EducationalNeuroscience

2014MeetingoftheEARLISIG22June12‐14,2014Göttingen,Germany

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Tableofcontents

Preface..............................................................................................................................5

AboutGöttingen...........................................................................................................7

Georg‐August‐UniversityGöttingen....................................................................8

TheHistoryofthePaulinerChurch.....................................................................9

GeneralInformation.................................................................................................12

MapofGöttingen........................................................................................................14

Programme..................................................................................................................18

Keynotelectures........................................................................................................20

Posterpresentations................................................................................................28

PostersessionA.........................................................................................................32

PostersessionB.........................................................................................................53

PostersessionC..........................................................................................................74

Participants..................................................................................................................95

Notes............................................................................................................................101

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Preface

DearParticipant,Weareverypleasedtowelcomeyoutothe3rdbiannualEARLISIG22NeuroscienceandEducationmeeting at theGeorg‐August‐UniversityGöttingen,Germany. Since its firstmeeting inZurich in2010 thebridgebetweenNeuroscienceandEducationhasbeenfurther strengthened and established. Today, thenumber of empirical studies in thisfieldisincreasinglyrising,whichsuccessfullydemonstratesthattheonceclaimedgulfbetweenneuroscienceandeducationmaynotbetoobigafterall.The2014programofthe SIG22 Neuroscience and Education meeting reflects these recent advances. ThequestionofwhetherEducationalNeuroscience isa fieldatthe2010meetinghasbeenpositivelyansweredandreplacedby thequestionofwhereandonwhat level can theneurosciencescontributetoquestionsofeducation.

Against thisbackground,weare verymuchpleased topresent anoutstanding list ofseven keynote speakers including Sian Beilock, University of Chicago, USA; EvelineCrone,Universiteit Leiden,NL; RolandH. Grabner,University of Göttingen, GER; YuliaKovas, Goldsmith University of London, UK; Nora Newcombe, Temple University,Philadelphia,USA;MichaelNitsche,GöttingenUniversityMedicalSchool,GER;andEricPakulak,UniversityofOregon,USA.

In addition to these keynote lectures, more than 70 poster proposals have beensubmitted to the conference this year from which 5 were selected for oralpresentationsandover60willbepresentedinthreedifferentpostersessions.Variousfields from learning and instruction, mathematics, reading, language development,sciencelearning,motivation,emotion,creativethinkingandgeneralcognitiveabilitieswill be presented in these sessions and will stimulate interesting theoretical andmethodological discussions. Hereby we would like to thank all presenters for theircontributionstotheSIG222014meeting.

We are also veryhappy to announce two important changes in thepresentmeeting.First,wehaveintroducedaposterawardforthebestposterpresentation.And,second,a conference dinner will take place to further support discussions among allparticipantsofthemeeting.

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We hope that you will enjoy the program and that you will have a stimulating andinteresting stay in Göttingen. We hope that the meeting will provide an excellentenvironmentforscientificexchangeandresearchcollaboration.

Lastbutnotleast,wewouldliketoexpressourgratitudetothemembersofthelocalorganizingteamaswellasthestudentassistantsandtotheEuropeanAssociationforResearchonLearningandInstruction(EARLI)whosupportstheSIGmeeting.

WewishyouagreattimeinGöttingen,

DanielAnsariBertDeSmedtRolandH.GrabnerStephanE.Vogel

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AboutGöttingen

Göttingen, the university city steeped in tradition, is situated right in themiddle ofGermany.Thiscity,withapproximately129.000inhabitantsofwhichmorethan25.000arestudents,ischaracterizedbyacreativeflairandauniqueatmosphere.

The village 'Gutingi', to which the city goes back, was first mentioned in 953 in adocument by Emperor Otto I. Today’s old town combines in a charming way thememoryofthemedievalmerchantcommunity(memberoftheHanseaticLeague1351‐1572)withtheambienceofamodernbusinesslocation.

With13facultiestheGeorg‐August‐University,foundedin1737,iswellrepresentedinnearlyallscientificdisciplines.Also,morethan40NobelPrizewinnersareassociatedwithitsname.

A plethora of sights from different eras shapes the special face of Göttingen, as forexample the double winged altar in St. Jacob’s church dating from 1402 or the OldTownHall(around1270/1369‐1443)withitsdecorationofthehallfromthelate19thCentury.

Averyspecialjewelisthe'Gänseliesel',thecity’slandmark.Thisartnouveaufigureisthedarling of all freshly promoteddoctors,whokiss her bronze cheeks after havingpassedtheirexams.

Colorful and diverse is also the cultural, historic and economic offer of the city. Thepedestrianzoneandcozybackstreetsinvitetoastrollandtoextensiveshoppingtours.In regard to the cultural sphere, Göttingen also impresses with an interesting anddiverse offer, like the international Händel Festival, the concerts of the GöttingenSymphonyOrchestraortheannual'Literaturherbst'.

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Georg‐August‐UniversityGöttingen

IN PUBLICA COMMODA ‐ FOR THE GOOD OF ALL reads the inscription on theFoundationMedalofthe“Georg‐August‐UniversitätGöttingen”.Established intheageoftheEnlightenment(1737)andcommittedtoitscriticalspirit,the"GeorgiaAugusta"was one of Europe's first universities to abandon the supremacy of theology andachieve equality for all faculties. Today the University is distinguished by the richdiversityof its subject spectrumparticularly in thehumanities, its excellent facilitiesfor the pursuit of scientific research, and the outstanding quality of the areas thatdefineitsprofile.

The University bears the name of its founder Georg August, King George II of GreatBritain,ElectorandDukeofBrunswick‐Lüneburg,(Hanover).Inaffinitywiththespiritof the Enlightenment, Göttingen abandoned the supremacy of theology and set itsfacultiesonanequalfooting.AsanacademiclocationGöttingenwaslongregardedasthehubofthemathematicalworld–apositionlost,however,in1933whenunderNazirulemorethan50professorsandlecturerswereforcedtoleavetheUniversity,amongthemseveralofthe44Nobellaureateswhosenamesareassociatedwiththecity.AftertheendofWorldWarII,GöttingenUniversitywasthe first inGermanytoresumeitsteaching operations and it went on to become one the largest higher educationinstitutions in the country.The foundingof theGöttingenUniversityLibrary in1734wasalandmark:Forthefirsttimeinlibraryhistorytheconceptofamodernresearchlibrary was put into practice and the institution became the first comprehensiveacademiclibraryofEuropeanstanding.

From2007to2012theGeorg‐August‐UniversityGöttingenwasrewardedwithfundingfromtheInitiativeofExcellenceoftheGermanFederalandStateGovernments.WithitsconstantlyexpandingrangeofMaster’sandPh.D.programmestheUniversitycultivatesexcellenceandoffersahighproximitytoresearch.Approximately26,300youngpeoplecurrently study here, some eleven per cent of whom are from abroad – a cleardemonstrationofthepullthattheUniversityhaslongexertedinternationally.

FormoreinformationabouttheGeorg‐AugustUniversity,pleasevisitthewebsite:

http://www.uni‐goettingen.de/en/the‐university/50217.html

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TheHistoryofthePaulinerChurch

ThePaulinerChurch –whichnow formspart of thehistorical building compoundofGöttingenStateandUniversityLibrary– isanarchitecturalmonumentof thehighestrank. It was the first church in Göttingen built in Gothic style and was used by theDominicans as part of their monastery (founded in 1294). The building reflects thearchitecturaltraditionofthemendicantorder.

WhenthereformationstartedinGöttingenin1529,theDominicanshadtostruggleforthe survival of theirmonastery. Since the town council hadno authority overparishchurchesthecityleadersdecidedtoholdLutheranservicesinthemendicantchurches,inparticularintheDominicanchurch,asitwasthetown’slargest.Thus,thePaulinerChurch was the place in Göttingen where the earliest protestant baptism wasadministered.

After secularization in the sixteenth century, a grammar school was set up in theformer Dominican monastery and soon enjoyed widespread reputation. The schoolformedtheheartofwhatlaterbecametheuniversity(foundedin1737)anditslibrary(foundin1734already).

Initiallythechurchwasusedforreligiousservices,butsoonthesewereheldelsewheresince therewasnot sufficientspace for therapidlygrowing library.Gradually it tookovertheentirebuildingcomplexincludingthePaulinerChurchitself.

In1812, JérômeNapoleonhadamezzanine floor inserted intothechurch.Theupperstoreythuscreatedwastransformedintoalibraryhall,inaharmonicblendofGothicandClassicstyleasitcanbeseenagaintoday.

Goethe,HeinrichHeine,andtheGrimmBrothersvisitedthelibraryfrequently.JohannWolfgangvonGoethewasoneof themostardentadmirersof the libraryandakeenuserofitsholdings.ForChristianGottlobHeyne,professorandlibrarianinGöttingen,the “HistoricalHall” (thename stems from the fact that thehistorybookswerekepthere),constitutedtheculminationofdecadesofhardwork.HeinrichHeinemadethishalltheclimaxofthelibrarydreaminhisHarzreise.

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InWorldWarII,thePaulinerChurchwasdestroyed.Afteritsreconstruction,thebookhallwas first used as the largest lecturehall. Later it housed theUnionCatalogueofLower Saxony. Since moving into its new building in 1992, Göttigen State andUniversity Library has used the hall as an exhibition room. Successful exhibitions ofnational importance,suchas “WagnisderAufklärung–GeorgChristophLichtenberg”[VenturingtheEnlightment–GeorgChristophLichtenberg],“700JahrePaulinerkirche”[Seven‐hundredyearsPaulinerChurch],and“Goethe,GöttingenunddieWissenschaft”[Goethe,Göttingenandscience]werepresentedthere.

With“GutenbergundseineWirkung”[Gutenbergandhiseffects]inJune2000,thehallwasreopenedto thepublicagain in itshistorical from–with theadditionof theair‐conditioned and high‐security Schatzhaus, allowing for the display of very valuableitems. The Pauliner Church is not only a venue for public exhibitions; it provides aspecialambienceforpubliceventsaswell.

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GeneralInformation

Localorganizingcommittee(Georg‐August‐UniversityGöttingen,Germany)

RolandH.GrabnerChristianHahnFriederL.SchillingerMariaSchneider StephanE.Vogel

Scientificcommittee

RolandH.GrabnerGeorg‐August‐UniversityGöttingen,Germanyroland.grabner@psych.uni‐goettingen.deBertDeSmedtKULeuven,Belgiumbert.desmedt@ped.kuleuven.beDanielAnsariUniversityofWesternOntario,Canadadaniel.ansari@uwo.ca

Meetingsecretariat

e‐mail:neuroedu.sig22@gmail.com

Meetingvenue

PaulinerkirchePapendiek1437073Göttingen

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Sponsors

EuropeanAssociationforResearchonLearningandInstruction(EARLI)

Internetaccess

Awirelessnetworkisavailableatthepremiseoftheconference.ThefollowingSSIDsareavailabletoyourwirelessdevices:eduroam(recommended)Thisserviceisencrypted.Inordertouseeduroamanaccountwithaninstitutionthatispartoftheeduroamnetworkisrequired.

GoeMobileThisserviceisunencrypted.Afteropeningawebbrowseraportalpageisavailableforlogintotheservice.Aguestaccountisrequiredforlogin:seecouponinyourwelcomepackage.

Posterinformation

The posters are presented in the poster room at themeeting venue. The posterwallsarenumbered fromA1 toA21, fromB1 toB21,and fromC1 toC21 for thepostersessionsA(Fridaymorning),B(Fridayafternoon),andC(Saturday).Youcanfindyourposternumberintheoverviewofpostersonpages28‐31.Pleasesetupyourposterduring thecoffeebreaksonFriday forsessionAandB,andduringthecoffeebreakonSaturdayforsessionC.Pleaseremoveyourposterafterthepostersession.Thepresentingauthorsareaskedtobepresentduringthepostersession.

CoffeebreaksandLunch

Inthecoffeebreaks,hotandcolddrinksaswellassomesnacksareofferedtoyou.There is no organized lunch for themeeting participants butwewill provide anoverviewofrestaurantsneartheconferencevenue.

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MapofGöttingen

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ImportantLocations1 ConferenceVenue(focusupperleft)

2 MainStation

3 BusStopGronerStraße

4 ConferenceDinner(RestaurantBullerjahn)

5 DepartmentofEducationalNeuroscience

6 Georg‐Elias‐Müller‐InstituteofPsychology

Directions

The conference takes place in the 1st floor of thePaulinerkirche ( 1 ) ‒ a formermonasteryintheheartofGöttingen.Youcanaccessthevenueconvenientlybyfootfrommostpartsofthecity,includingthemainstation( 2 )andthemajorityofho‐tels.Takingapublicbus,youcaneithergotomainstationandcontinueonfoot,orswitchtoline3,5‐10,13,28or29exitingatGronerStraße( 3 ).Theentrancetothevenue is locatedatPapendiek14 (see focuson themap),andcanbeaccessedviaGoetheallee/Prinzenstaße(blueline),orviaGroner/Groner‐TorStraße(redline).

Lunchmap

ThecitycenterofGöttingenoffersample lunchanddinneropportunities.Thefol‐lowinglistisashortselectionofrestaurantsaroundtheconferencevenuewithin‐dicationofpriceranges(€:<10,€€:10‐20,€€€:>20Euro).

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FalafelPoint € Goodfalafel

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Fellini €€ Italiancuisine

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Gauß €€€ Internationalcuisine

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Glöckle € Bratwurst(meatonly)

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Kartoffelhaus €€ Germancuisine

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RaniDhaba € Indianfood

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Shirini € Persianvegetarianfood

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Sternwarte (Planea) €€€ Internationalcuisine

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Szültenbürger €€ East‐Europeancuisine

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VillaCuba €€ Caribbeancuisine

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Programme

Thursday,June12,2014

15.00 Welcomeaddress

15.30 Keynotelecture1:GeneticsforEducation:thegood,thebadandtheugly.YuliaKovas,GoldsmithsUniversityofLondon,UK

16.30 Coffeebreak

17.00 Oralpresentations(until18.45)

Friday,June13,2014

09.00 Keynotelecture2:Alongitudinalanalysisofbraindevelopmentinrelationtocognitivecontrolandrewardsensitivity.EvelineA.Crone,LeidenUniversity,NL

10.00 Coffeebreak

10.30 Keynotelecture3:Neurocognitivemechanismsunderlyingmathematicalcompetencies.RolandH.Grabner,UniversityofGöttingen,GER

11.30 PosterSessionA

12.30 Lunchbreak

14.00 Keynotelecture4:Academicperformanceunderstress.SianBeilock,UniversityofChicago,USA

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15.00 Keynotelecture5:Thinkingaboutquantity:Theintertwineddevelopmentofspatialandnumericalcognition.NoraNewcombe,TempleUniversity,Philadelphia,USA

16.00 Coffeebreak

16.30 PosterSessionB(until17.30)

19.30 Conferencedinner

Saturday,June14,2014

09.00 Keynotelecture6:Development,implementation,andassessmentofanevidence‐basedtrainingprogramforat‐riskpreschoolers.EricPakulak,UniversityofOregon,USA

10.00 Coffeebreak

10.30 PosterSessionC

11.30 Keynotelecture7:Neuromodulatorybrainstimulation:Basicsandfunctionalimplications.MichaelNitsche,GöttingenUniversityMedicalSchool,GER

12.30 Closingaddress

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Keynotelectures

Thursday,June12,201415:30

Geneticsforeducation:thegood,thebadandtheugly.

YuliaKovasGoldsmithsUniversityofLondon,UKThe talk considers potential contributions of genetics to education, the general viewaboutgeneticsineducation,andattemptstodatetoidentifyspecificgenesthroughoutthe genome responsible for ubiquitous genetic influence. Many important foreducation findings have recently emerged from genetic research, suggesting thatgenetic effects are not static or deterministic, but change throughout life and indifferenteducationalandculturalcontexts.Forexample,academicachievement‐suchas performance in reading, language andmathematics ‐ has been found to be highlyheritable throughout school education in the UK. On the contrary, heritability ofgeneral cognitive ability is only moderate in the early school years and increasesgradually,reachingsubstantiallevelsinadulthood.Itispossiblethathighheritabilityofreadingandmathematicscanbeexplainedbythehighhomogeneityofeducationalenvironments. For example, the UK National Curriculum is highly uniform andthereforemaydecreasetheenvironmentalcontributiontothevarianceinthesetraits.On the contrary, general cognitive ability is not explicitly taught at schools, andthereforemay be under highly variable environmental influences across individuals,especiallyearlyindevelopment.Aschildrengothroughschool,theymaybegintousetheir acquired new skills in ways to further develop their general cognitive ability.Gene‐environmentcorrelations,wherebychildrenexperience,modify,andselecttheirenvironments,maycontributetotheobservedincreaseinheritabilityofIQ.Iwillalsodescriberecentadvancesinmoleculargeneticandgenomicresearchintotheaetiologyofindividualdifferencesineducationallyrelevanttraits.

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Friday,June13,201409.00

Alongitudinalanalysisofbraindevelopmentinrelationtocognitivecontrolandrewardsensitivity.

