedevidenceoflanguagedysfunctionsinpeoplewithGE;somethingthathas
notbeenthefocusoftheresearchonepilepsy.Subtlelanguagedysfunctionsmayhaveagreatimpact
on daily functioning (Sturniolo&Galletti, 1994), and, importantly,may negatively affect the life of
peoplewithepilepsy(Gauffinetal.,2011).Wealsoinvestigatedwhethertheselanguagedysfunctions
were related to atypical activation patterns in theDMN. In healthy adults, theDMN is suppressed
during cognitive tasks; this suppression was also observed during the semantic task SEN. This
4.DISCUSSION
36
deactivationoftheinterconnectedDMNsupportscognitiveprocesses(Foxetal.,2005;Binder2012).
In people with GE, the suppression showed to be not uniform; several regions did not exhibit
deactivation.Alackofdeactivationhasbeenlinkedtoadecreaseincognitiveperformance(Kellyet
al.,2008). InadirectcomparisonbetweenpeoplewithGEandhealthyadults, thedecrease inDMN
activationdifferedsignificantly in theposterior cingulate cortex–a centralprocessingnode in the
DMN (Fransson & Marrelec, 2008) – and the left anterior temporal cortex. Our results point to a
reducedfunctionalsegregationoftheDMNwhichcouldexplainthesubtlelanguageimpairmentsthat
people with GE have, and which were described in PAPER IV (McGill et al., 2012). A second
explanationfortheimpairmentofcomplexlanguagefunctionsasmeasuredbyBeSScanbefoundin
the aberrant hippocampal and parahippocampal activation in peoplewith GE,which could impair
semanticretrievalfunctioning(Greenbergetal.,2009;Sheldon&Moscovitch,2012).
4.2 Healthy Adults
One of the main issues in this dissertation is the variability in language ability between healthy
adults. In experiments, researchers try to keep the inter‐subject variability at the lowest level
possible,sincefindingsrelatedtothevariableofinterestcouldeasilybeobscuredbythisvariability.
This isespecially thecasewhengroupsaresmall, as isusual in fMRIstudies.As is thecase inour
presented studies, the study group is often controlled for: age, gender, handedness, concomitant
medical,neurological,orpsychiatricillnesses,andtheuseofpsychoactivedrugs.Betweenourstudy
populations,thereweredifferencesintheagerangeofthehealthyparticipants.Thisdifferenceinage
could bring out a greater variance in performance scores, but could also obscure results by
introducingmoreinter‐subjectvariability.
We included both males and females in our experiments but found no significant difference in
performancebetween thesegroups.This isnot to say thatgender‐relatedperformancedifferences
arenottobeexpected;ithasbeenshownthatfemalesoutperformmalesinlanguagetasks,especially
in verbal fluency tasks (Kimura 1992). Interestingly, improved performancemight not necessarily
haveagender‐relatedneuralcause(Sommeretal.,2008;Allendorferetal.,2012).Infutureresearch,
itmightbenecessary togathermoredetailed informationaboutparticipants. Several studieshave
investigated hormonal influences – which vary depending on themenstrual cycle – in relation to
performance (Fernández et al., 2003; Simić & Santini, 2012). They conclude that indeed language
performancevariesdependingonthemenstrualphase,butnotuniformlyfortaskorregion.Eventhe
4.DISCUSSION
37
lateralizationoflanguagehasbeenshowntovarydependingonthemenstrualphase(Hjelmerviket
al.,2012).
Whereas inter‐subject variability in brain regions related toword generation has found to be low
(Xiong et al., 2000), this is naturally not the case when participants who have right hemisphere
dominanceforlanguageareincluded.Controllingforhandednessisanindirectcontrolforlanguage
lateralization.However,ashasbeenobservedthroughoutthisdissertation,thelevelofhemispheric
dominanceishighlyvariableamongstright‐handedindividualsandbetweenregions.Moreover,the
majority of left‐handers (who are often excluded from language fMRI research) have also left‐
hemisphericdominanceforlanguage,whileright‐handerscouldhaveright‐hemisphericdominance.
It is though shown in a study combining fMRI and diffusion tensor imaging, that handedness is
directly relatednot only to laterality but also to hemispheric asymmetry (Propper et al., 2010).Of
course, assessing handedness gives a cheap and quick indication of language laterality; however,
when assessing control groups it is important to consider all the factors that influence language
abilitythatarenotcontrolledfor.
4.3 Interpretation of Activation Patterns
Brainfunctioningmeasuredbynon‐invasiveneuroimagingstudies likefMRIcannoteasilygenerate
asmuchincontestableevidenceascouldbeobtainedfromlesionorintracranialrecordingstudies.In
fMRIstudies,severalassumptionsaremade,thesearealsoaddressedintheMethodschapter.
Someoftheseassumptionsare:
a) neuralfunctioningischaracterizedbytheBOLDresponse
b) neuralfunctioningcanbevisualizedbysubtractionofactivationinabaselinetaskfrom
activationinacognitivetask
c) themeasuredactivationisrelatedtobrainfunctioning,ratherthantonoise
d) theresultscanbegeneralizedoutsideofthestudypopulation
Thediscussionofassumption a)isafundamentalone;howistheBOLDactivationthatweseeinour
imagesrelatedtoactivityonaneuronallevel?Thatthereisarelationisnolongerindoubt(Buckner
4.DISCUSSION
38
2003);howeverthenatureofthisrelationisfarfromclear.TheresearchgroupofLogothetishasvery
recentlydiscussedthecurrentstateofknowledgeabouttherepresentationoftheBOLDsignalona
neuronallevel(Goenseetal.,2012).Theystatethatthereisevidenceforunderlyingcontributions
bothfromlocalfieldpotentialsaswellasfromsmallerneuronalpopulations8;bothfromexcitatory
aswellasfrominhibitoryneuralactivity;andalsoforcontributionfromdifferentneurotransmitters.
TocomplicatetheviewontherelationshipbetweentheBOLDresponseandneuronalsignalseven
more;theauthorsconcludethat“therelationshipmaydifferdependingonarea,task,orbehavioral
stateofthesubject”.Theneuronalunderpinningsofcomplexlanguagefunctioningcanthereforenot
yetbeexplained,andthisassumptionthusremainsunproven.
Assumption b) takesthediscussiona levelhigherbyasking if theparadigmusedandtheanalysis
thereof indeedmeasuresthecognitive functionof interest.The fact thatactivation isobserved ina
region does notmean that the related cognitive function is located in that area. A parallel can be
drawnwiththelanguagedysfunctionsdiscussedintheIntroduction;dysfunctionsfollowingalesion
donotprove that the lesionedregion issolelyandselectivelyresponsible for theexecutionof that
function.Theregioncouldjustaswellbeasmallpartofaserialnetwork,orcontaininterconnecting
fibers from two executive areas (Roskies et al., 2001). Whereas the presented literature under
assumptiona) indicatedthat it isreasonabletoassumethatneuronsandnotneuronalconnections
giverisetoobservedBOLDresponses,theexactnatureofthecontributionoftheactivatedareacould
notbedeterminedfromourstudies.
