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

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