EvelineA.CroneLeidenUniversity,NLAdolescence is a natural time for explorative learning, risk taking and sensationseeking. Developmental neuroimaging studies including children, adolescents andadultsreportedprotracteddevelopmentofcorticalbrainregionswhichareimportantfor cognitive control, andheightenedactivation in reward related regions,withmostemphasis on the ventral striatum as a key brain region involved in reward seekingbehavior.Thesestudiesledtothehypothesisthatadolescentbraindevelopmentcanbeexplainedasanimbalancebetweenthedevelopmentofcorticalandsubcorticalbrainregions.However,moststudiesshowconsiderablevariabilitybetweenadolescents.This leadsto the question whether some adolescents develop faster than others, and whereassome adolescents are more sensitive to social‐affective influences than others. Animportant direction to understand this variability is by examining changes withinchildrenandadolescentsovertime.Thislongitudinalapproachhasseveraladvantagesover previously used cross‐sectional comparisons, for example, when there is largevariability between individuals, individual slopes aremore informative for detectingchangebecauseeachindividualatthesecondmeasurementprovidesitsowncontrolatthe first measurement. Second, a longitudinal design gives the possibility to usebehavioral and neuroimaging data to predict future behavioral outcomes. In a largestudy called ‘Braintime’, participants between ages 8‐27 yearswere scanned on twotimepoints,withatwoyearintervalinbetween,whileperformingacognitivecontroland a gambling task in the scanner. Outside of the scanner, participants completedquestionnairesforpuberty, impulsivity,workingmemory,readingandarithmetic.Weinvestigate whether neural responses in adolescence over time 1) are stable withinindividuals, 2) are related to age‐related changes and 3) are related to behavioralchangesovertime.

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Theneuroimagingresultssupportthemodelofprotracteddevelopmentofthefrontal‐cortical network and heightened ventral striatum response in early and mid‐adolescence.Theresultsfurthershowthatneuroimagingisavaluablemethodtodetectandpredict educational outcomes (reading, arithmetic).This studyprovides the firstproveforlongitudinalchangebytestingthewholerangeofadolescencewithmultiplemeasurements within each individual, and has the potential to unravel some of thepreviously suggested patterns and resolve inconsistencieswith respect to individualvariability.

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Friday,June13,201410.30

Neurocognitivemechanismsunderlyingmathematicalcompetencies

RolandH.GrabnerDepartmentofPsychology,Georg‐August‐UniversityofGöttingen,GERIn light of the increasingly recognized importance ofmathematical competencies forlife success, the number of educational neuroscience studies on school‐relevantmathematical cognition has remarkably grown in the past years. These studies havegenerated incremental knowledge on the cognitive and neural mechanisms ofmathematical information processing and have opened up new ways to treatmathematical learningdifficulties. In this talk, Iwillpresentevidence fromfunctionalmagnetic resonance imaging (fMRI), electroencephalography (EEG) and transcranialelectric stimulation (tES) studies, which illustrate the value added of neuroscientifictechniques in the investigation of questions related to mathematics education.Specifically, I will focus on individual differences in mathematical competencies,arithmetic problem‐solving strategies, and the potential to enhance mathematicslearning bymeans of non‐invasive brain stimulation. In addition, avenues for futureresearchwillbeoutlined.

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Friday,June13,201414.00

AcademicPerformanceunderStress

SianBeilockUniversityofChicago,USAFormanypeople,thedesiretoperformtheirbestinacademicsishigh.Consequencesforpoorperformance,especiallyinexaminations,includepoorevaluationsbymentors,teachers,andpeers;lostscholarships;andrelinquishededucationalopportunities.But,whydopoorperformances occur in those very situationswhere students are set ondoing their best? What cognitive and neural processes drive less‐than‐optimaloutcomeswhenthepressureishigh?And,canweuseknowledgeabouthowcognitivecontrolisalteredunderstresstoshedlightonwhysomepeoplethrivewhileothersfailinhigh‐stakessituations?Inthistalk,Iwilldiscussbehavioralandbrainimagingworkexamininghowstudents’knowledgeandgeneralcognitiveabilitiesinteractwithsocialand emotional factors (e.g., a student’s fear of test taking) to impact performance inacademicarenassuchasmath. Implications foreducationandassessment,aswellashow neuroscience can inform our understanding of the interplay of emotion andcognitivecontrolinacademicsettings,willbediscussed.

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Friday,June13,201415.00

ThinkingaboutQuantity:TheIntertwinedDevelopmentofSpatialandNumericalCognition

NoraNewcombeTempleUniversity,Philadelphia,USAThis talk considers how children and adults encode and reason about the manycontinuous dimensions that collectively define the physical world. Philosophical,psychological and neural work has focused especially on space and number, andsomewhat on time.However, there are other important continuousdimensions (e.g.,mass)andspacecanbebrokendownintodistinctdimensions(e.g.,perimeterversusarea).While formally distinct, variationon thesequantitativedimensions is typicallycorrelated,e.g., ifonemarchingbandhasmoremembersthananother,thatbandwillalsooccupymorespaceandtakelongertomarchpastthereviewingstand.Numberhasadistinctivecharacteristicamongthesedimensions,namelythatcountwordsandearlyteaching of arithmetic emphasize the discretization of numerical quantity. Debateconcerning the origins and development of quantitative thinking has centered onseveral questions: (1) whether a generalized magnitude system (see Walsh, 2003)exists,andifso,whetheritisastartingpointfordevelopment,anendpoint,orboth;(2)followingon from the answer to the first question,whetherdevelopment consists ofdifferentiation of a generalized magnitude system into separable dimensions, ormapping of separated processing systems onto each other, or a mixture of each atdifferent developmental points; (3) what factors lead to increasing precision inmagnitude estimation, both spatial and numerical. Answers to these questions haveeducationalimplications,e.g.,forteachingfractions.

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Saturday,June14,201409.00

Development,implementation,andassessmentofanevidence‐basedtrainingprogramforat‐riskpre‐schoolers.

EricPakulakUniversityofOregon,USAFor several yearswe have employedmultiple neuroimaging techniques to study thedevelopmentandplasticityof thehumanbrain. Over the courseof this researchwehave observed that different brain systems and related functions display different'profiles'ofneuroplasticity,orthedegreetowhichthesesystemsarechangeableandvulnerable.Guidedbythesefindings,wedevelopedatrainingprogramfor3‐5year‐oldchildrenwhoareatriskforschoolfailureforreasonsofpoverty.Thisprogramtargetschangeableandvulnerablesystemsforattentionandself‐regulationandincludesbothparentingandchildtrainingprograms.Relativetochildrenrandomlyassignedtooneof two comparison groups, children in our training program showed significantimprovementsinseveraldomainsincludingchildbrainfunctionssupportingselectiveattention, standardized measures of cognition, and parent‐reported child behaviors.Caregivers in the program also showed improved parenting behaviors and reducedparenting stress relative to the comparison groups. We are currently conducting alongitudinal follow‐up study to assess the degree to which these effects endure. Inaddition,wehaveculturallyadaptedandtranslatedtheprogramintoSpanishandarecurrently assessing the efficacy of this program when implemented with Latinofamilies. Finally,we are assessing the programwhenmore broadly implemented inpreschoolsandaretestinghypothesesthatparticipationinourprogramwillresult inimprovementsinstressphysiologyandself‐regulationinbothchildrenandcaregiversaswellasinlonger‐termimprovementsinfamilywell‐being.

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Saturday,June14,201411.30

Neuromodulatorybrainstimulation:Basicsandfunctionalimplications

MichaelNitscheGöttingenUniversityMedicalSchool,GERMajor physiological derivates of cognitive processes and behaviour are task‐specificalterations of cortical activity, and excitability. For learning and memory formation,even long‐lasting alterations take place. Functional imaging andelectroencephalographic methods have increased our knowledge about thesephysiological processes in the human brain largely.More recently, brain stimulationtoolshavebeendeveloped,whichareabletopromoteorcounteractthesephysiologicalalterations. These enable us to explore the causal relationship of physiological andcognitive behavioural processes. Moreover, these techniques might also be able toimprove functions. In this talk, an overview of effects and mechanisms ofneuromodulatory brain stimulation techniques will be given, including options toimprovefunctionsinhealthanddisease.

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Posterpresentations

PostersessionAFriday,June13,201411.30A1. Proportionalreasoning:InsightsfromapreliminaryEEGstudy.(Babaietal.)

A2. Ergometercyclingenhancesexecutivecontrolintaskswitching.(Barenbergetal.)

A3. Acute intense physical exercise fosters shifting performance in adolescents. (Berse etal.)

A4. Probing the nature of deficits in the 'Approximate Number System' in children withpersistentDevelopmentalDyscalculia?(Bugden&Ansari)

A5. Format‐dependent neural representations of numbers as revealed by multi‐voxelpatternanalysis.(Bulthéetal.)

A6. Thebenefitsofcomputer‐trainingprogramsonmentalcalculationforthedevelopmentofmathematicalabilities.(Caviolaetal.)

A7 Thenatureofabacus‐basedmentalcalculationtrainingisonekindofworkingmemorytraining:afunctionalMRIandbehaviorstudy.(Cheng&Chang)

A8. Non‐symbolic and Symbolic Magnitude Comparison Judgment Profiles in Children.(Chew&Reeve)

A9. Memory encoding and retrieval in children and young adults: ERP and oscillatoryevidenceforage‐relatedsimilaritiesanddifferences.(Czernochowski)

A10. The detrimental effect of interference in multiplication facts storing: typicaldevelopmentandindividualdifferences.(DeVisscher)

A11. DSM‐5 Impact on the Description and Prevalence of Learning Disorder in ADHDChildrenandAdolescents.(Dornelesetal.)

A12. Relationships between Cognitive and Behavioral Measures of Executive Function inPreschoolers.(Eversetal.)

A13. Approximatenon‐symbolicoperation,approximateandexactsymbolicoperations,andmathematicalproficiency.(Furman&Rubinsten)

A14. Looking for predictors of performance in single digit addition, subtraction andmultiplication:evidencefromaone‐yearlongitudinalstudy.(García‐Orza)

A15. Associationofphysicalactivityandsedentarybehaviorwithlearningoutcomesinadultstudents.(Gijselaersetal.)

A16. NeuralCorrelatesofself‐,friend‐andteacher‐evaluationsinadolescents‐lonelinessaspredictorandschoolself‐conceptasoutcome.(Goldeetal.)

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A17. Howdoesthemathematicalbraindevelop?AlongitudinalfMRIstudyinchildrenwithandwithoutdyscalculia.(Grondetal.)

A18 InvestigatingtheroleofthePPCinarithmeticfact learning:asimultaneoustDCS‐fMRIstudy.(Hauseretal.)

A19. IsImplicitMemoryIndependentfromSustainedAttention:AnEyeTrackingValidationStudy.(Ilgazetal.)

A20. TheKnowledgeandMisconceptionsofPrimaryandSecondarySchoolTeachersaboutthe Brain and Their Perceptions about Neuroscience in Education: AMixedMethodsResearchtoAnalysetheSituationinTurkeyin2013.(Karakus)

A21. Effectsofworking‐memorytrainingonacademicabilitiesinmiddlechildhood.(Karbachetal.)

PostersessionBFriday,June13,201416.30

B1. Raiseyourhandstospecify‐gesturesmeetingdorsalandventralstreamsforlearningmathematics.(Krause)

B2. Arelationshipbetweenbrainactivitydataandeye trackingdataduringmathematicaltasksfromtheviewofeducationalresearch.(Kuroda&Okamoto)

B3. Mind,Brain,andEducation:Acasestudyofstudentperceptionsofaninterdisciplinarygraduateprogram.(Lees)

B4. Brainactivityassociatedwithsolvinggeometryarea‐relatedproblems:effectofgeneralgiftednessandexcellenceinmathematics.(Leikinetal.)

B5. Brain activity associated with solving short insight‐based problems: focusing ongenerallygiftedandexcellinginmathematicsadolescents.(Leikinetal.)

B6. Dudeman&Sidegirl:OperationcleanWorld.AnewNumberGameusedtotrainNumberProcessingSkillsin5‐year‐olds.(Martens)

B7. Educational Neuroscience Applications: Memory of Multiplication Facts as a Model.(Mark‐Zigdon&Katzoff)

B8. Howthe1styearofformalschoolingshapessymbolicnumberdevelopment‐evidencefrombrainandbehavior.(Matejko&Ansari)

B9. Perceptualinformationinfluencestheformationofnumericalrepresentations:evidencefromanartificiallearningparadigm.(Merkley&Scerif)

B10. The relation between home numeracy, exact number skills and non‐symbolicaudiovisualmatchingabilities.(Mutafetal.)

B11. Field Dependence‐Independence cognitive construct and the human brain: A neuro‐educationalapproach.(Nisiforou)

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B12. CognitiveChange:TheEffectsofAquaticMotorActivitiesonEarly‐ChildhoodMotorandCognitiveDevelopment.(Nissimetal.)

B13. Kindergarten Children's Number Comparison Skills Predict First Grade Math Scores:EvidencefromaTwo‐minuteTest.(Nosworthyetal.)

B14. Neural efficiency inworkingmemory tasks: The impact of taskdemand and training.(Nussbaumeretal.)

B15. HowExpertMathematiciansComparetheNumericalValuesofFractions:EvidencefromEyeMovements.(Obersteiner&Reiss)

B16. Morethansubitizing:Symbolicmanipulationsofnumbers.(Olkunetal.)

B17. Feedback's informative value as the driving force of the feedback‐related negativity(FRN).(Opitz)

B18. StructuralandFunctionalNeuroimagingofReadinginChildren.(Partanenetal.)

B19. Eye movements during dot enumeration: The influence of visual and numericalinformation.(Pauletal.)

B20. Neuralrepresentationsinvisualcortexfornumericalmagnitudespresentedindifferentformats.(Petersetal.)

B21. The association between digit comparison performance and individual differences inarithmeticunravelled.(Sasanguieetal.)

PostersessionCSaturday,15June,201410.30C1. NeuralCorrelatesofFatigueDuringTaskSwitching.(Plukaardetal.)

C2. ExploringMentalRepresentationsforLiteralSymbolsUsingthePrimingDistanceEffect.(Pollack&LeonGuerrero)

C3. From executive functions to number knowledge: Neuropsychological performance inPortuguesepreschoolers.(Rato&Castro‐Caldas)

C4. Symbolicnumericalprocessingdeficit inpeoplewithWilliamssyndrome.(Rousselle&Noël)

C5. Examiningtheproblemsizeeffect:atDCSandEEGstudy.(Rütscheetal.)

C6. MusicintheBaddeleymodelofworkingmemoryinTDandSLIchildren.(Sallat)

C7. Effects of psychological and physiological variables on students subjective stressexperience. A multilevel longitudinal analysis in naturalistic educational settings.(Sembill&Kärner)

C8. On thedevelopmentof themultiplication factnetwork inelementary school children.(Soltanlouetal.)

C9. Teachers'perceptionofthebrainfunctioninLatinAmerica.(SoniGarcíaetal.)

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C10. ProcessingnumericalOrdinality:isitacoreability?(Sury&Rubinsten)

C11. The neuroscience literacy of pre‐service special needs educators and predictors ofneuromythsandknowledge.(Tancigetal.)

C12. Neuromythsamongsecondaryandcollegeteachers.(Tardifetal.)

C13. Patternsofchangeinthecognition‐emotionrelationshippredictmathproblemsolving.(Trezise&Revee)

C14. Theinfluenceofreadingproblemsonbasicnumericalprocessinginchildrenwithandwithoutmathdifficulties.(Vaessen&Gerretsen)

C15. Cognitive andneural characteristicsofmathematicaldifficulties in childrenwithmildtraumaticbraininjury(mTBI).(VanBeek)

C16. Developmental specializationof theparietal cortex for symbolicnumericalmagnituderepresentation.(Vogeletal.)

C17. Thelinkbetweenpreschooler'sexecutivefunctionandtheoryofmind.(Volckaertetal.)

C18. Cognitiveinterventioninpreschoolers.(Volckaert)

C19. BrainactivityassociatedwithtranslationfromavisualtoasymbolicrepresentationinAlgebraandGeometry.(Waismanetal.)

C20. The borrowing effect in two‐digit subtraction: Developmental aspects and neuralcorrelates.(Woitschecketal.)

C21. Different developmental onsets of symbolic approximate arithmetic skills acrosscountries:Hownumbersarenamedmatters.(Xenidou‐Dervouetal.)

32

PosterSessionAA1.

Proportionalreasoning:InsightsfromapreliminaryEEGstudy.

ReuvenBabai1,RuthStavy1,OrlyRubinsten2andNachshonKorem2

1DepartmentofScienceEducation,SchoolofEducation,TelAvivUniversity,TelAviv,Israel2DepartmentofLearningDisabilities,FacultyofEducation,UniversityofHaifa,Haifa,Israel

Children and adults have great difficulty with proportional reasoning. Proportion involves the

comparisonoftworatiosandinordertocompareratiosonefrequentlyneedstoformfractions.

Fractions are regarded as one of the most difficult topics in primary schools and improper

fractionsrepresentsagreaterdifficultytothestudentsthanproperones.

ProportionalreasoningwasstudiedbyEEGon18adults.Theywereaskedtocomparedintensities

ofcoloroftwomixturesofredandwhitepaintdrops,representedbytwodigits,onecoloredred

andonewhite,i.e.,tojudgewhethertherightorleftmixturehadadarkershade(colorintensityof

eachmixture is determined by the ratio red/white). The 320 comparison of ratio stimuliwere

equallydividedbetweenratioswithproperandimproperfractions.