To understand the right‐hemispheric activation observed throughout the work reported in this
dissertation, the interpretationneeds tobebasedon literature findingson languagedisability and
language functions in the left hemisphere as presented in the Introduction. Furthermore, a closer
lookat subtractionanalyses isneeded.Obviously, subtractingabaseline symbol‐viewingcondition
froma complex linguistic condition leavesactivation that couldbe related tomanycomponentsof
thelinguisticmodel.ThisisfurtherillustratedbyouranalysesinPAPERIII,wherethesubtractionof
the‘hard’fromthe‘easy’condition,namelyincongruentfromcongruentsentencereading,provided
verydifferentresultsfromwhenwesubtractedthebaselinecondition.Theanalysisthatinvestigated
sentence reading in comparison to the baseline did not result in any significant activation, likely
becauseofmostactivationthatistaskrelatedissharedbetweenindividuals.Onlywheninvestigating
specific aspects of sentence reading, individual differences emerged. These differences could be
representative forstrategydifferencesrelatedto languageskill.Theaimof thisdissertationwasto
8Localfieldpotentialscanberoughlydefinedastheaveragedinputsignalofaneuralpopulationmeasuredoverafewmillimeters,whilemulti‐unitactivationcanbemeasuredonsmallerneuralpopulationsandrepresentsneuronaloutputsignals(Logothetisetal.,2001)
4.DISCUSSION
39
generalize language ability contributions rather than to define separate linguistic components.
Therefore,thesubtractionmethodwassuitableforouranalyses.
Of course, a reverse subtraction, namely subtracting the task condition from baseline, can also be
done.Thiscontrastwillvisualizeanti‐correlatedpatterns. It is lesscommonto lookatdeactivation
patterns thanatactivationpatterns,althoughneuralsuppressioncanprovidevaluable information
as observed in PAPER IV. The representation of language models in neurolinguistic results is
criticallyreviewedbyVanLancker‐Sidtis(2006)andSidtis(2007),andrightfullyso.Severalquestions
underlyingassumptionb)areoftentakenforgrantedinneuroimaging.Someofthesequestionsare
whether language components have a functional correlate in the brain, or whether increased or
decreasedactivationrepresentsbetterorworseperformance.Itisplausiblethatthereisnouniversal
theory to describe neural functioning in the brain, but that activation should be interpretedwith
regardtoregionandtask9.ItisalsolikelythatothermethodsthantheGLMshouldbeusedtoanswer
questions such as ‘How is language ability represented in thebrain?’ inmoredetail. TheGLM is a
robustmodelbutnottherightchoicewhentheunderlyingbrainactivationisexpectedtodeviatein
physiological properties or interconnectivitywithother regions. Instead, a networkmodelmaybe
used;thiscanbebasedonROIsorbeunguided10.Thepossibilitiesofusingnetworkmodelsinclude:
creatinganoptimalmodelspecifictothetestedstudypopulation;detectingactivationpatternsthat
werenotexpecteda priori,andvisualizinghowdifferentregionshaveasharedcorrelationoranti‐
correlation with the task. Such an analysis could for instance shed light on the possibly aberrant
interactionsoftheDMNinpeoplewithGE
Assumption c) isperdefinitionnotcompletelytrueifnocounter‐measurementsaretaken.Sincea
whole‐brain fMRI dataset usually contains over 100 thousand voxels, and a GLM tests for the
significance of activation in each voxel, the chance of obtaining false positives is substantial. It is
necessary to at least apply a stringent p‐value, and preferably apply a correction for multiple
comparisons.Apitfallrelatedtotheamountofnoisepresentinthedataistheinflationoftheamount
offalsepositiveswhentestingonanon‐independentselectedsample.Thisinflationwaspopularized
as ‘voodoo correlations’ (Vul et al., 2009)11, and although it referred to social science studies in
particular,thearticleraisesavalidpointregardingselectionofregionsofinterest.Theapproachthat
weadoptedinPAPERII–selectingROIsbasedondataresults,andextractionofparameterestimates
only from these selected ROIs – has to be used cautiously. The reported significance can only be
based on the initial selection, and not on subsequent correlation tests thatwould only re‐test the
9e.g.inthefrontallobemaytheneural efficiency hypothesis of intelligence beapplied,seealso‘IntelligenceModels’intheIntroduction.
10suchasanindependentcomponentanalysis11‘Voodoocorrelations’wasadefinitionusedinthepre‐publishedtitle,thiswasvehementlydiscussedonline;overviewat:www.edvul.com/voodoocorr.php
4.DISCUSSION
40
alreadydeterminedcorrelation.Therefore,inPAPERII,weusedthismethodnottoselectbutrather
todeselectactivatedROIswhosestatisticalsignificancewasalreadyensuredintheinitialanalysisby
applyingacorrectionformultiplecomparisons.
Multiplecomparisonsarenotonlymadewithinadataset,butalsowhenrunningdifferentanalyses
ondatafromoneexperiment;whenrunningdifferentexperimentsonthesamestudypopulation;or,
arguably,when including different studieswithin one dissertation.With every newmeasurement,
thechanceoffindingafalsepositiveresultincreases.Howcanwebesureourresultsreallyrepresent
reality instead of random noise? Of importance is the fact that the different analyses of the same
studypopulation,(PAPERIonthepopulationofStudyAandPAPERIII&PAPERIVonthepopulation
of Study B) are based on pre‐defined selection of regions of interest; thus the analyses are only
guided by previous, independent research. PAPER II had a different approach. This paper started
with an unconstrained whole‐brain analysis, which, unguided by the researcher or other input,
reproducedtheROI‐restrictedfindingsofPAPERI.Clearly,PAPERIandPAPERIIareinterdependent
since they examine people from the same participant pool; therefore the results show similar
patterns.Thesepatternscouldbedueeithertonoiseortoperformance‐relatedactivation.Asisthe
casewith fMRIresearch,allactivationshouldberegardedasspuriousunlessreproducedoverand
over again. A strong evidence for results to be reliable, is reproduction over methods or study
populations. In PAPER I, our results from the fMRI analysis were congruent with our dichotic
listening results; both indicated that increased right‐lateralization was correlated with high
performance.StudyBwasperformedforthereasonofreproductionoftheresultsfromPAPERIand
PAPER II in a new study population. Some of our results from PAPER II remained unconfirmed,
howeverwedidreproducefindingsthatincreasedrighttemporallobeactivationanddecreasedleft
IFGactivationweredependentofhighperformance.Therefore,theseindependentlyandrepeatedly
obtainedresultsbecamethefocusofthisdissertation.PAPERIIIandPAPERIVinvestigatedifferent
regions of interest in the same healthy adult study population, and our view broadened, from
differences in the healthy population, to include the investigation of differences between healthy
participants and peoplewith epilepsy. Even though the healthy participant group is the same, the
hypothesesandtestsbetweenpapersaredivergent.Moreover,thet‐testsofPAPERIVandmultiple
regressionanalysesofPAPERIIIwerecorrectedformultiplecomparisonswithuseofthestringent
family‐wise error rate. The laterality index correlations of PAPER III are based on comparisons
betweentworegionsof interest, thisalreadyreducedthestatisticalcomparison fromthousandsof
voxelstothefewtestedROIs.
Assumption d) is again best proved by reproduction of results, as is done in PAPER III; by
reproducing findingsofPAPERIandPAPERII.Someofouranalysesareperformedonarelatively
small study population, even by fMRI standards. This population may or may not have been
representative of other healthy adults. Because of the small group size, the outcomes are rather
4.DISCUSSION
41
sensitivetooutliers,especiallyinmultipleregressionanalyses.Theproblemswithsmallgroupsizes
arediscussedbyThirionandcolleagues (2007),whosuggested thataround20participantswasan
acceptablegroupsize.Someofouranalysesarewhole‐groupanalyses,onupto27participants,but
someotheranalysesinvestigatewithin‐groupdifferences,andthereforehavelessdetectionpower12.
Lessdetectionpowerresultsinahigherpossibilityofmanyfalsenegatives;thustherewasagreater
chancethatwefailedtofindexistingneuralcorrelatestolanguageperformance.However,thefound
resultsaresignificant,becausefalsepositiveswerekepttoaminimumbyapplyingcorrectstringent
p‐values, and by applying corrections for multiple measurements on the multiple regression
analyses.
To comeback to the sensitivity to outliers in small groups, thiswas addressedwith an additional
analysisofdatafromStudyA,whichwasthestudywiththesmalleststudypopulation.Theresultsin
PAPERIIfromthemultipleregressionanalysis,thatshowedactivationduringSENCOrelatedtohigh
performanceintheBeSStestandthatwasunderlyingourhypothesesinPAPERIII,werere‐analyzed,
this time with a two‐sample t‐test. The two samples, high performers and low performers, were
participantsthathadperformedaboveandunderthemeanscoreforBeSSrespectively.Theresults,
presenteduncorrectedinFigure6,showactivationintherightIFG(parsorbitalis,BA47)andright
middle temporal gyrus (BA 21). This activation pattern proved to be significant at p < 0.05, FWE
corrected,whentheROIsfromPAPERIIIwereapplied.
Figure 6. Brain activation during the sentence completion SENCO task, when contrasting high BeSS performers to low BeSS performers. Activation is observed in the right hemisphere, in the inferior frontal gyrus pars orbitalis and in the middle temporal gyrus. This activation was significant at p<0.05, FWE corrected after small volume correction on predefined regions of interest.
12Itshouldbenotedhoweverthatourexperimentsweredoneusingequipmentandsoftwarefrom
post2007,whichcontributedtoimprovedsignaldetection.
4.DISCUSSION
42
4.4 Future Directions
Notably, severalof thepresented results, eitherunpublishedorpresented inourpapers,werenot
according to our expectations. The results together cannot reveal a sufficientmodel of the neural
correlatestolanguageability,sincetheconceptappearstobetoointricate.Nonetheless,ourresults
provideimportantclueshowtoobtainanevenbetterunderstanding.
Themost consistent findings in previous literature that is presented in the Introduction – ‘Right‐
hemisphericInfluences’andthatisdiscussedindetailinPAPERIII,indicateanimportantroleofthe
righthemisphereinunderstandinglanguagecontextandintegratinglinguisticinformation.Theright
hemisphereisactivatedespeciallywhenthelanguageusedisambiguousorfullofimagerysuchasin
metaphors.InoursentencereadingtaskSEN,theparticipantshadtoimaginewheresituationstook
place, this required spatial thinking and evoked right‐hemispheric activation (Brown & Kosslyn,
1993). Spatial thinking is not unique for our semantic task; in fact, a great deal of language
understanding requires the use of spatial concepts (Zwaan & Radvansky, 1998). It is tempting to
hypothesizehowourfindingsnotonlyindicateaneuralcorrelatetosentenceunderstandinginthe
rightposteriortemporallobe,butmaybelinkedtoimageryorspatialthinkinginvolvedinlanguage
tasks. Thus, the absence of performance‐modulated right‐hemispheric activation in relation to our
fluency taskmightbebecauseof thenatureof this task.Futurestudiescould introduceadifferent
fluencytaskthatincorporatesspatialthinking.Thiscouldbeaverbaldivergentthinkingtasks,such
as thebrick task (‘Howmany things canyoudowith abrick’) (Guilford et al., 1978). Carlssonand
colleagues(2000)presentedastudythatgivesapromisingbaseforthishypothesis.Thestudyfound
thattheBricktestincomparisontotheFAStestactivatestherightfrontallobesignificantlymorein
highlycreativeparticipantsthaninlowcreativeparticipants.TheFASperformancescoreshowever
didnotvarybetweenthosetwogroups.Brainactivationobtainedduringsuchadivergentthinking
task, or an other spatial thinking based task,might be sensitive to right‐hemisphericmodulations
relatedtolanguageperformance.Possibly,languageabilityshouldbemeasurednotwiththeFAStest
but with the complex language functioning BeSS test, since the latter test investigates more
componentsoflanguage.
It would also be valuable to test for intercorrelated networks in relation to performance. It is
reasonabletosuspectthathighlanguageabilitymightbecharacterizednotonlybyneuraladaptable
regions but also by adaptable connectivity, thus a change in correlation between activated brain
regions.Dynamiccausalmodelingofourregionsofinterestwouldgiveananswertothathypothesis.
4.DISCUSSION
43
In addition, functional brain activation images of our participant groups during rest have been
collected.Asdiscussedbefore;thebrainisfarfromrestingduringrest,butrathershowsactivationin
thedefaultmodenetwork.Sinceweobservedadiminishedsuppressionofthisnetworkduringtask
inpeoplewithgeneralizedepilepsy,theremaybeconnectivitydifferencesaswellthatarerelatedto
languagedysfunctionsoreventotheleveloflanguageability.Again,adynamiccausalmodelmight
help toanswer thishypothesisanddeterminewhether languageability level canbevisualizednot
only as divergent neural correlates but also as divergent neural interaction. Another method to
visualizeconnectionbetweenbrainregions isdiffusiontensor imaging,whichvisualizes theneural
pathways and intra‐ and interhemispheric connections in the brain (Glasser & Rilling, 2008).
Diffusion tensor imaging could reveal properties of neurons and neuronal pathways that may
distinguish high language ability (e.g. Konrad et al., 2012), and underlie the functional differences
observedthroughoutthiswork.
44
Seal my heart and break my pride I've nowhere to stand and now nowhere to hide
Align my heart, my body, my mind To face what I've done and do my time
‘DustBowlDance’–Mumford&Sons
45
5 CONCLUSIONS
The results presented in this dissertation consistently show that activation in the right posterior
temporallobeiscorrelatedwithhighlanguageabilityinhealthyadults.Themechanismbehindhigh
performance could be a better adaptation of right‐hemispheric temporal activation, and stronger
pragmaticorvisualimageryskills.
PAPER I aimed to relate regional lateralization of semantic language functions to language ability.
Dichotic listening laterality results showed that increased right‐hemispheric laterality correlated
withhigh languageperformance.ThefMRIfindingsrevealedthatspecificallyactivationintheright
IFGandrightposteriortemporallobecorrelatedwithhighlanguageability.
The aim of PAPER IIwas to both reproduce these findings and test for other neural correlates to
languageability.Themostconsistent findingwas theconfirmationof thecontributionof theright‐
hemisphericIFGandposteriortemporallobetohighlanguageability.
InPAPERIII,anewstudypopulationwasinvestigatedandtestedforreproducibilityofourprevious
results. Indeed, increased semantic activation in the right‐hemispheric posterior temporal lobe
correlated with high performance in a complex language test. It was also revealed that it was
decreased left‐hemispheric rather than increased right‐hemispheric IFG activation during word
generation that correlatedwith increasedword fluency ability. These resultswere congruentwith
the hypothesis of neural adaptability as a language ability characteristic. Furthermore, when task
difficultywasmodulated,thebilateralIFGwasactiveonlywhentaskdemandsincreased,thiseffect
wasnotexpectedbutnotobservedinWernicke’sarea.