Behavioral findingsshowed,asexpected,significantlyhigheraccuracyrateandashorterRT for

proper fractions than for improper ones. With regards to the EEG findings, one of the major

findings was a significantly more negative peak for proper fractions around 150‐170ms post

stimulus. This early effect presumably arising from occipito‐temporal cortices suggests that a

distinction between proper and improper fractions occurs very early during the processing of

proportionalreasoning

33

A2.

Ergometercyclingenhancesexecutivecontrolintaskswitching.

JonathanBarenberg1,TimoBerse1,NikolasHenrion1andStephanDutke1

1UniversityofMuenster,Muenster,Germany

Numerous studiesexamining the roleofworkingmemory in learningprocesseshighlighted the

relevance of executive functions. In sports and neurosciences, several studies found beneficial

effects of physical exercise on executive functions that were supposed to be mediated by

neurophysiological processes. It was shown that even single bouts of exercise can improve

executiveperformanceininhibitiontasks.Butit’sunclearwhetherexecutiveperformanceintask

switchingparadigmscanalsobenefitfromphysicalexercise.Weexaminedtheimpactofintense

ergometercyclingontaskswitchingintwostudies.InStudy1,50participantsweretestedafter

cycling and after resting in two different sessions. The order of interventionswas randomized

acrossparticipants.Participantsonlyshowedreducedswitchcostafterexercisewhencyclingbut

notrestingcoincidedwithSession2.InStudy2,50participantsalsoperformedtaskswitchingin

two sessions but exercise was manipulated between participants in Session 2. Controlling for

baselineperformanceinSession1,participantswhocycledinSession2showedlowerswitchcost

than participantswho rested in Session 2. The results of both studieswill be discussed in the

contextoflearningprocessesinexecutivetasks.

34

A3.

Acuteintensephysicalexercisefostersshiftingperformanceinadolescents.

TimoBerse1,JonathanBarenberg1,StephanDutke1,KlausVölker1andStefanKnecht2

1UniversityofMuenster,Muenster,Germany2UniversityHospitalMuenster,Muenster,GermanyResearchontheinfluenceofphysicalexerciseoncognitionhasshownthatevenacuteexercisecan

have beneficial effects. Effect sizes seemed to vary at least partly due to the type of cognitive

demands and inter‐individual differences. With regard to the executive functions of working

memory,itisassumedthatneurophysiologicalchanges(e.g.,inthedopaminesystem)mediatethe

effect.Mostoftheseresultswereobtainedwithsamplesofadults.Asthereareonlyfewstudies

investigatingadolescentsandexecutiveperformanceishighlyrelevantinthecontextofeducation,

weinvestigated254students(13to17years).Participantsperformedashiftingtaskafteracute

intensephysicalexerciseonabicycleergometerandafteraperiodofrest.Theorderofconditions

was counterbalanced between participants. The experimental procedure was run in a mobile

laboratory at schools and inter‐individual difference variables (e.g., genetic markers) were

assessed.Afterexerciseweobservedreducedshiftcostscomparedtotherestingcondition.This

wasinterpretedasfirstevidenceforabeneficialeffectofphysicalexerciseonexecutivefunctions

in adolescents. Further analysis revealed that genetic polymorphisms affecting the dopamine

systempredictedperformanceinspecifictaskcomponentssuggestingdopaminergicmediation

35

A4.

Probingthenatureofdeficitsinthe'ApproximateNumberSystem'inchildrenwithpersistentDevelopmentalDyscalculia?

StephanieBugden1andDanielAnsari1

1UniversityofWesternOntario,London,Canada

In the present study we examined whether children with Developmental Dyscalculia exhibit a

deficit in the so‐called ‘ApproximateNumberSystem’ (ANS).Todo so,weexamined a groupof

childrenwhodemonstratedconsistentlylowmathachievementover4yearsandcomparedthem

totypicallydeveloping(TD),aged‐matchedcontrols.TheintegrityoftheANSwasmeasuredusing

the Panamath (www.panamath.org) dot discrimination test. Children with DD were found to

perform significantly worse on this test than the TD controls, suggesting an impaired ANS.

However, given recent findings showing that numerosity discrimination is affected by visual

parameterswewentfurtherandinvestigatedwhetherchildrenperformeddifferentlyontrialson

whichnumberofdotsandtheiroverallareawereeithercongruentorincongruent.Thisanalysis

revealedthatDDandTDchildrenonlydifferedontheincongruenttrials.Thustheiroveralldeficit

can be explained by a difficulty in extracting number from an array of dotswhen area is anti‐

correlated with number. These data converge with recent findings showing the importance of

inhibitorycontrolindotdiscriminationanddemonstratethatcloseattentionneedstobepaidto

perceptualprocessesinvokedbytaskspurportedtorepresentmeasuresoftheANS.

36

A5.

Format‐dependentneuralrepresentationsofnumbersasrevealedbymulti‐voxelpatternanalysis.

JessicaBulthé1,HansOpdeBeeck1andBertDeSmedt1

1KULeuven,Leuven,Belgium

Duringthelastdecadetherehasbeenaboostofneuroimagingresearchaboutnumericalcognition

in order to reveal the underlying neural mechanisms of number processing. However, most

researchhasmainly focusedontheactivationof theparietal lobe.To increaseknowledgeabout

numberprocessing,thereisaneedforunderstandingnumberprocessingnotonlyintheparietal

lobe,butalsoinotherbrainregions.IntwofMRIstudies(study1:n=16&study2:n=12)the

participantswere given a number comparison task.We performedmultiplemultivoxel pattern

analysis, allowing us to focus on the neural representations of the different digit and dots.We

looked into different ROIs in the occipital lobe, frontal lobe, temporal lobe and parietal lobe.

In the study 1we found different neural representations for symbols and dots in all the ROIs.

Therewas no evidence for overlapping neural representations, suggesting a format‐dependent

representationofnumbers.Inthestudy2,weshowedthatthelinkbetweensymbolsanddotswas

thenumberofvisual elementson the screenandnot thenumericalmagnitudeunderlyingboth

formats.TheseresultswereobservedinseveralROIsinthehumancortex,includingtheIPS.This

knowledgeofhownumbersareprocessedinthebrainmighthelpustofurtherunderstandhow

dyscalculiaemerges.

37

A6.

Thebenefitsofcomputer‐trainingprogramsonmentalcalculationforthedevelopmentofmathematicalabilities.

SaraCaviola1,IreneC.Mammarella1andCesareCornoldi2

1DepartmentofDevelopmentalPsychology,UniversityofPadova,Padova,Italy2DepartmentofGeneralPsychology,UniversityofPadova,Padova,Italy

There is increasing interest in developing programs for improving children’s mathematical

abilities.However,previousresearchfocusedontrainingintheapproximate(Dehaene,2009)and

exact(Butterworth,1999;2005)numbersystem,withunclearresultsconcerningtheirimpacton

arithmeticachievement(Wilson,etal.2009).Hence,inthepresentprojectwefocusedonmental

calculationtrainingbycomparingarepeatedpractice trainingorastrategy instructiontraining.

Childrenattending3rd(N=117)and5th (N=102)gradeswererandomlyassigned to3different

groups: a computerized strategic training on mental calculation problems; a computerized

practicetrainingonmentalcalculation;acontrolgroup(educationasusual).Childrenweretested

individuallyatthepre‐testandpost‐testwithtasksinvolvingmentalcalculationproblems,math

fluencyandwrittencalculations.Moreover,toassesstransfereffectsverbal,spatialandnumerical

reasoningweretested.Resultsshowedthatchildrenofboththestrategicandthepracticetraining

groupstookbenefits fromthe trainingwhencomparedto thecontrolgroup,by improvingtheir

speed(practice training)oraccuracy(strategic training)onmental calculations.Moreover,both

traininggroupsimprovedinmathfluencyandwrittencalculation.

38

A7.

Thenatureofabacus‐basedmentalcalculationtrainingisonekindofworkingmemorytraining:afunctionalMRIandbehaviorstudy.

JohnY.S.Cheng1,2andChun‐YenChang3

1GraduateInstituteofScienceEducation,NationalTaiwanNormalUniversity2DivisionofNeurosurgery,SurgicalDepartment,TaipeiMedicalUniversityH,Taipei,Taiwan3NationalTaiwanNormalUniversity,Taipei,Taiwan

Theaimsofourunique longitudinal studyare to evaluate the relatively short termeffectof six‐

month abacus‐basedmental calculation (AMC) training on the functional connectivity network,

andtoinvestigatethepossibilityofAMCtrainingeffecttransfertotheuntrainedworkingmemory

task.Abacusexpertshavedemonstratedextraordinarypotentialofmentalcalculationinthepast

cross‐sectional studies.Non‐experts showactivity in theprefrontal andperisylvianareas,while

experts, with long‐term training of at least three to five years, show more activation over

premotor and parietal regions. The trained children advanced 9.11 percentile on the WISC‐IV

exam’sworkingmemory subsection (from81.19 to 90.30, p = 0.037<0.05).Resting stateMRI

revealedincreasedconnectivitybetweentheleftinferiorfrontalareaandtheleftinferiorparietal

lobe.The combined results suggested six months of AMC training can generalize to untrained

workingmemoryexams,andamidwayparadigmshiftcanbeexpectedalongthefronto‐parietal

circuitrywithintherelativelylongtimerequiredtobecomeanexpert.Comparedtothecommon

practice of task repetition, AMC is not only an arithmetic operation, but an appropriate and

interesting tool to improveworkingmemory capabilities by exercising visuo‐motor and visuo‐

spatialskills.

39

A8.

Non‐symbolicandSymbolicMagnitudeComparisonJudgmentProfilesinChildren.

CindyChew1andRobertReeve1

1TheUniversityofMelbourne,Melbourne,Australia

Thespeedandaccuracywithwhichchildrencomparenon‐symbolicquantitiesandArabicdigits

predict their math problem solving abilities; and the significance of non‐symbolic judgments

diminishes with age. Some researchers assume that (1) little variation exists in non‐symbolic

magnitude (NSM) judgment abilities, (2) that NSM scaffolds symbolicmagnitude (SM) abilities,

and(3)difficultieswithSMreflectsNSM‐SMmappingdifficulties.Toevaluatetheseassumptions,

1606‐ to8‐year‐olds’NSMandSM judgment, visuo‐spatialworkingmemory (VSWM),number‐

linejudgment,numbernamingspeed,non‐verbalIQandRTabilitieswereassessed.Latentclass

analysis of NSM and SM speed and accuracy judgments yielded a five subgroup solution:

subgroupswereonlypartiallyrelatedtoage.VSWMandnumbernamingspeed,butnotRTnor

IQ, predicted subgroup membership. Subgroup membership was related to NL and number

namingspeed.OnesubgroupexhibitedgoodSMbutpoorNSMabilities;membersexhibitedthe

poorestNLandnumbernamingskills.PoorNSMandVSWMabilitieswereassociatedwithpoorer

mathabilities;butgoodSMabilitiesalonedonotguaranteegoodmathabilities.

40

A9.

Memoryencodingandretrievalinchildrenandyoungadults:ERPandoscillatoryevidenceforage‐relatedsimilaritiesanddifferences.

DanielaCzernochowski1

1TechnicalUniversityKaiserslautern,Kaiserslautern,Germany

Basedexclusivelyonbehavioraloutcome, it isdifficult todissociatememorydevelopment from

controlabilitiescontributingtomemoryjudgments.Despitepotentialimplicationsforeducation,

thecognitiveprocessesand functionalmaturityof thebrainregionssupportingmemoryduring

development are still largely unknown. ERPs and EEG oscillations allow real‐time tracking of

cognitiveprocessesduringbothmemoryencodingandretrievalonatrial‐to‐trialbasis.Here,we

compared children aged 7 and 10 years and young adults during incidental and intentional

memory encoding and retrieval. During intentional compared to incidental encoding, theta

oscillations were larger for frontal electrodes in young adults, and also for parietal sites in

children. During memory retrieval, participants distinguished between identical, perceptually

changedandnewpictures.Performanceincreasedforintentionalrelativetoincidentalencoding,

in particular for changed pictures, but recognition accuracy was age‐invariant. ERPs revealed

parietal old‐/new effects associatedwith recollection across age groups, but the topography of

earlier ERP effects changed with development. In sum, electrophysiological measures reveal

similaritiesanddifferencesinthecognitiveprocessesunderlyingepisodicmemoryintheabsence

ofperformancedifferences.

41

A10.

Thedetrimentaleffectofinterferenceinmultiplicationfactsstoring:typicaldevelopmentandindividualdifferences.

AliceDeVisscher1

1UniversitéCatholiquedeLouvain,Louvain‐la‐Neuve,Belgium

While different profiles of dyscalculia are suggested, thedifficulty tomemorize arithmetic facts

(AF,verysimplearithmeticproblemslike3x5)isageneralandpersistenthallmarkofthismath

learning disability. Recently, it has been suggested that hypersensitivity‐to‐interference in

memorycouldpreventsomeone instoringAF.The featuresoverlapbetweenAF issuggestedto

provoke interferenceand, learnerswhoarehypersensitive‐to‐interferencewould therefore face

difficulties instoringAF. In thispaper,wecreatedameasureof the interferenceweightofeach

multiplication.We first testedwhether the interferenceparameter canpredict theperformance

across multiplications, beyond the problem‐size. We reported data from third‐ and fifth‐grade

childrenandundergraduatestudents,data fromapublishedcasestudyofdyscalculiaaswellas

longitudinaldataof fourth‐grade‐children tested twice,oneyearapart.Results showed that the

interference parameter predicts a substantial part of the performance across multiplications.

Moreover, the individual sensitivity to the interference parameter determined a part of the

individual differences in multiplication performance in the three data sets. This finding

contributestotheunderstandingofthetypicalandatypicalarithmeticdevelopment.

42

A11.

DSM‐5ImpactontheDescriptionandPrevalenceofLearningDisorderinADHDChildrenandAdolescents.

BeatrizDorneles1,LucianaCorso1,AdrianaCosta1,NelbaPisacco1,YasminiSperafico1andLuisAugustoRohde1

1UFRGSFederalUniversityofRioGrandedoSul,PortoAlegre,Brazil

Prevalence studies on learning disabilities (LD) in children and adolescents with ADHD show

inconclusive results, despite the frequent comorbidity between these syndromes. This paper

describesandanalyzestheprevalenceofLDinareferredsampleof270childrenandadolescents

withADHDtreatedatAttention‐Deficit/HiperactivityDisorderProgramatHospitaldeClínicasde

PortoAlegre‐UFRGS,inPortoAlegre,Brazil,accordingtothediagnosticcriteriaoftheDSM‐IV‐TR.

We verify a high rate of comorbidity (46,7%) between the two disorders, and the Written

ExpressionDisorderistheprevalent(32,6%),resultsthatconfirmspreviousfindings.Thesedata

mustbeconsideredinschoolplanningandininterventionaleducationprograms,asweknowthat

whenbothdisordersappear together (Barkley,2008) students showattentionalandacademics

deficitsmore important than thatof childrenwithonlyoneof thedisorders.The impactof the

changesinthediagnosticcriteriaforLDproposedbyDSM‐5intheprevalenceofthesedisordersis

discussed.AlthoughchangeswilloccurintheratesofLDprevalence,theimpactofDSM‐5onthe

prevalence, specificity and comorbidity of LD remains uncertain, as there are some proposed

changesthatwillbroadenthescopeofthecriteriaandothersthatwillreduceit.

43

A12.

RelationshipsbetweenCognitiveandBehavioralMeasuresofExecutiveFunctioninPreschoolers.

WiebkeEvers1,LauraWalk1,SonjaQuante1andKatrinHille1

1ZNL–TransferZentrumfürNeurowissenschaftenundLernen,Ulm,Germany

Performanceincognitivetestsofexecutivefunctions(EF)doesnotalwayscorrespondtobehavior

and emotion regulation of children in real‐life situations. The aim of the present studywas to

assess the relationship between performance in cognitive EF tests, behavioral EF tests, and

teacherratingsofchildren’sself‐regulation.Three‐tosix‐yearoldchildren(119boys,104girls)

were administered. Cognitive EFwere assessed using four tests (Digit Span, Block Recall, Day‐

NightStroop,Dots)and twoputative testsofbehavioralEF (TowerBuilding,Head‐Toes‐Knees‐

Shoulders [HTKS]). For the teachers’ ratingswe used two dimensions of the observation scale

“Social‐emotionalwell‐beingandresilienceofchildreninearlychildhoodsettings”(PERiK):self‐

control/thoughtfulnessandtaskorientation.Wefoundthatallmeasuresdifferentiatewithregard

toage.CorrelationsbetweencognitiveEFmeasureswith theHTKSwereabout twiceashighas

theircorrelationswiththeTowerBuilding.ThisindicatesthattheHTKStapssimilarprocessesas

thecognitiveEFmeasures.Teacherratingsdidnotshowhighercorrelationswithbehavioralthan

with cognitive EF measures as it was expected as sampling frame is more similar. It will be

discussedtowhatextentadistinctionintocognitiveandbehavioralmeasuresofEFispossible.

44

A13.

Approximatenon‐symbolicoperation,approximateandexactsymbolicoperations,andmathematicalproficiency.