Lastly, PAPER IV investigated the defaultmode network that is anti‐correlatedwith a task. Itwas
found that people with generalized epilepsy show poor anti‐correlation patterns of this network.
Thismightexplain thediminishedperformancescores for complex languageability that thegroup
containingpeoplewithGEshowedincomparisontohealthyadults.
46
Acknowledgments
Acknowledgments should probably not be written just a few days before print. There are so many I would like to thank. But I’ll drink coffee like there’s no tomorrow and try to name you all.
First,I’dliketothankmysupervisors,ourworktogetherunderyourguidancehasledtothesepublicationsonwhichmydissertationstands.
Thomas Karlsson;I’dneverhavethoughtthatspendingallthoseeveningsatworkcouldbesopleasant.GoSkellefteå!Coffee,wisewords,andjokes;alloftheseinabundance;untilIhadtorunforthetrain.IhopewewillcontinueincollaborationonourfMRIjourneythathasledussofar.
Peter Lundberg;wheneverIthoughtsomethingwasobvious,you’daskme:“Whyisthat?”Verytrue;nothinginthebrainisobvious,itisfascinating!ItwasbecauseofyourconnectionwithBasthatIcameinSwedentotheintherestoftheworldratherunknown–fjärdestorstadsregion!!‐.AtfirstIwassoconfusedbyyourSkånsk,howevernowI’mprettyconfidentwe’llworktogethergreatinexcitingstudiesthatareyettocome.
Anita McAllister;I’vegreatlyenjoyedyourenthusiasm;oneverythingfromlanguage,totheuseofyourvoice(Iwillpracticebeforepresentingthisbookthe17th!),tolovelystoriesliketheoneaboutPulvermüller.
Andaboveall;Maria Engström;youwerethemostdedicatedsupervisoraPhD‐studentcouldaskfor,itisthankstoyouthatIamwhereIamnow.I’vehadthepleasureofmeetingyourlovelyfamilyandenjoyingyourcompanyinBarcelonaandSevilla.You’velearnedmetoappreciatecontemporaryart,andweshareastrongpassionforthefjäll;ifwewon’tmeetatwork,we’llmeetthere!
Ialsowouldliketothankallofmyco‐authors,withyouI’vespendconsiderabletimebrainstormingandwonderingoverweirdresults.Mattias Ragnehed;whenIbegan,Igotyourdissertationwiththetext“Lyckatillmeddinegen”;well,hereitis!Mathias Hällgren;thanksforyourworkondichoticlistening;agreatcomplementtoourfMRIwork.Daniel Ulrici;you’veputsomuchworkintoourEpilepsystudy,thanksformakingitasuccess.AnneMarie Landtblom;we’vediscoveredtheseinterestingthings,andyouwerealwayscuriousformore,bedankt!Andit’sashamethefjällugglordidn’tmakeitintoourpaper.Helena Gauffin;I’vehadgreatfunandlotsoflaughswhenworkingwithyou,butevenmorewhenwedidnotwork.
Thankstoallthevolunteersthatparticipated,especiallythankstotheepilepsypatients,fortheirvaluabletimeandtheirpatience.
Mycolleaguesat,andthroughresearchlinkedtotheCMIVorRadiologicalSciences;wholivebytheadagio“greatworkdeservesgreatcoffeebreaks”.You’vetrulylearnedmehowtofikalikeaSwede.I’dlikethankallyouguysandmentionspecificallyAnders T (thanksforintroducingmetospexandcheapmovieswhenIwasjustarrivedinSweden),Maria M,Chunliang (andofcourselittleDavid;IhopeI’llmeethimagain!),Filipe,Olof,Anders P,Örjan S,Marcel,andHåkan G.SomeofmypartnersinfMRI‐crime:Mats L,Örjan D,Susanna,let’smeetattheFBI!My(ex‐)roommatesAnders G,Danne,Rodrigo,JonatanandKarin;we’vehadawonderfultimeinBeijingwithfriedicecreamandplayingguess‐what’s‐on‐the‐menu.FortheFuture!.Thepeoplewhomadethingswork;Anna,Annika,Henrik E,Ingela A,Ingela E,Johan,LillianandMaria K;I’dseriouslybelostwithoutyourhelp.
47
ThankstoDOMFiLandthepeoplewithwhoIhadtheprivilegetorepresenttheHealthSciencesPhDstudents;Axel,Sven,Alma,Daniel andStefan.I’velearnedmanythingsthatIneverknewandmorethingsthatIimmediatelyforgot,butitwasgreatfun!
IenjoythinkingbackonthetimewhenIstartedallfreshandnaïvewithresearchinUtrecht.ThankstoRyota KanaiwhoIdidmyveryfirstexperimentswith.I’vesathoursandhoursadaptingtomovingstimuli,onlytofigureoutthattheexperimentshouldbedoneotherwiseonceagain.Andyetitwasfascinating,exciting,andagoodtraininginhowdatacollectionwouldbe.
ThankstoBas Neggerswhosupervisedmeintosomethinghalfdecentasaresearcher,andwhoguidedmetomyveryfirstpublications.Notonlydidyoubelieveinme,weevenhadawesometimesonvacation‐Imeanconferences.BBQ,snorkeling,andbeer;livinginapartmentsinsteadofboringhotels;lifewasgood.SometimesImissplayingwithstrongmagnets.
Thankstomygreatformer(andfirst!)neurosciencecolleaguesfromUtrecht,whoIenjoymeetingforbeer,bbq,(itseemstobearecurringthemewithdutchies)androadtripsduringconferences:Antoin;notonlyIrememberthatyoucouldevokethumbtwitcheswhileapplyingTMSonyourownheadwithyourotherhand,butalsothatAustraliaroadtripwasepic.TogetherwithKelly;I’dliketoaddtothestoryfromthelastthesisaboutour5000kmdrivewithoutproperpreparationandthefactthatweaccidentallylostaday.Becausewhatabouttheimpromptucampfires,birdsandkangaroosliterallyeverywhere,andthefactthatwedidthewholetripwithonlyONEcd(TheClassof’55)thatrockedasmuchasyouguysdo.Tjerk &Willem,thanksfordoingsweetstudiesandwritingsweetpaperstogetherwithme.Mariët;youwereagreatfriend,we’vehadgoodtalks,bestroommateever!Cédric,Remko;Ireallyhopewe’llmeetagain,it’sgreatfungoingoutwithyou!
Thankstomyfriends;fortheextrasupportduringthiscrazyperiod,forlendingmeyourbrain(Andreas)oryourtime&help(Stacy,Emily).ThanksforyourfriendshipDavid&Natasha,David B,Frida &David L,Elin,Britta, Jonathab (sic),Sune &Karin,Caroline,Emilie,Denes & MargitandallofmyfriendsintheImmanuelskyrkan.Thanksforthewine,whiskeyandcheese,thelaughsandthehelpwithmoving,mostofallthanksforyourwarmhearts.Ican’twaittomake‘sociallife’adailythingagain.ThankstoRichtje &Jeroen,andNatascha &Wouterforyourvisitsandlove;youguysaretruefriendsandIhopeonmany(more)snowandhikegetawaystogether.Also,sometimesIwishIcouldkidnapallyourkids,butI’mgladIdidn’tdoitbecauseI’dneverhavefinishedwritingthisthing.Joel;youbecameagoodfriendafterwe’veonlytalkedforafewminutes.That’sexceptional.Let’sdosomeskitouring.ThankstoMatthijs;Bobmightbeyourbrotherfromanothermother,butyou‘remycolleagueinanothercountry;we’vesharedawholecareerfromthenavytopsychology.Yourworkisgreat,yourenthusiasminspiring,andyourstories;theyarehilarious.