TamarFurman1andOrlyRubinsten1

1EdmondJ.SafraBrainResearchCenterfortheStudyofLearningDisabilities,DepartmentofLearningDisabilities,UniversityofHaifa,Israel

Numerical representations are thought to rely on two representation systems: symbolic (e.g.,

Arabicnumerals"6”ornumberwords)andapproximatenon‐symbolic(ANS)representation(e.g.,

groupofdots).Thefactthattheserepresentationsarerelatediswelldocumented.However,the

currentliteratureisinconclusiveregardingtheirrelationshipwithmathematicalproficiency.ANS

is commonly examined by comparison tasks, but recently some studies have focused on the

performanceofmathoperations(e.g.,addition).

Methods

Participants were presented with two inverse (X+Y‐Y) and non‐inverse (X+Y‐Z) computer

animations of mathematical operations. The first, represented addition and subtraction

operationsandthesecond,multiplyinganddivisionones.Allofthetaskswerepresentedinfour

formats:(1)ANSoperations(e.g.,operationsusinggroupsofdotsandestimatingtheresult),(2)

exactnon‐symbolicoperations (e.g., exact computationof the result), (3) approximate symbolic

operations (e.g., operations using numerals and estimating the result), (4) exact symbolic

operations(e.g.,exactcomputationoftheresult).

ResultsandConclusions

Relationshipswerefoundamongthefourtypesofoperationsandbetweenthemand

mathematicalproficiency.Thiswasfoundwhencontrollingworkingmemoryability.

45

A14.Lookingforpredictorsofperformanceinsingledigitaddition,subtractionandmultiplication:evidencefromaone‐yearlongitudinalstudy.

JavierGarcía‐Orza1,AlejandroEstudillo2,AntonioMatas1andAdamSánchez‐Urbano1

1UniversityofMalaga,Malaga,Spain2UniversityofKent,Canterbury,UK

Recent research has explored the numerical skills that act as predictors of arithmetic fact

knowledge.However,mostof thesestudiessuffer fromsomelimitations:somestudiesexplored

only the predictive role of one or two tasks; arithmetic fact knowledge has been considered

globally in some other studies; finally, some studies used a transversalmethodology instead a

longitudinal one. Here we explored the predictors of single‐digit addition, subtraction and

multiplication in a one‐year longitudinal study. The basic numerical skills of 70 studentswere

evaluatedattheendoffirst‐gradeandtheirperformanceatarithmeticoperationswasmeasured

at theendof second‐grade.Regressionanalyseswerecarriedoutseparately foreachoperation.

The performance in a non‐symbolic comparison task, an Arabic number comparison task, a

transcoding task (dictation of one‐ and two‐digit Arabic numbers), and a numerical sequence

counting task, were included as predictors. Results indicated differences between operations.

WhereasforadditionthepredictorwastheArabiccomparisontask,thesignificantpredictorsfor

multiplicationwere thedictationofArabicnumbers and thenon‐symbolic comparison task.No

significant predictors arose for subtraction. Results are discussed in relation to models of

arithmeticfactlearning.

46

A15.

Associationofphysicalactivityandsedentarybehaviorwithlearningoutcomesinadultstudents.

JérômeGijselaers1,RenateDeGroot1andPaulA.Kirschner1

1OpenUniversityoftheNetherlands,Heerlen,Netherlands

Physicalactivityandsedentarybehaviorarerelatedtolearningoutcomesinchildren.Researchin

adults, concerning this relationship, isnotapparent.Therefore,we investigated ifandhowthey

arerelatedinadultsparticipatingindistanceeducation.Dataontheindependentvariableswere

collectedviaanonlinesurveyatthestartofthestudy.Learningoutcomesweremeasuredbythe

amount of attained European Credits (EC’s) after 6 months. We corrected for possible

confounders. 1811 participants were included. A two‐hurdle model was used as different

predictorsmaymatterforeachhurdle.AlogisticregressionforattaininganyEC’s(1sthurdle)and

alinearregressionforthesubgroupthatattainedEC’s(2ndhurdle).Physicalactivitywasaslightly

negativepredictorforpassingthefirsthurdle.Themodelexplainedthedatafor13.6%ofwhich

physical activity added 0.6%. Possibly, time spent on physical activity in this specific group of

studentscoulddetractfromthetimetheyspentonlearning,asitislikelythattheirsparetimeis

limited. In addition, sedentary behavior was not associated with learning outcomes. Linear

regressiononthestudents thatpassedthe firsthurdledidnotyieldanysignificantassociations

forphysicalactivityorsedentarybehavior.

47

A16.

NeuralCorrelatesofself‐,friend‐andteacher‐evaluationsinadolescents‐lonelinessaspredictorandschoolself‐conceptasoutcome.

SabrinaGolde1,LydiaPöhland1,RobertLorenz1,PatriciaPelz1,AndreasHeinz1,DianaRaufelder2andAnneBeck1

1Charité‐UniversitätsmedizinBerlin,Berlin,Germany2FreeUniversityBerlin,Berlin,GermanyRecentmeta‐analyseshavearguedthattheventromedialprefrontalcortex(vMPFC)isspecifically

involved in self‐related cognitions. It isunknownwhether this region is also involved inneural

processing of close others in adolescents, such as friends and teachers. 41 adolescents judged

duringfMRIwhethertraitadjectivesdescribedeitherthemselves,theirfriendsortheirteachers.

Additionally, we used structural equationmodeling (SEM) to analyse the relationship between

loneliness,neuralresponsestoself‐,friend‐andteacher‐judgmentswithinthevMPFCandschool

self‐concept(SSC).fMRIanalysis(p<.05family‐wiseerrorcorrected)revealedhigheractivationin

the vMPFCduring self‐ and friend‐judgments than during teacher‐judgments. SEM showed that

loneliness negatively predicted activations in all judgment conditions. In turn, high response to

self‐judgments predicted a high SSC, high neural response to teacher‐judgments a low SSC.

Ourfindingsindicatethatfriendsmightbemorerelevanttotheselfofadolescentsthanteachers.

Furthermore,findingssuggestthatneuralprocessingofteachersin‘self‐specific’regionsisrelated

tolowerself‐ratingsofacademicabilities.Overall,lonelyadolescentskeepagreaterpsychological

distancetoothers,whichcouldexplainourresults.

48

A17.

Howdoesthemathematicalbraindevelop?AlongitudinalfMRIstudyinchildrenwithandwithoutdyscalculia.

UrsinaGrond1,MichaelvonAster1,2,RuthO'Gorman1,3,ErnstMartin1,3andKarinKucian1

1UniversityChildren’sHospital(CenterforMR‐Research,Children'sResearchCenter),Zurich,Switzerland2GermanRedCrossHospitalsWestend,Zurich,Switzerland3ZurichCenterforIntegrativeHumanPhysiology,Zurich,Switzerland

Childrenwith developmental dyscalculia (DD) show distinct problems in numerical processing

andaberrant activationof thenumericalnetwork compared to typicallydeveloping (TD)peers.

Cross‐sectional studies reveal a functional specialization of the numerical network over

development.Aimofthestudyistoinvestigatetheneuronaldevelopmentofnumericalabilitiesin

TDandDDchildrenbasedonlongitudinaldata.SeventeenchildrenwithDDand11TDchildren

between 7‐11 years were evaluated twice by neuropsychological tests and fMRI over a 4‐year

period. The behavioural results showed that childrenwithDDperformed significantly lower in

numericalskillsatbothtimepointsofthestudy.ThefMRIdatarevealedanactivationincreasein

the fronto‐parietal network of children with DD over time. In contrast, no difference in brain

activation was found in TD children. Furthermore, regression analysis revealed a negative

correlation between the activation increase over time and the number of correctly solved

subtractions and additions. The behavioural results of this longitudinal study confirm the

persistence of thedeficits in numerical processing inDD.On theneuronal level, developmental

activationpatternsinDDarelessfocusedcomparedtoTDchildrenandmightthereforereflecta

moreeffortfuluseofthenumericalnetwork.

49

A18.

InvestigatingtheroleofthePPCinarithmeticfactlearning:asimultaneoustDCS‐fMRIstudy.

TobiasHauser1,BrunoRütsche2,KarolineWurmitzer2,SilviaBrem1,ChristianRuff3andRolandGrabner4

1UniversityClinicsforChildandAdolescentPsychiatry(UCCAP),UniversityofZurich,Zurich,Switzerland2InstituteforBehavioralSciences,ETHZurich,Zurich,Switzerland3SocialandNeuralSystems(SNS)laboratory,UniversityofZurich,Zurich,Switzerland4Georg‐Elias‐Müller‐InstituteofPsychology,Georg‐August‐UniversitätGöttingen,Göttingen,Germany

Thedevelopmentofmathematicalskillsisacentralaimofformalschooling.Oneimportantstepto

achieve this aim is the acquisition of arithmetic skills, which is typically characterized by a

transitionfromtheapplicationofeffortfulcalculationstrategiestoanincreasinguseofarithmetic

factsfrommemory.Peoplesufferingfromdevelopmentaldyscalculiaoftenshowimpairmentsin

the establishment of arithmetic fact knowledge. Neuroimaging studies have revealed that the

posteriorparietalcortex(PPC)surroundingtheangulargyrus iscritically involvedinarithmetic

factretrieval.Inaddition,recentstudieshaveshownthatitispossibletomodulatemathematical

performancebymeansofnon‐invasivetranscranialDirectCurrentStimulation(tDCS)ofthePPC.

Inthisstudy,weusedsimultaneoustDCS‐fMRItoevaluatewhetherarithmeticfactlearningcanbe

positively influenced by brain stimulation and to investigate the neural correlates of these

learningeffects.Specifically,wecomparedtheeffectsofanodal,cathodalandshamstimulationon

performance in an arithmetic learning task and the accompanying brain activity. Our findings

provide a better understanding of the potential of tDCS to enhance learning and the neural

mechanismsunderlyingtheseeffects.

50

A19.

IsImplicitMemoryIndependentfromSustainedAttention:AnEyeTrackingValidationStudy.

HaleIlgaz1,ArifAltun1andPetekAskar1

1AnkaraUniversity,Ankara,Turkey2HacettepeUniversity,Ankara,Turkey3TEDUniversity,Ankara,Turkey

The aim of this study is to extend and verify whether implicit memory is independent from

sustainedattentioninadigitalenvironment.15undergraduatestudents(7malesand8females;

mean age 22) atHacettepeUniversity participated in this study. For directing the participants’

attention, contextual cueing paradigm was used. A computer based test with Multiple Object

Tracking (MOT) paradigmwas used for identifying participants’ sustained attention levels. The

testwasrunonatouchscreenmonitorandconsistedoffourdifficultylevels:demonstration,easy,

mediumandhard.Meanscores fromeach levelwerecalculatedassustainedattentionscore for

eachparticipant.Anovelformofashortstorywasdesignedwithtwodifferenttypesofcontextual

cueing(staticanddynamic) inaweb‐basedenvironment.Oncethereadingtaskwascompleted,

participants had given a simple mathematical operations test as a distraction task. After

distraction task, learners are requested to complete aword stemcompletion task.Each correct

responsewasgivenascoreforanalysis.EyemovementswererecordedwithTOBIIStudio.Non‐

parametricanalyseswereconductedandtheresultsshowthatdespiteusingcontextualcueingfor

directingattention,implicitmemorywasnotaffectedbythatmanipulation.

51

A20.

TheKnowledgeandMisconceptionsofPrimaryandSecondarySchoolTeachersabouttheBrainandTheirPerceptionsaboutNeuroscienceinEducation:AMixedMethodsResearchtoAnalysetheSituationinTurkeyin2013.

OzgeKarakus1

1Mersin,Turkey

This study firstly explores primary/secondary school teachers’ knowledge and their

misconceptions about brain; secondly, the source of theirmisconceptions; and finally, teachers’

perceptionsaboutneuroscienceinTurkey.Inthisstudy,amixedmethodsapproachwastakenby

using a questionnaire and interviews. Thequestionnairewas taken fromDekker et al.’s (2012)

paperandconsistedof32 statements.15of thesewereactuallymisconceptionsaboutbrain. In

total, 278 primary and secondary school teachers completed thequestionnaire;with6 of them

being interviewed. Findings from thequestionnaires showed that teachers agreedwith53.02%

(SD=27.80) of the neuromyths in Turkey. This statistic is lower in UK (49%) and Netherlands

(49%) (Dekker et al., 2012).Therefore these results could strongly validate the concerns about

theprevalenceofneuromyths(OECD,2002).Findingsfromtheinterviewsrevealedthatteachers’

personal experiences/observations were more influential as being the source of their

misconceptions about brain. This outcome could show how "scientific" is the education. To

conclude,bytakingintoconsiderationtheprevalenceofneuromyths,itissuggestedthattraining

isneededinordertopreventunscientificapplicationsthroughoutclassroomsinTurkey.

52

A21.Effectsofworking‐memorytrainingonacademicabilitiesinmiddlechildhood.

JuliaKarbach1,TiloStrobach2andTorstenSchubert2

1SaarlandUniversity,Saarbrücken,Germany2HumboldtUniversity,Berlin,Germany

Workingmemory(WM)capacityishighlycorrelatedwithgeneralcognitiveabilityandhasproven

tobeanexcellentpredictorforacademicsuccess.GiventhatWMcanbeimprovedbytraining,our

aimwastotestwhetherWMtrainingbenefitedacademicabilitiesinelementaryschoolchildren.

Weexamined28participants(meanage=8.3years,SD=0.4)inapretest‐training‐posttest‐follow‐

updesign.Over 14 training sessions, children either performed adaptiveWM training (training

group,n=14),ornon‐adaptivelow‐leveltraining(activecontrolgroup,n=14)onthesametasks.

Pretest, posttest, and follow‐up at three months after posttest included a neurocognitive test

battery (WM, task switching, inhibition) and standardized tests for math and reading abilities.

AdaptiveWM training resulted in larger traininggains thannon‐adaptive training.Thebenefits

inducedbytheadaptivetrainingtransferredtoanuntrainedWMtaskandastandardizedtestfor

readingability,butnottotaskswitching,inhibition,ormath.TransfertotheuntrainedWMtask

wasmaintainedoverthreemonths.Theanalysisofindividualdifferencesrevealedcompensatory

effectswithlargergainsinchildrenwithlowerWMandreadingscoresatpretest.

53

PosterSessionB

B1.

Raiseyourhandstospecify‐gesturesmeetingdorsalandventralstreamsforlearningmathematics.

ChristinaKrause1

1UniversityofBremen,Bremen,Germany

A main issue for learning mathematics is to detach from concrete representations although

mathematicalobjectscanonlybeaccessedthroughthem.InmyPhD‐studyIinvestigatetheroleof

gestures in social processes ofmathematical knowledge construction. I framedmy research in

thetheoretical background of symbolic interactionism and embodied cognition. Mathematical

learningasaprocesswasreconstructedwithintwomethodologies,combininganepistemicaction

model(Bikner‐Ahsbahs2006)andamodelrespecting the intertwineddevelopmentofrelations

betweenspeech,gestureandinscription(Arzarello2006).Thisisbasedontwoassumptionsmade

about the learning ofmathematics:First,mathematical objects are individually constructed but

established within social interaction. Second, learning is a multimodal process.This approach

alreadyrespectsresearchonmirrorneuronsandtheroleofBroca’sarea(Gallese&Lakoff2005,

Rizzolatti&Craighero2004,Rizzolatti&Arbib1998).Oneofmyresultsdescribeshowgestures

specify thewhere, whatand howof mathematical objects,supporting the genesis of socially

negotiatedmathematicalmeaning. I suggest a connection to the dorsal and the ventral system

(Ungerleider&Miskin1992,O’Reagan&Noë2001)andaimtodiscussfutureprospectsthatmay

followadoptingthisapproach.

54

B2.

Arelationshipbetweenbrainactivitydataandeyetrackingdataduringmathematicaltasksfromtheviewofeducationalresearch.

YasufumiKuroda1andNaokoOkamoto2

1BukkyoUniversity,Kyoto,Japan2RitsumeikanUniversity,Kyoto,Japan

Since the1990's, severalbrainactivitymeasurementdeviceshavebeendeveloped.Someof the

advantagesofthesedevicesincludetheabilitytotakenon‐invasivemeasurementsandtheease‐

of‐use inmeasuring thebrain activity of studentswhile learning. In addition, very efficient eye

trackingmeasurementdeviceshavebeendevelopedrecentyears.Thepurposeofthisstudyisto

explore the relationshipbetweenbrainactivitydataandeye trackingdataduringmathematical

tasks from the view of educational research. In the experiments, we measured hemoglobin

changes in prefrontal cortices using NIRS (Near Infra‐Red Spectroscopy) system, which could

measurehemoglobinchangesinseated‐positions,whilesolvingmathematicaltasks.Atthesame

time,wemeasuredhowmanytimestohavemovedfixationpointusingeyetrackingmeasurement

devicesystem.We found thatphysiologicaldataof studentchangedgreatlyby thedifferenceof

thedifficulty level of themathematics tasks. In addition to the conventionalwaysof behavioral

data and test scores, the brain activity data and the eye tracking data would be new index to

learningdiagnosis.However, in order tomake thedata useful, there is a need to clarify typical

characteristicsofthedataundervariouslearningsituations.

55

B3.

Mind,Brain,andEducation:Acasestudyofstudentperceptionsofaninterdisciplinarygraduateprogram.

MarthaLees1

1UniversityofMassachusetts,Amherst,USA

Advancesindevelopmentalneuroscienceresearch,callsforeducationalreform,andanemphasis

on interdisciplinarityhavegenerated interest in howsciencemight informeducationalpractice

andpolicy,resultingintheemergingfieldofmind,brain,andeducation(MBE).Aprimarygoalof

thefieldistoconnectthecognitiveanddevelopmentalsciences,biology,andeducationtodevelop

a scientific grounding for educational practice and policy by creating new institutions where

researchandpracticearecloselyconnected.Oneaspectofthisinfrastructureincludestraininga

newgenerationofinterdisciplinaryresearchersandpractitionerswhohaveskillsandknowledge

in the multiple disciplines. This study uses a mixed‐methods case‐study design to investigate

students' perceptions of their experiences developing interdisciplinary knowledge in an MBE

graduate program, their perceptions of the potential and limitations of MBE to address

educationalproblems,andhowtheseperceptionsvarybasedondisciplinarybackground.

56

B4.

BrainActivityassociatedwithsolvinggeometryarea‐relatedproblems:Effectofgeneralgiftednessanexcellenceinmathematics.

MarkLeikin1,IlanaWaisman1,ShelleyShaul1andRozaLeikin1

1UniversityofHaifa,Haifa,Israel

InthispaperwereportonthestudythatusesERPmethodologyinordertoexaminetheimpactof

generalgiftedness(G)andexcellenceinschoolmathematics(EM)onhighstudents'mathematical

performance associated with area‐related problems. The research sample included 83 right‐

handedmalehighschoolstudents(16‐17yearsold)dividedintofiveresearchgroups:fourgroups

designedbyacombinationof levelsofGandEMfactorswhile the fifthgroup includedstudents

with superior mathematical abilities (S‐MG). We found effects neuro efficiency effect in gifted

students who excel in mathematics (G‐EM and S‐MG students), whereas the highest overall

electricalactivitywas found inEMstudentswhowerenot identifiedasgenerallygifted(NG‐EM

students).NG‐EMstudentswere(naturally)moreaccurate thanNG‐NEMstudentswhileNG‐EM

students displayed the highest electrical potentials when solving the problems. It appears that

electricalpotentialsinG‐EMandNG‐EMstudentsweresimilarwhileinS‐MGstudentstheywere

significantly loweras comparedbothgroupsof studentswhoexcel inmathematics.Wesuggest

that a combination of the ERP technique, along with more traditional educational research

methods,enablesobtainingreliablemeasuresonthementalprocessinginvolvedinmathematical

problemsolving.

57

B5.

BrainActivityassociatedwithsolvingshortinsight‐basedproblems:Focusingongenerallygiftedandexcellinginmathematicsadolescents.

RozaLeikin1,MarkLeikin1,IlanaWaisman1andShelleyShaul1

1UniversityofHaifa,Haifa,Israel

We use ERP methodology to explain the differences in adolescents' mathematical abilities.

Seventy‐one male participants formed four research groups designed according to the

combination of general giftedness (G) and excellence inmathematics (EM).We focus on brain

electrical activityassociatedwith solving short insight‐basedmathematicalproblems.GandEM

factors had significant effects on problem‐solving strategies expressed in laterality and the

strength of brain activation on problem‐solving. The study demonstrates that G and NG

individualsrecruitbothhemispheresdifferently:themeanamplitudeattherighthemispherewas

greater in G students as compared to NG participants, while the mean amplitude at the left

hemispherewasgreaterinNGstudentsascomparedtoGparticipants.Ourresearchdemonstrates

that each G factor andEM factor separately does not lead to a neuro‐efficiency effect,whereas

theircombinationisclearlyexpressedinlowerelectricalbrainactivity.Basedonourfindings,we

hypothesize that G and EM are different individual traits.We suggest that students fromG‐EM

groupsneeddifferentlearningenvironmentwithenhanceinsight‐basedproblemsolvinginorder

torealizetheirmathematicalpotential.

58

B6.

Dudeman&Sidegirl:OperationcleanWorld.AnewNumberGameusedtotrainNumberProcessingSkillsin5‐year‐olds.

BiekeMaertens1

1KULeuvenKulak,Kortrijk,Belgium

Humans possess basic number processing skills (e.g. number comparison and number line

estimation)ofwhichpreviousstudieshavedemonstratedthat thosearerelatedtomathematics

achievement.Inthesestudies,itwasassumedthatbothnumberprocessingtaskssharethesame

underlying representation located in the intra‐parietal sulcus (IPS). Recent research, however,

observednorelationshipbetweentheperformanceonthecomparisontaskontheonehandand

the number line estimation task on the other, suggesting that different mechanisms and

consequentlyotherbrainregionsmayplayarole inbothtasks.Forthisreason,wedesignedan

intervention study focusing on both basic number processing skills using a new tablet game.

Playing this game, in several levels, 70 kindergartners practiced either their comparison skills

(group 1) or their estimation skills (group 2). By means of a pre‐ and post‐test consisting of

experimental (non‐)symbolic comparison and number line estimations tasks, it was measured

whethertabletgametrainingononeofthesebasicnumberprocessingskillscouldbegeneralized

totheother.Resultsandimplicationsforeducationwillbediscussedattheconference.

59

B7.

EducationalNeuroscienceApplications:MemoryofMultiplicationFactsasaModel.

NitzaMark‐Zigdon1andAyeletKatzoff1

1LevinskyCollegeofEducation,Tel‐Aviv,Israel

Theaimofthisstudyistoextendknowledgeregardingthebestconditionsfordeclarativememory

formation at school. As a model, we used learning of basic multiplication facts, due to its

importance as a basis for learning complex mathematical procedures. Recent neurocognitive

studies provided evidence that memorized multiplication facts involve verbal brain areas.

Therefore, we combined neurobiological research on memory with pedagogical findings on

learning multiplication facts, following the approach of educational neuroscience. Declarative

memory formation consists of 2 labile phases requiring stabilization: consolidation and

reconsolidation. In thesephases,memorycanbe impaired ifnewcompeting learningtasks turn

up. In this study, third grade children were trained to memorize multiplication facts. For the

consolidation phase,we used different kinds of interferences (similar/non similar information)

andatthereconciliationphasedifferenttimemeasuresforreactivation(24h/1week).Wefound

that memory was disrupted if there was interference during the two labile phases with new

competinglearningespeciallywithsimilarinformationandtiminginfluencesthestrengthofthe

interferenceonreconsolidation.Theseresultshavepracticalapplicationforlearningandteaching

declarativemathematicalinformation.

60

B8.

Howthe1styearofformalschoolingshapessymbolicnumberdevelopment‐evidencefrombrainandbehavior.

AnnaMatejko1andDanielAnsari1

1UniversityofWesternOntario,London,Canada1st grade is a sensitiveperiod fornumber skill development.Researchhas shown thatGrade1

children are more accurate on nonsymbolic (dot) than symbolic number comparison (Arabic

numerals). By Grade 2 and 3, children perform equally well on these tasks, suggesting that

symbolicprocessingimprovesbetween1stand2ndgrade.Tofurtherexplorethis,weconducted

a longitudinal investigation of Grade 1 children. Specifically, we explored whether individual

differences inneural representationsofmagnitudecomparisonpredict symbolic&nonsymbolic

number development over time. 31 Grade 1 childrenwere assessed onmeasures ofmath and

symbolic & nonsymbolic number comparison at the beginning & middle of Grade 1. At the

beginning of Grade 1 children completed a symbolic & nonsymbolic number comparison task

whilefunctionalneuroimagingdatawereacquired.Analysessuggestchildrenaremoreproficient

onnonsymbolic vs. symbolicnumbercomparisonat theoutsetofGrade1. Inaddition, thedata

show that greater activity in the left superior parietal lobule during symbolic processing

correlateswithmathachievement.Thisisthefirststudytoexaminehowindividualdifferencesin

activationduringsymbolic&non‐symbolicnumberprocessinginGrade1predictvariabilityinthe

trajectoriesofearlynumberdevelopment.

61

B9.

Perceptualinformationinfluencestheformationofnumericalrepresentations:evidencefromanartificiallearningparadigm.

RebeccaMerkley1andGaiaScerif1

1UniversityofOxford,Oxford,UK

It is commonly assumed that numerical symbols are mapped onto core nonsymbolic

representations of number. Recent evidence has revealed that processing nonsymbolic

representationsofnumberissignificantlyinfluencedbytheassociatedvisualpropertiesofthese

representations, including area and density. Here, we tested whether congruency between

numerosity and visual parameters in nonsymbolic arrays facilitated adults’ learning of novel

symbols.Sincetherearethreerepresentationsofnumber(words,digits,nonsymbolicarrays),we

also tested whether providing verbal auditory nonword labels facilitated learning. Forty

undergraduate students were trained to associate novel abstract symbols with numerical

magnitudes. Half of the symbols were associated with arrays in which total surface area and

numerosity were correlated. Participants were randomly assigned to the visual only or

audiovisual condition. Following training, participants completed a symbolic numerical

comparisontaskwiththelearnedsymbols,atwo‐alternativeforced‐choicemappingtaskbetween

symbolsandnonsymbolicarrays,andanordinalitytest.Resultsrevealedaninteractionbetween

ratio and area on the symbolic comparison task, suggesting that visual parameters of the

nonsymbolic arrays did influence learning. Therewere no significant group differences on any

measures.

62

B10.

Therelationbetweenhomenumeracy,exactnumberskillsandnon‐symbolicaudiovisualmatchingabilities.

BeldeMutaf1,DelphineSasanguie2,BertDeSmedt1andBertReynvoet1

1KULeuven,Leuven,Belgium2KULeuvenKulak,Kortrijk,Belgium

Inthefieldofnumericalcognition,magnitudeprocessinghascommonlybeeninvestigatedusing

non‐symbolicnumber comparison tasks (i.e.whichdot array contains themostdots).Recently,

however, it is suggested that the performance on this task might be confounded by visual

processing. In thecurrentstudy,wealternativelyexaminednon‐symbolicmagnitudeprocessing

in 4 year olds using an audiovisual matching task (i.e. matching auditory presented sounds of

fallingappleswithavisualdisplayofapples inabasket).Additionally,aFree‐Countingtask(i.e.

countashighasyoucan),aCount‐Elicitationtask(i.e.countashighasyoucanusingone‐to‐one

correspondencewith linedpoker‐chips up to 15), and aGive aNumber task (i.e. give a certain

amount of poker‐chips from the bunch of 15) were conducted to assess exact number skills.

Parents also filled in a questionnaire on home numeracy activities and their SES, and the

association between these questionnaires and the performance on the experimental tasks was

investigated.Theresultswillbediscussedinthelightofdevelopmentaltheoriesontherelationof

approximateandexactnumberskills.

63

B11.Field Dependence‐Independence cognitive construct and the human brain:neuro‐educationalapproach.EfiNisiforou1

1CyprusUniversityofTechnology,Limassol,Cyprus

Cuttingedgetechnologiesarefundamentalinneurosciencestudiesoflearningandcognition.Theblendofneuroscience,educationandnewtechnologiesisofgreatimportanceandmayprovideapositive impact on young people cognition with respect to the way they learn.Electroencephalography(EEG)wasusedtodemonstratewhathappenstothehumanbrainas itreceives visual information. Specifically, the study aims to identify users’ visual attention withrefer to theField‐Dependent/ Independentcognitivestyleconstructwhile theywereprocessingvisualstimuli.Additionally,itattemptstoprovideindepthunderstandingoftherelationbetweencognitive abilities and brain cognitive process. The target audience of the study consists of anumberofstudents,recruitedfromapublicUniversityinCyprus.Thequantitativevariablesusedinthestudywereanalyzedwiththesoftware’sdeviceandtheuseofthestatisticalpackageSPSS.Results revealed the necessity to develop learning stimuli that reflect user's cognitive ability.Eventually, byunderstandinghowcognitive styles affectuser’s visualbehaviourwe can furtherenrich our knowledge on how to design online environments which will improve users' webexperiencesandleadtoacceleratedandmoreefficientlearning.

64

B12.Cognitive Change: The Effects of Aquatic Motor Activities on Early‐ChildhoodMotorandCognitiveDevelopment.Michal Nissim1, Ronit Ram‐Tsur1, Michal Zion1, Tal Dotan Ben‐Soussan1 and ZemiraMevarech1

1Bar‐IlanUniversity,Ramat‐Gan,Israel

TheeffectsofAquaticMotorActivities(AMA),On‐LandMotorActivities(OLMA)andNon‐MotorActivities(NMA)followingsixmonthsofintervention,onmotorandcognitivedevelopmentwerecompared in a sample of 94 children aged 4‐6. Our hypothesis suggests that changing theenvironment of the activity towatermay strengthen specific neurological connections, therebyimproving motor and cognitive abilities, which might be connected to cerebellum functioning.Evidence for the connection betweenmotor experience, cognitive development and cerebellumfunctionality are still under investigation. Evidence for the effect of different environments oncognitivedevelopment isremarkablyscarce.Developmental‐functionality tests, includingmotor,Raven’s Colored Progressive Matrices (RCPM), cross‐out and visual matching tests were used.AMA was found to predict the changes in gross motor, time‐estimation and RCPM scores.Moreover, improvement in gross motor abilities moderates the association between AMA andchildren’svisualmatchingscore.Thesefindingsincreasetheunderstandingofchild‐developmentprofessionals, regarding the connection between the aquatic environment and motor andcognitivedevelopment,possiblyleadingtoimprovedearly‐childhoodinterventions.

65

B13.Kindergarten Children's Number Comparison Skills Predict First Grade MathScores:EvidenceFromaTwo‐minuteTest.NadiaNosworthy1,SamuelZheng2andDanielAnsari

1AndrewsUniversity,BerrienSprings,USA2TorontoDistrictSchoolBoard,Toronto,Canada3UniversityofWesternOntario,London,Canada

Children’sabilitytocomparesymbolic(e.g.,Arabicnumerals)andnonsymbolic(e.g.,dotarrays)numericalmagnitudeshasbeen found tocorrelatewith theirmathachievement.Most research,however, has focused on computerized paradigms,whichmay not always be suitable for quickapplicationinclassrooms.Consequently,wedesignedatwo‐minutepaper‐and‐pencilassessmentto measure kindergarten children’s ability to compare symbolic and nonsymbolic numericalmagnitudes and assessed thedegree towhichperformanceon thismeasure explains individualdifferences in achievement. Children were required to cross out the larger of two, single‐digitnumericalmagnitudes.Resultsfrom250kindergartnersrevealedthatsymbolicandnonsymbolicnumber comparison accuracy scores correlated with individual differences in arithmeticachievement.Resultsalsodemonstratedthatparticipants’scoresonthepaper‐and‐penciltest inkindergarten was a significant predictor of math performance in first grade. These findingssuggest the important role of symbolic and nonsymbolic processing in children’s higher‐levelmath abilities and the importance of assessing this very basic skill in children, highlighting thepotentialofthistoolfortheassessmentofearly,foundationalnumericalabilities.

66

B14.Neural efficiency in workingmemory tasks: The impact of task demand andtraining.DanielaNussbaumer1,RolandH.Grabner2andElsbethStern1

1ETHZurich,Zurich,Switzerland2Georg‐August‐UniversityofGöttingen,Göttingen,Germany

Studiesofhumanintelligenceprovidestrongevidencefortheneuralefficiencyhypothesis:Moreefficientbrainfunctioninginmoreintelligentindividuals,thatis,lesscorticalactivationinbrighterindividuals.Themaingoalofthisstudywastoexploretherelationshipbetweenintelligenceandcorticalactivationincombinationwithacognitivetraining.In83participants,corticalactivationwas assessed by means of event‐related desynchronization (ERD) before and after workingmemory(WM)training.Inapre‐testtrainingpost‐testdesign,ERDduringperformanceoftrainedaswellasuntrainedtransfertaskswascorrelatedwithscoresinapsychometricintelligencetest(Raven’sAdvancedProgressiveMatricestest).WefoundanegativecorrelationbetweenERDandintelligenceformoderatelydifficulttasks.Adecreaseincorticalinvestmentfrompre‐topost‐testwas found for simple tasks but likewise for individualswith lower and higher intelligence.Wecould not find a stronger activation decrease frompre‐ to post‐test for individualswith higherintelligence. These findings suggest partial confirmation of the neural efficiency hypothesis formoderatelydifficulttasksandtheyprovideanindicationthattrainingcanhelpinreducingcorticalactivationwhilesolvingsimpletasks.

67

B15.How Expert Mathematicians Compare the Numerical Values of FractionsEvidencefromEyeMovements.AndreasObersteiner1andKristinaReiss1

1TUMSchoolofEducation,München,Germany

Fractioncomparisontasksarefrequentlyusedtostudythementalrepresentationoffractions.Ithas been a matter of debate if individuals solve such tasks componentially by comparing thefraction numerators and denominators, or holistically by considering the fraction magnitudes.Recent research suggested that expertmathematicians use componential strategies for fractionpairswith commoncomponents, andholistic strategies forpairswithout commoncomponents.Theseconclusionswerebasedonresponsetimemeasures,whichareanonlyindirectindicatorofindividualstrategies.Thisstudyrecordedforthefirsttimeeyemovementstotestifthismethodallows distinguishing strategy use depending on problem type. Results from a first experimentwitheightacademicmathematiciansshowedthatparticipantsfixatedthenumeratorssignificantlylonger on fraction pairs with common denominators, and vice versa for fraction pairs withcommon numerators, hinting to componential strategies. There were no such differences forfraction pairs without common components, hinting to holistic strategies. We are currentlycollectingdata froma largersampleofuniversity studentsmajoring inmathematics.So far,eyemovements seem to be a promising method for assessing individual strategies on fractioncomparisontasks.