Thankstomyfamily.ThankstoTjeerd &Ienke,myparentswhotaughtmethatIcouldbecomewhateverIwanted.Andyouweretherewithme;whetheritwasonawindyboatorinanoisymagnet.Thanksforthecarepackagesandthedesignofthisbook.ThankstoDick &Edith,myparents‐in‐law,foralwaysbeingthereandlendingahandwithwhatevercrazythingswe’dthinkof.ThankstoMarlies (thanksforyourvisitsandpracticalhelp!),Pauline&Karin;mysistersandsister‐in‐lawforeverything,butmostofallforbeingdevotedauntstoLucas.
Finally;thankstoBob.Thanksforbeingmylast‐resortguineapig(freelyinterpretingtaskinstructionsandsufferingthroughEEG‐try‐outs).We’vedeliveredbabyLucaslastyear,adissertationthisyear;weprobablyshouldtakeiteasyforawhile.Butwewon’t.Witheveryadventure,Ilovetotaketheleap,butitisbecauseofyouthatIdon’tcrash.Mylifewouldn’tbeawesomewithoutyou.
49
References
Abou–KhalilB(2007).ReviewMethodsfordeterminationoflanguagedominance:theWadatestandproposednoninvasivealternatives.CurrentNeurologyandNeuroscienceReports7(6):483–490.
AhrensK,LiuH,LeeC,GongS,FangS,andHsuY(2007).FunctionalMRIofconventionalandanomalousmetaphorsinMandarinChinese.BrainandLanguage100:163–171.
AllendorferJB,LindsellCJ,SiegelM,BanksCL,VannestJ,HollandSK,andSzaflarskiJP(2012).Femalesandmalesarehighlysimilarinlanguageperformanceandcorticalactivationpatternsduringverbgeneration.Cortex48(9):1218–1233.
AnnettM(1998).Handednessandcerebraldominance:therightshifttheory.JournalofNeuropsychiatryandClinicalNeurosciences10(4):459–469.
BergAT,BerkovicSF,BrodieMJ,BuchalterJ,CrossJH,vanEmdeBoasWV,EngelJ,etal.(2010).Revisedterminologyandconceptsfororganizationofseizuresandepilepsies:reportoftheILAECommissiononClassificationandTerminology,2005–2009.Epilepsia51(4):676–685.
BinderJR(2012).Taskinduceddeactivationandthe“resting”state.NeuroImage62(2):1086–1091
BinderJR,DesaiRH,GravesWW,andConantLL(2009).Whereisthesemanticsystem?Acriticalreviewandmeta–analysisof120functionalneuroimagingstudies.CerebralCortex19:2767–2796.
BookheimerS(2002).FunctionalMRIoflanguage:Newapproachestounderstandingthecorticalorganizationofsemanticprocessing.AnnualReviewofNeuroscience25:151–188.
BookheimerS,ZeffiroT,BlaxtonT,GaillardW,andTheodoreW(1995).Regionalcerebralbloodflowchangesduringobjectnamingandwordreading.HumanBrainMapping3:93–106.
BoothJR,BurmanDD,MeyerJR,GitelmanDR,ParrishTB,andMesulamMM(2003).Relationbetweenbrainactivationandlexicalperformance.HumanBrainMapping19(3):155–169.
BottiniG,CorcoranR,SterziR,PaulesuE,SchenoneP,ScarpaP,FrackowiakRS,etal.(1994).Theroleoftherighthemisphereintheinterpretationoffigurativeaspectsoflanguage.Apositronemissiontomographyactivationstudy.Brain117:1241–1253.
BotvinickM,NystromLE,FissellK,CarterCS,andCohenJD(1999).Conflictmonitoringversusselection‐for‐actioninanteriorcingulatecortex.Nature402(6758):179–181.
BrownHD,andKosslynSM(1993).Cerebrallateralization.CurrentOpinioninNeurobiology3(2):183–186.
BuchananT,LutzK,MirzazadeS,SpechtK,ShahN,ZillesK,andJänckeL(2000).Recognitionofemotionalprosodyandverbalcomponentsofspokenlanguage:anfMRIstudy.CognitiveBrainResearch9:227–238.
BucknerRL(2003).Thehemodynamicinverseproblem:MakinginferencesaboutneuralactivityfrommeasuredMRIsignals.ProceedingsoftheNationalAcademyofSciencesUSA100(5):2177–2179.
CabezaR,andNybergL(2000).ImagingcognitionII:Anempiricalreviewof275PETandfMRIstudies.JournalofCognitiveNeuroscience12:1–47.
50
CaplanR,andDaprettoM(2001).Makingsenseduringconversation:AnfMRIstudy.NeuroReport12(16):3625–3632.
CaplanR,SiddarthP,VonaP,StahlL,BaileyC,GurbaniS,SankarR,etal.(2009).Languageinpediatricepilepsy.Epilepsia50:2397–2407.
CappaSF(2012).Imagingsemanticsandsyntax.NeuroImage61(2):427–431.
CarlssonI,WendtPE,andRisbergJ(2000).Ontheneurobiologyofcreativity.Differencesinfrontalactivitybetweenhighandlowcreativesubjects.Neuropsychologia38(6):873–885.
CarpenterPA,andJustMA(1999).Modelingthemind:veryhigh‐fieldfunctionalmagneticresonanceimagingactivationduringcognition.TopicsinMagneticResonanceImaging10(1):16–36.
CattsHW,andKamhiAG(2005).Causesofreadingdisabilities.InHWCattsandAGKamhi(Editors),LanguageandReadingDisabilities,SecondEdition:pp94–126.Boston:Allyn&Bacon.
ChaixY,LaguittonV,Lauwers‐CancesV,DaquinG,CancesC,DémonetJF,andVilleneuveN(2006).Readingabilitiesandcognitivefunctionsofchildrenwithepilepsy:influenceofepilepticsyndrome.Brain&Development28:122–130.
CostafredaSG,FuCH,LeeL,EverittB,BrammerMJ,andDavidAS(2006).AsystematicreviewandquantitativeappraisaloffMRIstudiesofverbalfluency:roleoftheleftinferiorfrontalgyrus.HumanBrainMapping27(10):799–810.
CrowTJ(2000).SchizophreniaasthepricethatHomosapienspaysforlanguage:aresolutionofthecentralparadoxintheoriginofthespecies.BrainResearchReviews31:118–129.
CrystalD(2010).TheCambridgeencyclopediaoflanguage,ThirdEdition.NewYork:CambridgeUniversityPress.
CuenodCA,BookheimerSY,Hertz–PannierL,ZeffiroTA,TheodoreWH,andLeBihanD(1995).FunctionalMRIduringwordgeneration,usingconventionalequipment:Apotentialtoolforlanguagelocalizationintheclinicalenvironment.Neurology45(10):1821–1827.
DaprettoM,andBookheimerSY(1999).Formandcontent:dissociatingsyntaxandsemanticsinsentencecomprehension.Neuron24(2):427–432.
DémonetJF,ThierryG,andCardebatD(2005).Renewaloftheneurophysiologyoflanguage:functionalneuroimaging.PhysiologicalRevies85(1):49–95.
DoppelmayrM,KlimeschW,HödlmoserK,SausengP,andGruberW(2005).Intelligencerelatedupperalphadesynchronizationinasemanticmemorytask.BrainResearchBulletin66(2):171–177.
DrägerB,JansenA,BruchmannS,FörsterAF,PlegerB,ZwitserloodP,andKnechtS(2004).Howdoesthebrainaccommodatetoincreasedtaskdifficultyinwordfinding?AfunctionalMRIstudy.NeuroImage23,1152–1160.
DronkersNF,PlaisantO,Iba‐ZizenMT,andCabanisEA(2007).PaulBroca’shistoriccases:highresolutionMRimagingofthebrainsofLeborgneandLelong.Brain130(Pt5):1432–1441.
FernándezG,WeisS,Stoffel–WagnerB,TendolkarI,ReuberM,BeyenburgS,KlaverP,etal.(2003).MenstrualCycle–DependentNeuralPlasticityintheAdultHumanBrainIsHormone,Task,andRegionSpecific.TheJournalofNeuroscience23(9):3790–3795.
FoxMD,SnyderAZ,VincentJL,CorbettaM,VanEssenDC,andRaichleME(2005).Thehumanbrainis
51
intrinsicallyorganizedintodynamic,anticorrelatedfunctionalnetworks.ProceedingsoftheNationalAcademyofScienceUSA.102:9673–9678.
FranssonP,andMarrelecG(2008).Theprecuneus/posteriorcingulatecortexplaysapivotalroleinthedefaultmodenetwork:evidencefromapartialcorrelationnetworkanalysis.NeuroImage42:1178–1184.
FriedericiAD(2012).Thecorticallanguagecircuit:fromauditoryperceptiontosentencecomprehension.TrendsinCognitiveSciences16(5):262–268.
FriedericiAD,RüschemeyerSA,HahneA,andFiebachCJ(2003).Theroleofleftinferiorfrontalandsuperiortemporalcortexinsentencecomprehension:localizingsyntacticandsemanticprocesses.CerebralCortex(13):170–177.
FuCH,MorganK,SucklingJ,WilliamsC,AndrewC,VythelingumGN,andMcGuirePK(2002).Afunctionalmagneticresonanceimagingstudyofovertletterverbalfluencyusingaclusteredacquisitionsequence:Greateranteriorcingulateactivationwithincreasedtaskdemand.NeuroImage17(2):871–879.
GauffinH,FlensnerG,andLandtblomAM(2011).Livingwithepilepsyaccompaniedbycognitivedifficulties:youngadults’experiences.Epilepsy&Behavior22:750–758.
GeschwindN(1965).Disconnexionsyndromesinanimalsandman.I.Brain88:237–294.
GlasserMF,andRillingJK(2008).DTItractographyofthehumanbrain’slanguagepathways.CerebralCortex18(11):2471‐2482.
GoenseJ,WhittingstallK,andLogothetisNK(2012).NeuralandBOLDresponsesacrossthebrain.WIREsCognitiveScience3:75–86.
GreenbergDL,KeaneMM,RyanL,andVerfaellieM(2009).Impairedcategoryfluencyinmedialtemporallobeamnesia:Theroleofepisodicmemory.JournalofNeuroscience29:10900–10908.
GroenMA,WhitehouseAJO,BadcockNA,andBishopDVM(2012).Doescerebrallateralizationdevelop?AstudyusingfunctionaltranscranialDopplerultrasoundassessinglateralizationforlanguageproductionandvisuospatialmemory.BrainandBehavior2(3):256–269.
GuilfordJP,ChristensenPR,MerrifieldPR,andWilsonRC(1978).Alternateuses:manualofinstructionandinterpretation.SheridanPsychologicalServices,Orange,CA.
GüntürkünO,DiekampB,MannsM,NottelmannF,PriorH,SchwarzA,andSkibaM(2000).Asymmetrypays:visuallateralizationimprovesdiscriminationsuccessinpigeons.CurrentBiology10(17):1079–1081.
HaierRJ,SiegelB,TangC,AbelL,andBuchsbaumMS(1992).Intelligenceandchangesinregionalcerebralglucosemetabolicratefollowinglearning.Intelligence16(3–4):415–426.
HeimS,EickhoffSB,andAmuntsK(2009).DifferentrolesofcytoarchitectonicBA44andBA45inphonologicalandsemanticverbalfluencyasrevealedbydynamiccausalmodelling.NeuroImage48(3):616–624.
HeimS,GrandeM,MeffertE,EickhoffSB,SchreiberH,KukoljaJ,ShahNJ,etal.(2010).Cognitivelevelsofperformanceaccountforhemisphericlateralisationeffectsindyslexicandnormallyreadingchildren.NeuroImage53(4):1346–1358.
Hertz–PannierL,GaillardWD,MottSH,Cuenod,CA,BookheimerSY,WeinsteinS,ConryJ,etal.(1997).Noninvasiveassessmentoflanguagedominanceinchildrenandadolescentswith
52
functionalMRI:Apreliminarystudy.Neurology48(4)1003–1012.
HirnsteinM,LeaskS,RoseJ,andHausmannM(2010).Disentanglingtherelationshipbetweenhemisphericasymmetryandcognitiveperformance.BrainandCognition73(2):119–127.
HjelmervikH,WesterhausenR,OsnesB,ByholtEndresenC,HugdahlK,HausmannM,andSpechtK(2012).Languagelateralizationandcognitivecontrolacrossthemenstrualcycleassessedwithadichotic–listeningparadigm.Psychoneuroendocrinology37(11):1866–1875.
HugdahlK(1995).Dichoticlistening:probingtemporallobefunctionalintegrity.In:RJDavidson,andKHugdahl(Editors),BrainAsymmetry:pp123–156.Cambridge,MA,MITPress.
HugdahlK(2011).Fiftyyearsofdichoticlisteningresearch–Stillgoingandgoingand….BrainandCognition76(2):211–213
HugdahlK,WesterhausenR,AlhoK,MedvedevS,LaineM,andHämäläinenH(2009).Attentionandcognitivecontrol:unfoldingthedichoticlisteningstory.ScandinavianJournalofPsychology50(1):11–22.
JosseG,KherifF,FlandinG,SeghierML,andPriceCJ(2009).PredictingLanguageLateralizationfromGrayMatter.TheJournalofNeuroscience29(43):13516–13523.
JungRE,andHaierRJ(2007).Theparieto–frontalintegrationtheory(P–FIT)ofintelligence:convergingneuroimagingevidence.BehavioralandBrainSciences30:135–154.
JustMA,CarpenterPA,KellerTA,EddyWF,andThulbornKR(1996).Brainactivationmodulatedbysentencecomprehension.Science274:114–116.
KaanE,andSwaabTY(2002).Thebraincircuitryofsyntacticcomprehension.TrendsinCognitiveSciences6(8):350–356.
KaplanE,GoodglassH,andWeintraubS(1983).BostonNamingTest.Philadelphia:Lea&Febiger.
KeihlK,LiddleP,SmithA,MendrekA,ForsterB,andHareR(1999).Neuralpathwaysinvolvedintheprocessingofconcreteandabstractwords.HumanBrainMapping7:225–233.
KellyAM,UddinLQ,BiswalBB,CastellanosFX,andMilhamMP(2008).Competitionbetweenfunctionalbrainnetworksmediatesbehavioralvariability.NeuroImage39:527–537.