68

B16.Morethansubitizing:Symbolicmanipulationsofnumbers.SinanOlkun1,ArifAltun2andSakineGöçerŞahin2

1TEDUniversity,Ankara,Turkey2HacettepeUniversity,Ankara,Turkey

This study tested the hypothesis that subitizing ability may cause achievement differences inmathematics especially for students with mathematics learning disabilities. Students from 1stthrough 4th gradewere applied to curriculum basedmath achievement tests (MAT). Based onMATscores,theyweredividiedintofourgroupsasMathematicsLearningDisorder(MLD)risks,low achievers (LA), typical achievers (TA), and high achievers (HA). All students were askedrandomly and canonically arranged dot enumeration tasks with 3 through 9 dots. Medianresponse times (MRT)were calculated for each task and plotted for each grade level and tasktypes.Therewerevirtuallynodifferences inMRTs fornumber3 and4.On theotherhand, theMLD risk group spent relatively more time on enumerating canonically arranged dots from 5through9.Resultsprovidedmore support for the claim that rather than subitizing, numerositycodingmechanismsor the typeof symbolicquantitymanipulations isdifferent in childrenwithdifferentmathematicalachievementsespeciallythelowergroup,theMLDriskgroup.

69

B17.Feedback's informative value as the driving force of the feedback‐relatednegativity(FRN).BertramOpitz11UniversityofSurrey,Guildford,UK

The fast and efficient evaluation of feedback is essential for learning in humans. The feedback‐relatednegativity(FRN)oftheevent‐relatedpotentialhasbeenidentifiedasaneurophysiologicalmarker of feedback processing. Here we consider a novel account where learning serves tominimizeuncertaintyabout(future)statesandfeedbackthatprovidesthemostinformationaboutthe current state is most useful for learning. Thus, the amplitude of the FRN scales with theinformation provided by the feedback. In the present study volunteers performed a stimulus‐response association learning task with varying proportions of positive, negative, and non‐informative feedback. The informative value ofwas calculated by assessing the average of self‐informationofthefeedback.Participantslearnedstimulusresponseassociationsverywellwithanaverageproportionof90%correctresponses.Astepwiseregressionanalysisrevealedthatonlythe informativevaluewasassociatedwithasignificantregressionweightexplaining31%of thetotal variance of the FRN amplitude. The present results indicate that the FRN reflects theaccumulated neural activity elicited by the computation of the informative value of the mostrecent feedback. The net outcome of this computational process is subsequently utilised forlearning.

70

B18.StructuralandFunctionalNeuroimagingofReadinginChildren.MaritaPartanen1,LindaSiegel1andDeborahGiaschi1

1UniversityofBritishColumbia,Vancouver,Canada

Neuroimagingresearchhasshownthatreading involvesthe lefthemisphereandthatwhiteandgreymatterstructuresarerelatedtoreadingability.However,theanalysisofbrainnetworksusedfor reading is rarely conducted with more than one neuroimaging method and thus furtherevidence isneeded toassociatebrain structurewith function.Thepurposeof this studywas toexaminereadingnetworksusingseveralneuroimagingtechniques.Childrenwithvaryingreadingabilities(7‐9yearsold)completedanMRIscantomeasureorthographicandphonologicalreading(fMRI), functional connectivity (resting state fMRI), greymatter volume (T1), andwhitematterdensity (diffusion tensor imaging). Whole brain activation and regions of interest (ROI) weredetermined from the fMRI reading tasks. We subsequently analyzed the ROIs for functionalconnectivity,greymattervolume,andwhitematterdensity.Resultsshowedactivationforreadingin left frontal, insular, parietal, and fusiformgyri. The time courses of theROIswerepositivelycorrelated to each other from the resting state scan, indicating that reading networkswork intandem even at rest. Greymatter volume andwhitematter densitywithin the ROIswere alsorelated toreadingability, suggesting thatbothstructureand functionare important for readingability.

71

B19.Eyemovementsduringdotenumeration:The influenceofvisualandnumericalinformation.JacobPaul1,JasonForte1andRobertReeve1

1UniversityofMelbourne,Melbourne,Australia

Individual differences in dot enumeration (DE) abilities predictmath problem solving success;however, the reason for differences in DE abilities is unclear. We test the hypothesis thatdifferences inDEabilitiesreflectdifferences invisualprocessingcapabilities, reflectedbyvisualscanning efficiency. To test this claim we analyzed eye movement patterns as individualscompleted a DE task. Ten observers viewed dot displays in which visual and numericalinformation were manipulated. To assess the affect of dot structure canonicity, twoconfigurationsforDEsetsizes1through12wererandomlygeneratedandpresentedat0°,90°,180°,and270°orientationssothat inter‐dotdistancesremainedconstant. Observersmadetwojudgements: thenumberofdotsand theapparent canonicityofdotdisplays. Analysesrevealedindividual differences in the efficiency, regularity and similarity of scan paths and fixationpatterns. Eye movements for identical dot patterns varied as a function of dot numerosity,apparentcanonicity,andexposurefrequency.Individualdifferencesinvisualscanningefficiencywere associated with computation success. Implications for math learning theories andinterventionpracticesareconsidered.

72

B20.Neuralrepresentations invisualcortex fornumericalmagnitudespresented indifferentformats.LienPeters1,HansOpdeBeeck1andBertDeSmedt1

1KULeuven,Leuven,Belgium

One intriguing question with clear education relevance deals with how the brain processesnumbers. In this study, we investigated the effects of different ways of representing numbers(digits,dots,numberwords)duringcalculation.Weexaminedhowdifferentrepresentationsareprocessed in the brain and how they evolve across the visual system. The study included twofMRI‐experiments.InExperiment1,subjectshadtosubtractmagnitudesupto20presentedasdotpatterns, digits and number words, and compare the result to a reference magnitude. Weconsistently found a region in lateral‐occipital (LO) cortex that respondedmore to digits thanwords. InExperiment2,wemanipulated format (letterversusdigit) andstring length. Subjectsperformedanordinaltask.TheLOpreferencefordigitsversuswordsfromExperiment1wasnotreplicatedhereandmighthavereflectedatask‐dependentpreference.Furthermore,wefoundashiftinrepresentationoflettersanddigitsthroughoutthevisualprocessingstreamfromgroupingbased on number of characters to grouping based on stimulus category. We are currentlyreplicating Experiment 1 in children, attempting to investigate the effect of differentrepresentations(digits,words,dots)onbrainfunctioning.Preliminaryresultsofthisstudywillbepresentedattheconference.

73

B21.The association between digit comparison performance and individualdifferencesinarithmeticunraveled.DelphineSasanguie1,BertDeSmedt2andBertReynvoet1

1KULeuvenKulak,Kortrijk,Belgium2ParentingandSpecialEducation,Leuven,Belgium

Studiesinbothadultsandchildrenshowedthattheperformanceonasingle‐digitcomparisontask(i.e.decidingwhichoneislarger)isconcurrentlyaswellaspredictivelyassociatedwithindividualdifferences in arithmetic. To date, however, it is unclear which specific process within thecomparisonofdigitscausesthisrelation.Potentialcandidatesincludetheprocessingofcardinalityinformation, order information, digit‐wordmatching or fast digit recognition, all ofwhich havebeensuggestedtorelyondifferentbrainareas.Thepresentstudyaimedtoclarifythisissue.Adultparticipantsperformedadigitrecognitiontask(i.e.isthisadigitornot?),anaudiovisualmatchingtask (i.e. are 7 and /seven/ numerical identical?), a relative‐order judgment task (i.e. is thenumberpair6–7 in thecorrectascending left torightcountingorder?)andacomparisontask(e.g. is7 larger than6?).Theperformanceonthese taskswasrelatedto theperformanceonanarithmetictest.Inaddition,similartaskswithletterswereconductedtocontrolforgeneralnon‐numericalfactors.Resultsandimplicationsforeducationwillbehighlightedattheconference.

74

PosterSessionCC1.NeuralCorrelatesofFatigueDuringTaskSwitching.SarahPlukaard1,LydiaKrabbendam1,DickVeltman2andJelleJolles1

1VUUniversityAmsterdam,Amsterdam,theNetherlands2VUUniversityMedicalCenter,Amsterdam,theNetherlands

Fatigue in healthy students is a common problem and associated with reduced academicachievement.However, theeffectsof fatigueoncognitionarepoorlyunderstood. In the currentfMRI study, 25 female students with long‐term fatigue were compared to 26 female studentswithout fatigue on a task‐switching paradigm. Both groups were scanned following a fatiguemanipulation (i.e., 1.5 hours of demanding cognitive tasks) in one session and a controlmanipulation (i.e., 1.5hoursof non‐demandingactivities) in another session.The sessions tookplace in counterbalanced order on two separate days. There were no differences between thegroupsor sessionsonbehaviouralperformance.Across thegroupsandsessions, activationwasobserved in the left premotor, supplementary motor, inferior parietal, middle temporal anddorsolateralprefrontalcortex,andintherightposteriorcingulatecortexandposteriorinsula.Thegroup with long‐term fatigue activated the left anterior cingulate cortex more than the groupwithout fatigue. Interactions between group and session were found in the left dorsolateralprefrontal,somatosensoryassociationandpremotorcortex.Theseresults indicatethatamentalfatigue induction differently affects prefrontal areas in students with and without long‐termfatiguewhileswitchingbetweentasks.

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C2.ExploringMentalRepresentationsforLiteralSymbolsUsingthePrimingDistanceEffect.CourtneyPollack1andSibyllaLeonGuerrero1

1HarvardGraduateSchoolofEducation,Cambridge,USA

Priorresearchhasinvestigatedhowsymbolicrepresentationsofnumberlinktorepresentationsof quantity on a notation‐independent mental number line. Unknown is whether ‘short‐term’symbolic representations of quantity, such as literal symbols (e.g., ‘x’) that have been givenquantitative meaning, can also map onto this mental number line. Prior research hassubstantiatedaprimingdistanceeffect (PDE), inwhicheaseof comparinga targetnumber to afixed standard is a function of prime‐target distance (e.g., Defever et al., 2011; Reynvoet et al.,2002).CanliteralsymbolsmaptothementalnumberlineandproduceaPDEasothersymbolicrepresentationsdo?FortyparticipantscompletedaseriesofnumbercomparisontasksinvolvingArabicnumeralsandliteralsymbols,atrainingtask,andaworkingmemorytask.WhileaPDEwaspresent during comparison with Arabic numerals, we found no evidence of a PDE with literalsymbols.Ourfindingssuggestthat literalsymbolswithquantitativemeaningmaynotaccessthesame mental number line as other number formats or may not access it in the same way.Additional research is needed to understand the types of mental representations utilized inhigher‐levelmathematics(e.g.,algebra),whichincludesbothArabicnumeralsandliteralsymbols.

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C3.From executive functions to number knowledge: NeuropsychologicalperformanceinPortuguesepreschoolers.JoanaRato1andAlexandreCastro‐Caldas1

1InstituteofHealthSciences,CatholicUniversityofPortugal,Lisbon,Portugal

Previous literature suggests that early number knowledge is under‐assessed byneuropsychologicaltools,comparedwithothercognitiveskills.Inthepresentstudyweanalysedthe relationbetweencomponentabilities (as theexecutive functionsand fingergnosis)and theearlynumberknowledge, evaluating theirpredictivepower.The sample comprised35 typicallydevelopingchildren(19boysand16girls)with5years‐old(60‐71months;M=67.26,SD=5.43).Aneuropsychological assessment protocol was developed for this purpose. Executive functions,subitizing and finger gnosis skills were found to be predictors of number knowledge. Thesecomponentsseemtocontributetoperformanceonnumericaltasks,andshouldbeconsideredinmathematics education. Our findings support several views concerning the foundations ofnumeracy and have implications for the early identification of preschoolers’ math skills. Theconclusionsof this studystrengthen theefforts for reformingmathematicseducationunder thedevelopingfieldofEducationalNeuroscience.

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C4.SymbolicnumericalprocessingdeficitinpeoplewithWilliamssyndrome.LaurenceRousselle1andMarie‐PascaleNoël1

1UnitédePsychologieduDéveloppementCognitif,Liège,Belgium

Recent studies suggest that people with Williams syndrome (WS) present specific deficit inprocessingnumericalmagnitudes(Krajcsietal.,2009;O’Hearnetal.,2007;Patersonetal.,2006).AspatientswithWSwerealwaystestedinthevisualmodality,theirdeficitcouldeitherbespecifictotheprocessingofnumericalmagnitudeorresultfromtheirbasicvisuo‐spatialimpairment(maincharacteristic of their cognitive phenotype). Supporting the second hypothesis, a first studyshowedthatpeoplewithWShavelowernumericalacuityonlyinnumericaltaskswithhighvisuo‐spatial processing requirements (i.e. comparing two lengths or two arrays of elements but notwhen comparing two durations or two sequences of flash in a single location; Rousselle et al.,2013). Recently,we testedwhether a similar dissociationwould be observed in processing themeaningofnumericalsymbols.PatientswithWSwereaskedtocomparethenumericalmagnitudeof two Arabic d vs two spoken verbal numerals. Their subitizing abilities were also assessedthroughtheenumerationof1to7dotsshownfor250ms.ParticipantswithWSwerecomparedtochildrenmatchedonverbalornonverbalmentalabilities.Resultsshowthattheyhavedifficultiesin accessing the meaning of numerical symbols whatever the format and present smallersubitizingrange.

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C5.Examiningtheproblemsizeeffect:atDCSandEEGstudy.BrunoRütsche1,TobiasU.Hauser2,LutzJäncke3andRolandH.Grabner4

1InstituteforBehavioralSciences,ETHZurich,Zurich,Switzerland2UniversityClinicsforChildandAdolescentPsychiatry(UCCAP),UniversityofZurich,Zurich,Switzerland3InstituteofPsychology,UniversityofZurich,Zurich,Switzerland4Georg‐August‐UniversityofGöttingen,Göttingen,Germany

Theproblemsizeeffect isawell‐establishedfindinginarithmeticproblemsolvingcharacterizedby worse performance in problems with larger compared to smaller operand size. We usedtranscranialdirectcurrentstimulation(tDCS)toevaluatewhetherelectroencephalography(EEG)oscillations shown to be indicative of problem size are causally related to performance andwhethertheeffectsofbrainstimulationdependonproblemsize.Participantsunderwentanodal(30min,1.5mA,overleftposteriorparietalcortex)andshamtDCS.EEGwasrecordedwhiletheysolvedsmallandlargeproblems.Anodalstimulationdecreasedresponselatenciesandincreasedlower alpha desynchronization (8‐10 Hz) in large problems, whereas it decreased thetasynchronization(4‐7Hz)insmallproblems.Thesefindingsprovidefirstevidenceofacausallinkbetween oscillatory theta and alpha activity and arithmetic processes, and reveal that problemsizemoderatestheeffectsofbrainstimulation.

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C6.

MusicintheBaddeleymodelofworkingmemoryinTDandSLIchildren.StephanSallat1

1 Speech‐Language‐Communication in Special Needs Education Institute of Special Needs Education, University of Leipzig,Germany

Verbal working memory performance in TD children and adults was shown to correlate withcomprehensionofspokenlanguage(Daneman&Merikle,1996;Just&Carpenter,1992),writtenlanguage(Daneman&Merikle,1996;Gathercole&Baddeley,1993),wordacquisition(Baddeley,Gathercole,&Papagno,1998),andsyntaxprocessing(Ellis&Sinclair,1996).DuetoitsimportanceforlanguageacquisitionBaddeleyetal.(1998)proposedoneofthesubsystems,thephonologicalloop, as Language Learning Device. Children with specific language impairment (SLI) showdeficienciesinverbalworkingmemory(WM),asreflectedinpoorperformanceinword,non‐wordor sentence repetition paradigms (Marton & Schwartz, 2003; Montgomery, 2003). Beside theproblemsinspeechprocessingSLIchildrenalsoshowproblemsinmusicalandthusnonlinguistictasks(Jentschkeetal.,2008;Sallat,2008;Sallat,Stachowiak&Jentschke,inprep.,seealsoMampeetal.2009).Uptonowitisamatterofdiscussionwhetherthephonologicalloopisalsoinvolvedinstoringmusicalortonalinformation(Pechmann&Mohr,1992;Semal,Demany,Ueda,&Halle,1996).Inthestudywecomparedverbalworkingmemoryperformance(AGTB5‐10,Hasselhornetal.2012)withmusicalworkingmemoryresultsin407‐8yearoldTDandSLIchildren.