KimuraD(1992).Sexdifferencesinthebrain.ScientificAmerican267:118–125.
KimuraD(2011).Fromeartobrain.BrainandCognition76(2):214–217.
KnechtS,DeppeM,DragerB,BobeL,LohmannH,RingelsteinEB,andHenningsenH(2000).Languagelateralizationinhealthyright‐handers.Brain123:74–81.
KonradA,VucurevicG,MussoF,andWintererG(2012).VBM‐DTIcorrelatesofverbalintelligence:apotentiallinktoBroca’sarea.JournalofCognitiveNeuroscience24(4):888‐895.
LaaksoK,BrunnegårdK,HarteliusL,andAhlsénE(2000).Assessinghigh‐levellanguageinindividualswithmultiplesclerosis:Apilotstudy.ClinicalLinguistics&Phonetics14(5):329.
LangerN,PedroniA,GianottiLRR,HänggiJ,KnochD,andJänckeL(2012).Functionalbrainnetworkefficiencypredictsintelligence.HumanBrainMapping33:1393–1406.
LeeD,SwansonSJ,SabsevitzDS,HammekeTA,WinstanleyFS,PossingET,andBinderJR(2008).FunctionalMRIandWadastudiesinpatientswithinterhemisphericdissociationoflanguagefunctions.Epilepsy&Behavior13:350–356.
53
LogothetisNK,PaulsJ,AugathM,TrinathT,andOeltermannA.(2001).NeurophysiologicalinvestigationofthebasisofthefMRIsignal.Nature412:150–157.
LustJM,GeuzeRH,GroothuisAGG,vanderZwan,BrouwerWH,vanWolffelaarPC,andBoumaA(2011).Drivingperformanceduringwordgeneration—TestingthefunctionofhumanbrainlateralizationusingfTCDinanecologicallyrelevantcontext.Neuropsychologia49(9):2375–2383.
MariniC,KingMA,ArcherJS,NewtonMR,andBerkovicSF(2003).Idiopathicgeneralisedepilepsyofadultonset:clinicalsyndromesandgenetics.JournalofNeurology,Neurosurgery,andPsychiatry74:192–196.
MashalN,FaustM,andHendlerT(2005).Theroleoftherighthemisphereinprocessingnonsalientmetaphoricalmeanings:ApplicationofprincipalcomponentsanalysistofMRIdata.Neuropsychologia43(14):2084–2100.
MashalN,FaustM,HendlerT,andJung–BeemanM(2009).AnfMRIstudyofprocessingnovelmetaphoricsentences.Laterality14(1):30–54.
Maxwell AE, Fenwick PBC, Fenton GW, and Dollimore J (1974). Reading ability and brain function: A simple statistical model. Psychological Medicine 4: 274–280.
McGillML,DevinskyO,KellyC,MilhamM,CastellanosFX,QuinnBT,DuBoisJ,etal.(2012).Defaultmodenetworkabnormalitiesinidiopathicgeneralizedepilepsy.Epilepsy&Behavior23(3):353–359.
McKiernanKA,D’AngeloBR,KaufmanJN,andBinderJR(2006).Interruptingthe”streamofconsciousness”:anfMRIinvestigation.NeuroImage29:1185–1191.
MedinaLS,BernalB,andRuizJ(2007).RoleoffunctionalMRindetermininglanguagedominanceinepilepsyandnonepilepsypopulations:aBayesiananalysis.Radiology242(1):94–100.
MeylerA,KellerTA,CherkasskyVL,LeeD,HoeftF,Whitfield‐GabrieliS,GabrieliJD,etal.(2007).Brainactivationduringsentencecomprehensionamonggoodandpoorreaders.CerebralCortex17(12):2780–2787.
MitchellRLC,andCrowTJ(2005).Righthemispherelanguagefunctionsandschizophrenia:theforgottenhemisphere?Brain128(Pt5):963–978.
Neils‐StrunjasJ(1998).Clinicalassessmentstrategies:evaluationoflanguagecomprehensionandproductionbyformaltestbatteries.In:StemmerB,WhitakerHA,editors.Handbookofneurolinguistics.SanDiego(CA):AcademicPress71–82.61.
NeubauerAC,andFinkA(2009).Intelligenceandneuralefficiency.NeuroscienceandBiobehavioralReviews33(7):1004–1023.
NewmanSD,Tweig,DB,andCarpenterPA(2001).Baselineconditionsandsubtractivelogicinneuroimaging.HumanBrainMapping14:228–235.
NiskanenE,KönönenM,VillbergV,NissiM,Ranta–AhoP,SäisänenL,KarjalainenP,etal.(2012).TheeffectoffMRItaskcombinationsondeterminingthehemisphericdominanceoflanguagefunctions.Neuroradiology.54(4):393–405.
OcklenburgS,WesterhausenR,HirnsteinM,andHugdahlK.AuditoryHallucinationsandReducedLanguageLateralizationinSchizophrenia:AMeta–analysisofDichoticListeningStudies.JournaloftheInternationalNeuropsychologySociety.2013Jan18:1–9.[Epubaheadofprint]
PaulesuE,FrithU,SnowlingM,GallagherA,MortonJ,FrackowiakRSJ,andFrithCD(1996).Is
54
developmentaldyslexiaadisconnectionsyndrome?EvidencefromPETscanning.Brain119:143–157.
PeelleJE,McMillanC,MooreP,GrossmanM,andWingfieldA(2004).Dissociablepatternsofbrainactivityduringcomprehensionofrapidandsyntacticallycomplexspeech:EvidencefromfMRI.BrainandLanguage91:315–325.
PoduriA,andLowensteinD(2011).Epilepsygenetics—past,present,andfuture.CurrentOpinioninGenetics&Development21(3):325–332.
PratCS(2011).Thebrainbasisofindividualdifferencesinlanguage.Comprehensionabilities.LanguageandLinguisticsCompass5(9):635–649.
PratCS,andJustMA(2011).Exploringtheneuraldynamicsunderpinningindividualdifferencesinsentencecomprehension.CerebralCortex21(8):1747–1760.
PratCS,KellerTA,andJustMA(2007).Individualdifferencesinsentencecomprehension:Afunctionalmagneticresonanceimaginginvestigationofsyntacticandlexicalprocessingdemands.JournalofCognitiveNeuroscience19:1950–1963.
PratCS,MasonRA,andJustMA(2011).Individualdifferencesintheneuralbasisofcausalinferencing.BrainandLanguage116(1):1–13.
PriceCJ(2000).Theanatomyoflanguage:contributionsfromfunctionalneuroimaging.JournalofAnatomy197:335–359.
PriceCJ(2012).Areviewandsynthesisofthefirst20yearsofPETandfMRIstudiesofheardspeech,spokenlanguageandreading.NeuroImage62(2):816–847.
PriceCJ,Gorno‐TempiniML,GrahamKS,BiggioN,MechelliA,PattersonK,andNoppeneyU(2003).Normalandpathologicalreading:convergingdatafromlesionandimagingstudies.NeuroImage20:30–41.
PropperRE,O’DonnelLJ,WhalenS,TieY,NortonIH,SuarezRO,ZolleiL,etal.(2010).AcombinedfMRIandDTIexaminationoffunctionallanguagelateralizationandarcuatefasciculusstructure:Effectsofdegreeversusdirectionofhandpreference.BrainandCognition73(2):85‐92.
RamseyNF,JansmaJM,JagerG,vanRaaltenT,andKahnRS(2004).Neurophysiologicalfactorsinhumaninformationprocessingcapacity.Brain127(Pt3):517–525.
ReichleED,CarpenterPA,andJustMA(2000).Theneuralbasesofstrategyandskillinsentence‐pictureverification.CognitivePsychology40(4):261–295.
RocaM,ParrA,ThompsonR,WoolgarA,TorralvaT,AntounN,ManesF,etal.(2010).Executivefunctionandfluidintelligenceafterfrontallobelesions.Brain133:234–247.
RoskiesAL,FiezJA,BalotaDA,RaichleME,andPetersenSE(2001).Task‐dependentmodulationofregionsintheleftinferiorfrontalcortexduringsemanticprocessing.JournalofCognitiveNeuroscience13(6):829–843.
RuffRM,LightRH,ParkerSH,andLevinHS(1997).Thepsychologicalconstructofwordfluency.BrainandLanguage57:394–405.
SakaiKL,HashimotoR,andHomaeF(2001).Sentenceprocessinginthecerebralcortex.NeuroscienceResearch39:1–10.
55
SalmelinR,KiesiläP,UutelaK,ServiceE,andSalonenO(1996).Impairedvisualwordprocessingindyslexiarevealedwithmagnetoencephalography.AnnalsofNeurology,40:157–162.
SchmidtGL,andSegerCA(2009).Neuralcorrelatesofmetaphorprocessing:therolesoffigurativeness,familiarityanddifficulty.BrainandCognition71:375–386.
SeghierML,andPriceCJ(2012).FunctionalHeterogeneitywithintheDefaultNetworkduringSemanticProcessingandSpeechProduction.FrontiersinPsychology3:281.
SeghierML,JosseG,LeffAP,andPriceCJ(2011a).Lateralizationispredictedbyreducedcouplingfromthelefttorightprefrontalcortexduringsemanticdecisionsonwrittenwords.CerebralCortex21(7):1519–1531.
SeghierML,KherifF,JosseG,andPriceCJ(2011b).RegionalandHemisphericDeterminantsofLanguageLaterality:ImplicationsforPreoperativefMRI.HumanBrainMapping32(10):1602–1614.
ShaywitzSE,ShaywitzBA,PughKR,FullbrightRK,ConstableRT,MenciWE,ShankweilerDP,etal.(1998).Functionaldisruptionintheorganizationofthebrainforreadingindyslexia.ProceedingsoftheNationalAcademyofSciencesUSA95:2636–2641.
SheldonS,andMoscovitchM(2012).Thenatureandtime–courseofmedialtemporallobecontributionstosemanticretrieval:AnfMRIstudyonverbalfluency.Hippocampus22:1451–1466.
SidtisJJ(2007).Someproblemsforrepresentationsofbrainorganizationbasedonactivationinfunctionalimaging.BrainandLanguage102(2):130–140.
SimićN,andSantiniM(2012).Verbalandspatialfunctionsduringdifferentphasesofthemenstrualcycle.PsychiatriaDanubina24(1):73–79.
SimosPG,BreierJI,FletcherJM,BergmanE,andPapanicolaouAC(2000).CerebralMechanismsInvolvedinWordReadinginDyslexicChildren:aMagneticSourceImagingApproach.CerebralCortex10:809–816.
SmitsM,Visch‐BrinkE,Schraa‐TamCK,KoudstaalPJ,andVanderLugtA(2006).FunctionalMRimagingoflanguageprocessing:anoverviewofeasy‐to‐implementparadigmsforpatientcareandclinicalresearch.Radiographics26:145–158.
SnijdersTM,VosseT,KempenG,vanBerkumJJ,PeterssonKM,andHagoortP(2009).Retrievalandunificationofsyntacticstructureinsentencecomprehension:anFMRIstudyusingword–categoryambiguity.CerebralCortex19:1493–1503.
SommerIE,AlemanA,SomersM,BoksMP,andKahnRS(2008).Sexdifferencesinhandedness,asymmetryoftheplanumtemporaleandfunctionallanguagelateralization.BrainResearch1206:76–88.
SpringerJA,BinderJR,HammekeTA,SwansonSJ,FrostJA,BellgowanPSF,BrewerCC,etal.(1999).Languagedominanceinneurologicallynormalandepilepsysubjects:afunctionalMRIstudy.Brain122(11):2033–2046.
SturnioloMG,andGallettiF(1994).Idiopathicepilepsyandschool–achievement.ArchiveofDiseaseinChildhood70:424–428.
SzaflarskiJP,BinderJR,PossingET,McKiernanKA,WardBD,andHammekeTA(2002).Languagelateralizationinleft–handedandambidextrouspeople:fMRIdata.Neurology59(2):238–244.
SzaflarskiJP,SchmithorstVJ,AltayeM,ByarsAW,RetJ,PlanteE,andHollandSK(2006).A
56
longitudinalfunctionalmagneticresonanceimagingstudyoflanguagedevelopmentinchildren5to11yearsold.AnnalsofNeurology59:796–807.
ThirionB,PinelP,TucholkaA,RocheA,CiuciuP,Mangin,J‐F,andPolineJB(2007).StructuralanalysisoffMRIdatarevisited:ImprovingthesensitivityandreliabilityoffMRIgroupstudies.IEEETransactionsonMedicalImaging26(9):1256–1269.
ThompsonPM,CannonTD,NarrKL,vanErpTGM,PoutanenVP,HuttunenM,Lönnqvist,etal.(2001).Geneticinfluencesonbrainstructure.NatureNeuroscience4(12):1253–1258.
VanLancker‐SidtisD(2006).Doesfunctionalneuroimagingsolvethequestionsofneurolinguistics?BrainandLanguage98:276–290.
VigneauM,BeaucousinV,HervéPY,DuffauH,CrivelloF,HoudéO,MazoyerB,etal.(2011).Meta‐analyzinglefthemispherelanguageareas:Phonology,semantics,andsentenceprocessing.NeuroImage30:1414–1432.
VulE,HarrisC,WinkielmanP,andPashierH(2009).PuzzlinglyhighcorrelationsinfMRIstudiesofemotion,personality,andsocialcognition.Perspectivesonpsychologicalscience4(3):274–290.
WeberB,WellmerJ,SchurS,DinkelackerV,RuhlmannJ,MormannF,AxmacherN,etal.(2006).PresurgicallanguagefMRIinpatientswithdrug‐resistantepilepsy:Effectsoftaskperformance.Epilepsia47(5):880–886.
WoodAG,SalingMM,AbbottDF,andJacksonGD(2001).Aneurocognitiveaccountoffrontallobeinvolvementinorthographiclexicalretrieval:AnfMRIstudy.NeuroImage14:162–169.
XiongJ,RaoS,JerabekP,ZamarripaF,WoldorffM,LancasterJ,andFoxPT(2000).Intersubjectvariabilityincorticalactivationsduringacomplexlanguagetask.NeuroImage12(3):326–339.
YangFG,EdensJ,SimsponC,andKrawczykDC(2009).Differencesintaskdemandsinfluencethehemisphericlateralizationandneuralcorrelatesofmetaphor.BrainandLanguage111(2):114–124.
ZwaanRA,andRadvanskyGA(1998).Situationmodelsinlanguagecomprehensionandmemory.PsychologicalBulletin123:162–185.
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