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C7.Effectsofpsychologicalandphysiologicalvariablesonstudents’subjectivestressexperience. A multilevel longitudinal analysis in naturalistic educationalsettings.DetlefSembill1andTobiasKärner1

1LehrstuhlfürWirtschaftspädagogik,UniversitätBamberg,Bamberg,Germany

Learninginschoolentailsanamountofpotentialstressorsbutmostofthecross‐sectionalstudiesarebasedonlyuponself‐reports. Considering that thereare several levels involved,wehave tomeasurepsychologicalaswellasphysiologicalvariables.Academicself‐conceptisconsidered.Bycontinuous state sampling psychological statesweremeasured (perceived resources, subjectivestress experience). The physiological level is represented by the baseline saliva cortisolconcentrationand theheart rate variability (LF/HF‐ratio).Theaimof the studywas to identifycross‐level interactions explaining learners stress experience. 28 prospective industrial clerkswereinvestigatedduring9school lessonsinschool.Thereare10to38state‐measurementsperpersonwhichaddupto775measurementsintotal.Analyzing influencesofseveralvariablesonthe subjective stress experience a multilevel model with two levels was applied: Time basedmeasurementsarenestedinindividuals.AsignificantpositiveeffectoftheLF/HF‐ratio(p<.05)onstressexperiencecanbereported.Furthermorethereisasignificantcross‐levelinteractionofbaselinesalivacortisolconcentrationwiththesubjectivestressexperience(p<.05).Videobasedobservationswillcomplementthesedataforbetterexplanationsoflearningprocesses.

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C8.On the development of themultiplication fact network in elementary schoolchildren.MojtabaSoltanlou1,SilviaPixner2,LianeKaufmann3andHans‐ChristophNürk1

1UniversityofTübingen,Tübingen,Germany2UMIT‐TheHealthandLifeSciencesUniversity,HallinTyrol,Austria3InnsbruckMedicalUniversity,Innsbruck,Austria

Number factsarecommonlyassumed tobestored inanassociativemultiplication fact retrievalnetwork.Prominentevidenceforthisassumptioncomesfromso‐calledoperanderrors(e.g.4x6=28,belonging to themultiplication tableof4because4x7=28).Errors related tooneof theoperands constitute about 2/3ormore of all errors in healthy adults.However, little is knownaboutthefrequencyandthedevelopmentofoperand‐relatedperformanceinelementarychildren.Therefore,inthislongitudinalstudy,weexploredelementarychildrenfrom3rdand4thgradeinamultiplicationverificationtaskandrecordedresponsestoproblemswithoperand‐relatederrorsandoperand‐unrelatederrors.Performanceincreasedwithageandexperience.Mostimportantly,an operand‐relation effect was observed from 3rd grade on, but seemed to change over time.Theresultssuggestthateveninchildrenmultiplicationfactsarestoredinanassociativenetwork,which,however,seemstodevelopandstabilizewithageandexperience.

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C9.Teachers'perceptionofthebrainfunctioninLatinAmerica.AdrianaSoniGarcía1,PaulHoward‐Jones1andSaraMeadows1

1UniversityofBristol,GraduateSchoolofEducation,Bristol,UK

Europe has produced several studies exploring how neuroscience can inform education. Thispioneerprojectaims toexplore ideasabout thebrainheldbyeducators inLatinAmerica (L.A.)andtocontributetowardsbuildingabridgefordialoguebetweenneuroscienceandeducationinthisregion.Aninterpretive,qualitativemethoddesignusedasemi‐structuredinterviewapproach,andbecauseof the largegeographicalcoverageattempted, itwasconductedviaSkype.15basiceducationlevelteachersfromeightL.A.countries,withlittletonoknowledgeofneuroscienceandits use in education, were interviewed individually. A theoretical thematic analysis revealed anumberofprominentideas:abeliefthatemotionsplayanimportantroleinbrainfunctioningandlearning,andthatdopaminecanbeactivatedbybeingina“pleasantenvironment”orpracticing“brain gym”. Participants showed interest, and little caution, in becomingmore informed abouttheuseofneuroscience in education.Asobserved inEuropeand theU.S., L.A. teachers seemedkeenonlearningaboutneuroscience,whichcouldmakethemvulnerabletoobtaininginformationfrom the wrong sources (e. g. pseudo‐neuroscientists, the media, or out of date research).However,someofthebeliefsaboutthebrainhadnotbeenpresentinothercountriesbefore.

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C10.ProcessingnumericalOrdinality:isitacoreability?DanaSury1,OrlyRubinsten1,AlicedeVisscher2andMarie‐PascaleNoël2

1UniversityofHaifa,thedepartmentforlearningdisabilities,M.P.Meromha‐galil,Haifa,Israel2CenterofCognitiveNeuroscience,InstituteofPsychology,CatholicUniversityofLouvain,Belgium.

Ordinalityisahallmarkfeatureofnumbersthatmightbeaffectedbylanguage(i.e.,thedirectionof writing system). We report three studies that are aimed to evaluate the cognitive basis ofnumerical ordinal processing: (1) three groups of Hebrew speaking Israeli children (5‐9 y.o.)completedanordinaljudgingtaskswithquantities(i.e.,dotpatterns)orArabicnumberswhilethedirection of the sequence (ascending/descending) was manipulated. Findings indicate thatchildren from the age of five are able to process numerical ordinality while in school agedchildren, responses to ordinal sequences were modulated by direction; In the symbolic task,ordinalityeffectwassignificantonlyinthe8‐9‐yearsoldgroup.(2)InBelgianchildrenwhousealeft to right writing system, the effect of direction was reversed (i.e., the ordinal ascendingdirectionwasprocessedmoreaccurately). (3) In a third experiment,weevaluated the effect ofmaskedprimed,ordinalvs.nonordinalnumericalsequencesontheabilitytoestimatequantityinadult participants. Priming ordinal sequences affected the patterns of estimation, suggestingautomaticprocessingofordinality.We suggest that there are two separate cognitive representations of ordinal and quantityinformationandthatordinalprocessingactasacoreability.

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C11.Theneuroscienceliteracyofpre‐servicespecialneedseducatorsandpredictorsofneuromythsandknowledge.SimonaTancig1,SuzanaPulecLah1,IngridZolgarJerkovic1andMojcaVrhovski1

1UniversityofLjubljana,FacultyofEducation,Ljubljana,Slovenia

OneofthemainobjectivesoftheMBEscienceistoassurebestpracticeteachingthroughscientificevidenceofneuro‐andcognitivesciences,whileapplicationofneuromythsineducationshouldbeavoided. Raising neuroscience literacy should preventmisunderstandings about how the brainworks.Trainingandprofessionaldevelopmentshouldthusincludeacomponentofneurosciencerelevant toeducation.Themainpurposeof thisstudy is to investigate theneuroscience literacyand predictors of neuromyths and knowledge of the brain. The study also investigatesmotivesandinterestsofeducatorsinMBEscience.Measures–Instruments:Aquestionaryforbackgroundinformation and interests in MBE science; a survey of neuroscience literacy adapted fromHurculano‐Houzel (2002) andHoward Jones (2009);Walker andPlomin's survey (2005) aboutteachers' perception how genes and environment influence educationally relevant behavior.Participants:All instrumentswereadministered to studentsof specialpedagogy(N=200)at theFacultyofEducation.Dataanalysis:Descriptivestatisticandregressionanalysiswereappliedtoobtained data. Discussion: The results will be discussed in the context of planning actions forraising the neuroscience literacy and implementing the MBE science findings in the studyprograms.

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C12.Neuromythsamongsecondaryandcollegeteachers.EricTardif1,Pierre‐AndréDoudin1andNicolasMeylan1

1HauteécolepédagogiqueVAUD,Lausanne,Switzerland

Manyso‐called“brain‐based”approacheshavebeenstronglycriticizedfortheirlackofempiricalsupport and sometimes for the use of pseudoscientific concepts. Several authors are thereforeusing the term neuromyths referring to false beliefs or misinterpretations regardingneuroscientific facts.We surveyed teachers and trainee teachers about their agreement towardhemisphericpreferences,modalitypreferencesandtheBrainGym©method.Morethan80%oftherespondentsagreedthatsomeindividualsusemoreonehemisphereovertheotherandthatsome aremore visual while others are auditory. They also though that this was supported bybrain research. Althoughmost subjects (73%) responded that theywere not taking in accounthemisphericpreferences intheirteachingpractices,mostof themagreedthatapedagogybasedon suchdifferentiationwould favours learning.Togetherwithother studies, the results suggestthat teachers and trainee teacherswould benefit from appropriate training in this new field ofresearch.

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C13.Patternsofchange inthecognition‐emotionrelationshippredictmathproblemsolving.KellyTrezise1andRobertReeve1

1UniversityofMelbourne,Melbourne,Australia

Surprisinglylittleisknownaboutwhetherrelationshipsbetweencognitive(C)andemotional(E)statesremainstableorchangeovertime,orhowdifferentpatternsofstabilityand/orchangeinC‐E relationships affectmath problem solving abilities. However, cross‐sectional fMRI data showthat anxiety/worry‐problem solving relationships are mediated by frontal regions; variationsamong which are associated with an ability to coordinate task demands. To investigate theimplicationsof stabilityand/or changeC‐E relationsover time,12014‐year‐olds’ algebraicWMandworrylevelswereassessedtwiceinasingledayastheystudiedforanalgebratest.Weusedlatent class transition analysis to identify stability/change in E‐C relations, which yielded a sixsubgroup solution. Subgroups varied in WM capacity, worry, stability/change in theserelationships andalgebraic test abilities. Inparticular, thehighWMcapacity‐lowworry “stableacrosstime”subgroupperformedbestonthealgebratest;andincontrast,thelowWMcapacity‐highworry “unstable across time” subgroup performedworst. The findings are interpreted asshowing that it important to assess variations in C‐E relationships over time (rather thanassessingCorEstatesalone)toaccountfordifferencesinacademicproblemsolvingabilities.

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C14.

The influence of reading problems on basic numerical processing in childrenwithandwithoutmathdifficulties.AnniekVaessen1,2andPattyGerretsen1

1RegionalInstituteforDyslexia,Arnhem,theNetherlands2MaastrichtUniversity,Maastricht,theNetherlands

Ithasbeenclaimedthatchildrenwithreadingproblemsoftenalsoexperiencemathproblemsandthe otherway around. Studies report an overlap between reading andmath problems varyingbetween17and81%.Thequestion is inwhichway the cognitive problemsunderlying readingdifficulty relate to arithmetic performance. Do children with reading difficulties mainly haveproblemswithmathbecausetheyhavedifficultieswithautomatizingarithmeticproceduresandwithhigherordermathematicaltasksthat(partly)relyonverbalprocesses,ordotheyalsohaveproblems with basic numerical processing? And do children with combinedmath and readingdifficulties(RDMD)showasimilardeficitpatternonbasicnumericaltasksaschildrenwithmathdifficultiesonly(MD)?Inthepresentstudy,therelationshipandoverlapbetweenreadingfluencyproblemsandarithmeticproblemsisinvestigatedinalargeDutchsampleof1200primaryschoolstudents. The influence of reading performance on numerical processing is investigated, andchildren with reading problems only (RD), MD, and RDMD are compared on a number ofarithmeticandbasicnumberprocessingtasks.Resultssuggestthatreadingproblemsaffectsomebasic numerical processes, but leave other processes unaffected. Results and practicalimplicationswillbediscussed.

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C15.Cognitiveandneuralcharacteristicsofmathematicaldifficultiesinchildrenwithmildtraumaticbraininjury(mTBI).LeenVanBeek1

1KULeuven,Leuven,Belgium

Impairments in academic skills have been reported following pediatricmTBI andmathematicsrather than reading or spelling is themost compromised in these children. However, a precisecharacterizationofthesemathematicaldifficulties(MD)isunavailable.Thisstudyaimstoprovidea characterization of the MD in pediatric mTBI at both behavioral and neuroanatomical level.Twenty semi‐acute pediatric mTBI patients and 20 matched controls underwent cognitiveassessment and MRI‐examination. Mathematical competence was measured with standardizedandexperimentalmeasurements.Becausediffuseaxonal injury is common inTBIand iswidelybelievedtoaccountforpersistentcognitiveproblemsafterTBI,weusedDiffusionTensorImaging(DTI) toexaminewhitematterabnormalities.PreliminarybehavioralresultsshowthatchildrenwithmTBI scored loweronblock recall tasks, suggestingpoorervisuo‐spatialworkingmemoryand they were also less accurate in comparing numerical magnitudes, indicating a deficit innumericalprocessing.ByusingDTI‐tractography,wearecurrentlydelineatingwhitemattertractsthatareinvolvedinmathematics/oftendamagedaftermTBI.Theresultsoftheseanalyseswillbeavailableat theconferenceandwillallowus toseehowwhitematter isrelatedtomathematicsachievementinchildrenwithmTBI.

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C16.Developmental specialization of the parietal cortex for symbolic numericalmagnituderepresentation.StephanE.Vogel1,CeliaGoffin2andDanielAnsari2

1Georg‐August‐UniversityofGöttingen,Göttingen,Germany2NumericalCognitionLaboratory,WesternUniversity,London,Canada

Previous neuro‐imaging work has suggested that the intraparietal sulcus (IPS) becomesincreasingly specialized for representing symbolic numerical magnitudes over developmentaltime. In these studies, however, non‐numerical dimensions such as response selection and taskperformance were insufficiently controlled. Confounding influence on previous results canthereforenotberuledoutandobserveddevelopmentaldifferencesmaybebiased.Toreducetheimpactofconfoundingvariables,functionalMagneticResonanceImagingAdaptationwasusedinorder tomeasure the brain response of 6‐ to 14‐year‐old children. A single‐digit numeral wasrepeatedlypresentedonacomputerscreenandinterspersedwiththepresentationofnoveldigitsdeviating as a function of numerical‐ratio. Signal recovery in response to the presentation ofnumericaldeviantswasanalyzedforagedifferences.Resultsdemonstratethatageandnumerical‐ratio modulated signal recovery in the left IPS, suggesting an age‐related specialization ofsymbolicnumericalmagnituderepresentation in the lefthemisphere.Activationof theright IPSwasmodulatedbynumerical‐ratiobutnotby age.Together, the resultsprovidenovel evidencethat the left and right IPS may be differentially engaged in constructing symbolic numericalknowledgeoverdevelopmentaltime.

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C17.Thelinkbetweenpreschooler'sexecutivefunctionandtheoryofmind.AlexandraVolckaert1,M.Houssa1,NathalieNader‐Grosbois1andMarie‐PascaleNoël1

1UniversitéCatholiquedeLouvain,Louvain‐la‐Neuve,Belgium

In the last 20 years, the link between executive function (EF) and Theory of Mind (ToM)wasregularly explored in the scientific literature (e.g., Carlson,Mandell, &Williams, 2004; Hughes,Dunn,&White,1998;Kloo&Perner,2003).Resultsofthosestudiesarenotalwayscongruent.Theaimofthisstudywastoassessthespecificrelationbetweenperformanceof774‐to6‐year‐olds’BelgianfrenchspeakingchildrenonseveraltasksmeasuringEF(specificallyinhibition)anddifferenttasksinToM.Inaddition,parentsassessedToMandEFabilitiesbyquestionnaires.After controlling for age and intellectual quotient, some correlations between ToM and EFmeasureswerefound.TheseresultssuggestthatToMmaybeacrucialfactorforEFdevelopment(and inversely).Furthermore,regressionanalyseswillbepresentedanddiscussed.Someof thechildren received a training aiming at improving their TOM skills, others received a trainingaimingat improving theirEF skills and theothers receiveda control training.Analyses (still inprogress) will examine whether improvement in EF after the training is correlated withimprovementinTOMandconversely.Similaranalysesareinprogresswithexternalizingbehaviorpreschoolers (N = 63) and will be discussed, in comparison with typically developingpreschoolers.

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C18.Cognitiveinterventioninpreschoolers.AlexandraVolckaert1

1UniversitéCatholiquedeLouvain,Louvain‐la‐Neuve,Belgium

In this research wewant to observe if a cognitive intervention aiming at enhancing inhibitioncapacities, would not only have an impact on cognitive capacities, but also would lead tobehavioralchangeswithadecreaseinexternalbehaviouralproblems.47preschoolerstookpartinapretestinvolvingcognitive(attention,motorandcognitiveinhibition,flexibilityandworkingmemory) and behavioural measures (questionnaires and an observational paradigm forexternalizingbehaviors).Childrenwere thenrandomlyallocated to controlversusexperimentalgroups. Every child received 2 intervention sessions of 45 minutes per week during 8 weeks.While children from the control group received free hand craft sessions, children from theexperimentalgroupreceivedgames/exercisesaimingat increasingtheir inhibitioncapacities.Attheendoftheintervention,everychildfromeachgrouptookpart inthepost‐test.Weobservedsignificantdifferencesbetweencontrol andexperimentalgroup in favourof the lattergrouponinhibition, attention andworkingmemorymeasures. Some differences were alsomeasured onbehavioural measures. We thus show that it is possible to enhance inhibition capacities inpreschoolersandthatthishasalsoanimpactonothercognitivefunctionsaswellas,toasmallerextend,onexternalbehaviour.

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C19.Brain activity associated with translation from a visual to a symbolicrepresentationinAlgebraandGeometry.IlanaWaisman1,MarkLeikin1,ShelleyShaul1andRozaLeikin1

1UniversityofHaifa,Haifa,Israel

We investigate brain activity ‐ using ERP methodology ‐ of male adolescents when solvingmathematicalproblems inalgebraandgeometry.Thestudydesign linksmathematicseducationresearchwithneurocognitive studies.Both inalgebraandgeometry,weperformacomparativeanalysisofbrainactivityassociatedwiththetranslationfromvisualtosymbolicrepresentationsof mathematical objects. Algebraic tasks require translation from graphical to symbolicrepresentationofa function,whereastasks ingeometryrequiretranslationfromadrawingofageometric figure to a symbolic representation of its property. The findings demonstrate thatelectrical activity associated with the performance of geometrical tasks is stronger than thatassociatedwithsolvingalgebraic tasks.Additionally,we founddifferentscalp topographyof thebrainactivityassociatedwithsolvingalgebraicandgeometric tasks.Basedon the studyresults,weargue thatproblemsolving in algebra andgeometry is associatedwithdifferentpatternsofbrain activity. The findings lead to new research hypotheses aswell as to the explanationwhydifferentstudentsarenotequallygoodingeometryandalgebra.

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C20.Theborrowingeffectintwo‐digitsubtraction:Developmentalaspectsandneuralcorrelates.ChristinaWoitscheck1, ThomasDresler1,Mojtaba Soltanlou2, Liane Kaufmann3, SilviaPixner4,KorbinianMoeller2,Ann‐ChristineEhlis5andHans‐ChristophNürk6

1LEADGraduateSchool,EberhardKarlsUniversity,Tuebingen,Germany2KnowledgeMediaResearchCenter,Tuebingen,Germany3DepartmentofPsychiatry,GeneralHospital,HallinTyrol,Austria4InstituteofAppliedPsychology,UMITUniversity,HallinTyrol,Austria5DepartmentofPsychiatry,EberhardKarlsUniversity,Tübingen,Germany6DepartmentofPsychology,EberhardKarlsUniversity,Tübingen,Germany

Ingeneral,itisassumedthattheborrowingoperationinsubtraction(for42‐27,adecadeunithasto be borrowed) increases task difficulty, i.e. response latencies and error rates. However, ascomparedto thecarryeffect inaddition– theoreticalknowledgeandempiricalevidence for theborrowing effect in subtraction are relatively scarce. In two studies, we investigateddevelopmental change in children andpossible neural correlates of the borrowingoperation inadults.Ina longitudinalsampleofchildreninthirdandfourthgrade,respectively, theborrowingeffectcould be demonstrated for two‐digit subtraction problems. Additionally, the children showed alearning‐associateddecreaseinreactiontimesforsolvingsubtractionproblemswithinoneschoolyear,independentlyoftheborrowingeffectsuggestingdissociablemechanismsofborrowingandgeneral subtraction performance. By using functional near‐infrared spectroscopy (fNIRS) weexaminedthebrainactivityfortheborrowingeffectinasampleofadults.Activationwasobservedin a fronto‐parietal network underlying two‐digit subtraction. These activation patterns,particularly in the parietal cortex, were modulated by the borrowing operation. The resultssuggestthattheborrowingprocedureisadissociabledevelopmentalprocesswithspecificneuralcorrelates.

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C21.

Differentdevelopmentalonsetsofsymbolicapproximatearithmeticskillsacrosscountries:Hownumbersarenamedmatters.IroXenidou‐Dervou1,CamillaGilmore2,MennovanderSchoot1,ErnestvanLieshout1

1VUUniversityAmsterdam,Amsterdam,theNetherlands2LoughboroughUniversity,Leicestershire,UKApproximate arithmeticwith large symbolic (Arabic) numerosities is an important predictor ofmath.Evidencesuggeststhatthisskillemergesinkindergarten.Symbolicmentalrepresentationsareassumedtomapontopre‐existingnonsymbolicones(abstractmagnitudes).AlthoughArabicnumeralsareuniversal,numbernamingsystemsarenotand theycan influenceperformance innonverbaltasks.DutchnumbernamingiscognitivelymoredemandingcomparedtoEnglish,dueto the inversion property for numbers above twenty. We conducted two experiments: 1) Wetested English‐speaking and Dutch‐speaking children, before school entry, matched for exactaddition,countingandSES.DutchchildrenperformedworseanddemonstratedWMoverloadinsymbolic but not nonsymbolic approximate addition. Importantly, symbolic ‐not nonsymbolic‐approximate arithmetic correlated highly with number naming above twenty. 2) In the Dutchchildren, we found different developmental trajectories for nonsymbolic and symbolicapproximateaddition.Incontrasttononsymbolicapproximateaddition,theexpectedratioeffectfor symbolic was only demonstrated in Grade 1, and not earlier. Cumulatively, our resultshighlight the importance of number naming in numerical development and suggest that cross‐linguisticdifferencescanaffecttheonsetofsymbolicapproximation.

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Participants

Altun,ArifHacettepeUniversityCollegeofEducation,Ankara,Turkey altunar@gmail.com

Ansari,Daniel UniversityofWesternOntario,Canada daniel.ansari@uwo.ca

Askar,Petek TEDUniversity,Ankara,Turkey petek.askar@gmail.com

Babai,ReuvenTelAvivUniversity,DepartmentofScienceEducation,Israel reuvenb@post.tau.ac.il

Barenberg,Jonathan UniversityofMuenster,Germany barenberg@uni‐muenster.de

Beilock,SianL. UniversityofChicago,USA beilock@uchicago.de

Berse,TimoUniversityofMuenster,InstituteforPsychologyinEducation,Germany timo.berse@psy.uni‐muenster.de

Boriss,Karin UniversityofMuenster,Germany karin.boriss@uni‐muenster.de

Brod,GarvinMaxPlanckInstituteforHumanDevelopment,Berlin,Germany brod@mpib‐berlin.mpg.de

Bugden,Stephanie UniversityofWesternOntario,London,Canada sbugden2@uwo.ca

Bulthé,Jessica KULeuven,Belgium jessica.bulthe@ppw.kuleuven.be

Caviola,Sara UniversityofPadova,Italy sara.caviola@unipd.it

Cheng,JohnY.S.

GraduateInstituteofScienceEducation,NationalTaiwanNormalUniversity;DivisionofNeurosurgery,SurgicalDepartment,TaipeiMedicalUniversityH,Taiwan

john888ns@gmail.com

Chew,Cindy TheUniversityofMelbourne,Australia cindy.chewsw@hotmail.com

Commissar,Lia WellcomeTrust,London,UK l.commissar@wellcome.ac.uk

Crone,EvelineA. LeidenUniversity,theNetherlands ecrone@fsw.leidenuniv.nl

Czernochowski,Daniela TechnicalUniversityKaiserslautern,Germany czernochowski@sowi.uni‐kl.de

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DeSmedt,Bert KULeuven,Belgium bert.desmedt@ped.kuleuven.be

DeVisscher,Alice UCL,Louvain‐la‐Neuve,Belgium alice.devisscher@uclouvain.be

Dix,Annika Humboldt‐UniversitätzuBerlin,Germany annika.dix@hu‐berlin.de

Dorneles,BeatrizUFRGSFederalUniversityofRioGrandedoSul,PortoAlegre,Brazil bvdornel@terra.com.br

Eid,Aman FreeUniversityBerlin,Germany aman.eid@gmail.com

Ejersbo,Lisser AarhusUniversity,Copenhagen,Denmark lre@dpu.dk

Estudillo,Alejandro UniversityofKent,Canterbury,UK aje24@kent.ac.uk

Evers,WiebkeZNL‐TransferZentrumfürNeurowissenschaf‐tenundLernen,Ulm,Germany

wiebke.evers@znl‐ulm.de

Festman,Julia UniversityofPotsdam,Germany festman@uni‐potsdam.de

Furman,Tamar HaifaUniversity,TelAviv,Israel furmantamar@gmail.com

Garcia‐Orza,JavierUniversidaddeMálaga,LaboratoriodeCogniciónNumérica,Spain jgorza@uma.es

Gaschler,Robert UniversitätKoblenz‐Landau,Germany gaschler@uni‐landau.de

Gijselaers,JérômeOpenUniversityoftheNetherlands,Heerlen,theNetherlands jerome.gijselaers@ou.nl

Grabner,RolandH. Georg‐August‐UniversityGöttingen,Germany roland.grabner@psych.uni‐goettingen.de

GöçerŞahin,Sakine HacettepeUniversity,Ankara,Turkey sgocersahin@gmail.com

Golde,Sabrina Charité‐UniversitätsmedizinBerlin,Germany sabrina.golde@charite.de

Grond,UrsinaUniversityChildren’sHospital(CenterforMR‐Research,Children'sResearchCenter),Zurich,Switzerland

Ursina.Grond@kispi.uzh.ch

Hahn,Christian Georg‐August‐UniversityGöttingen,Germany christian.hahn@psych.uni‐goettingen,de

Hansen,Sonja UniversityofCologne,Germany sonja.hansen@uni‐koeln.de

97

Hauser,TobiasUniversityClinicsforChildandAdolescentPsychiatry(UCCAP),UniversityofZurich,Switzerland

tobias.hauser@uzh.ch

Houssa,Marine UniversitéCatholiquedeLouvain,Belgium marine.houssa@uclouvain.be

Karbach,Julia SaarlandUniversity,Saarbrücken,Germany j.karbach@mx.uni‐saarland.de

Kärner,TobiasLehrstuhlfürWirtschaftspädagogik,UniversitätBamberg,Germany tobias.kaerner@uni‐bamberg.de

Katzoff,AyeletLevinskyCollegeofEducationandGivaatWashington,Tzufim,Israel katzofayelet@gmail.com

Kim,Minkang TheUniversityofSydney,Australia minkang.kim@sydney.edu.au

Kovas,Yulia GoldsmithsUniversityofLondon,UK y.kovas@gold.ac.uk

Krabbendam,Lydia VUUniversity,Amsterdam,theNetherlands lydia.krabbendam@vu.nl

Krinzinger,HelgaUniversityHospitaloftheRWTHAachen,Germany hkrinzinger@ukaachen.de

Kucian,KarinUniversityChildren'sHospital,Zurich,Switzerland karin.kucian@kispi.uzh.ch

Kuroda,Yasufumi KyotoUniversityofEducation,Kyoto,Japan ykuroda@kyokyo‐u.ac.jp

Leikin,Mark UniversityofHaifa,Israel markl@edu.haifa.ac.il

Leikin,Roza UniversityofHaifa,Israel rozal@edu.haifa.ac.il

Lyons,Ian UniversityofWesternOntario,London,Canada ilyons@uwo.ca

Maertens,Bieke KULeuvenKulak,Kortrijk,Belgium bieke.maertens@ppw.kuleuven.be

Mammarella,IreneC. UniversityofPadova,Italy irene.mammarella@unipd.it

Mark‐Zigdon,Nitza LevinskyCollegeofEducation,TelAviv,Israel nitzamark@gmail.com

Matas,Antonio UniversityofMalaga,Spain amatas@uma.es

Matejko,Anna UniversityofWesternOntario,London,Canada amatejko@uwo.ca

98

McAteer,Erica InstituteofEducation,London,UK e.mcateer@ioe.ac.uk

Merkley,Rebecca UniversityofOxford,UK rebecca.merkley@psy.ox.ac.uk

Meylan,NicolasHauteécolepédagogiqueVAUD,Lausanne,Switzerland nicolas.meylan@unil.ch

Mutaf,Belde UniversityofLeuven(KULeuven),Belgium belde.mutaf@ppw.kuleuven.be

Newcombe,NoraS. TempleUniversity,Philadelphia,USA newcombe@temple.edu

Nisiforou,EfiCyprusUniversityofTechnology,Limassol,Cyprus nisiforou.efi@gmail.com

Nitsche,Michael GöttingenUniversityMedicalSchool,Germany mnitsch1@gwdg.de

Nosworthy,Nadia AndrewsUniversity,BerrienSprings,USA nosworthy@andrews.edu

Novosel,Branka OtvorenoUcilisteLittera,Samobor,Croatia branka.novosel1@zg.t‐com.hr

Obersteiner,Andreas TUMSchoolofEducation,Munich,Germany andreas.obersteiner@tum.de

Okamoto,Naoko RitsumeikanUniversity,Kyoto,Japan okamoto.naoko.jp@gmail.com

Olkun,Sinan TEDUniversity,Ankara,Turkey sinanolkun@gmail.com

Opitz,Bertram UniversityofSurrey,Guildford,UK b.opitz@surrey.ac.uk

Otten,Mara KULeuven,Belgium m.otten@student.vu.nl

Pakulak,Eric UniversityofOregon,USA pak@uoregon.edu

Partanen,MaritaUniversityofBritishColumbia,Vancouver,Canada partanen@alumni.ubc.ca

Paul,Jacob UniversityofMelbourne,Australia jpaacuolb@gmail.com

Peters,Lien KULeuven,Belgium lien.peters@ppw.kuleuven.be

Plukaard,Sarah VUUniversityAmsterdam,theNetherlands s.c.plukaard@vu.nl

99

Pollack,CourtneyHarvardGraduateSchoolofEducation,Cambridge,USA courtney.pollack@post.harvard.edu

Ram‐Tsur,Ronit Bar‐IlanUniversity,Holon,Israel ronitram@netvision.net.il

Rato,JoanaUniversidadeCatolicaPortuguesa,Lisbon,Portugal joana_rodrigues_rato@alunos.lisboa.ucp.pt

Raufelder,Diana FreeUniversityBerlin,Germany diana.raufelder@fu‐berlin.de

Reynvoet,Bert KULeuven,Belgium bert.reynvoet@kuleuven‐kulak.be

Rippon,Tamsyn Private,Bern,Switzerland tammyrawson@yahoo.co.uk

Rosenberg‐Lee,Mariam StanfordUniversity,PaloAlto,USA miriamrl@stanford.edu

Rousselle,LaurenceUnitédePsychologieduDéveloppementCognitif,Liège,Belgium laurence.rousselle@ulg.ac.be

Rubinstein,Orly UniversityofHaifa,Israel orly.rubinsten@gmail.com

Runge,Malte FreeUniversityBerlin,Germany malte.runge@fu‐berlin.de

Rütsche,BrunoInstituteforBehavioralSciences,ETHZurich,Switzerland bruno.ruetsche@ifv.gess.ethz.ch

Sallat,StephanSpeechandLanguagePedagogyandPathology,UniversityofErfurt,Germany stephan.sallat@uni‐erfurt.de

Sasanguie,Delphine KULeuven–FWO,Belgium Delphine.Sasanguie@kuleuven‐kulak.be

Schillinger,FriederL: Georg‐August‐UniversityGöttingen,Germany frieder.schillinger@uni‐goettingen.de

Schneider,Maria Georg‐August‐UniversityGöttingen,Germany mschneider@gwdg.de

Sinclaire‐Harding,Lysandra UniversityofCambridge,UK ls547@cam.ac.uk

Sokolowski,Moriah UniversityofWesternOntario,London,Canada h.moriah.sokolowski@gmail.com

Soltanlou,Mojtaba UniversityofTübingen,Germany mojtaba.soltanlou@uni‐tuebingen.de

SoniGarcía,AdrianaUniversityofBristol,GraduateSchoolofEducation,UK algunosnacenpostumos@yahoo.com

100

Stavy,Ruth TelAvivUniversity,Israel ruth@post.tau.ac.il

Stull,Lalena self‐employed,Italy lalasplace@hotmail.com

Sury,DanaUniversityofHaifa,thedepartmentforlearningdisabilities,Israel surydana@gmail.com

Tancig,SimonaUniversityofLjubljana,FacultyofEducation,Slovenia simona.tancig@guest.arnes.si

Tardif,EricHauteécolepédagogiqueVAUD,Lausanne,Switzerland eric.tardif@hepl.ch

Tolmie,Andrew InstituteofEducation,London,UK a.tolmie@ioe.ac.uk

Trezise,Kelly UniversityofMelbourne,Australia kelly.trezise@gmail.com

Vaessen,AnniekRegionalInstituteforDyslexia,Arnhem&MaastrichtUniversity,theNetherlands A.Vaessen@rid.nl

vanAtteveldt,NienkeVUUniversityAmsterdam,Fac.ofPsychology&Education,Dept.ofEducationalNeuroscience,theNetherlands

n.m.van.atteveldt@vu.nl

vanBeek,Leen KULeuven,Belgium leen.vanbeek@ppw.kuleuven.be

vanderVen,Sanne UtrechtUniversity,theNetherlands s.vanderven@uu.nl

vanHoogmoed,Anne UtrechtUniversity,theNetherlands a.h.vanhoogmoed@uu.nl

Vogel,StephanE. Georg‐AugustUniversityGöttingen,Germany stephan.vogel@psych.uni‐goettingen.destephanvog@gmail.com

Volckaert,Alexandra UniversitéCatholiquedeLouvain,Belgium alexandra.volckaert@uclouvain.be

Waisman,Ilana UniversityofHaifa,Israel waisman.ilana@gmail.com

Walk,LauraZNLTransferZentrumfürNeurowissenschaftenundLernen,Ulm,Germany

laura.walk@znl‐ulm.de

Woitscheck,ChristinaLEADGraduateSchool,EberhardKarlsUniversity,Tübingen,Germany christina.woitscheck@uni‐tuebingen.de

Xenidou‐Dervou,Iro VUUniversityAmsterdam,theNetherlands i.xenidou‐dervou@vu.nl

101

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