Morgan Botdorf & Tracy Riggins University of Maryland ... Documents/Botdorf_Riggins_Relations... ·...
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• Participants completed a forward digit span task (Gathercole & Adams, 1993). • Participant’s Digit Span Score was measured as the proportion of sequences correctly recalled. • A bivariate correlation showed that Digit Span Score was signiGicantly and positively correlated with age. • The following ROIs were created by averaging cortical thickness values for areas of interest: • ACC: left/right rostral anterior cingulate cortex and caudal anterior cingulate cortex • SPC: left/right superior parietal cortex • SFC: left/right superior frontal cortex • MFC: left/right rostral middle frontal cortex and caudal middle frontal cortex • Associations between cortical thickness and digit span performance were examined next. • Separate linear regressions were run entering each ROI as the predictor and Digit Span Score as the dependent variable. • Covariates: Total gray matter volume and gender. • Cortical thickness in each ROI was a signiGicant predictor of Digit Span Score, such that those with a thinner cortex in the speciGied areas performed better than those with a thicker cortex. • Associations between age and cortical thickness were explored. • Separate linear regressions were run entering age as the predictor and each ROI as the dependent variable. • Covariates: Total gray matter volume and gender. • Age was a signiGicant predictor of ACC volume, SPC volume, SFC volume, but not MFC volume. Methods Introduction Relations between working memory and cortical thickness in frontal and parietal regions in early childhood Morgan Botdorf & Tracy Riggins University of Maryland, College Park Participants • 181 children aged 4-8 years (M= 6.27, SD = 1.49 years, 92 females) completed the study. • Participants were part of a larger study examining the development of episodic memory in early childhood. MRI Data • T1-weighted high resolution (1mm 3 ) anatomical images were acquired from a Siemens 3T scanner with a 32- channel coil at the Maryland Neuroimaging Center using a standard structural MRI scan sequence. • Freesurfer v5.1 (Fischl, 2012) was used to calculate cortical thickness volumes and total gray matter volume. The Desikan-Killiany atlas was used for cortical parcellation (Desikan et al., 2006). • Boundary lines between CSF, gray matter, and white matter were visually inspected to ensure accuracy. Manual edits were made when necessary. Methods: MRI Data Discussion References • These results suggest that even in early childhood, there are associations between WM abilities and thickness in cortical areas known to support WM in adults. • Age was negatively associated with the thickness of ACC, SPC, SFC, but not MFC. • Thickness in each ROI was negatively associated with WM as measured by Digit Span. • Consistent with Kharitonova’s Gindings (2013), our results support a relation between SPC and WM, but did not support a mediation. However, our results did suggest that ACC is not only associated with WM, but mediates the relation between age and WM. • Future research should focus on investigating longitudinal changes in these cortical areas as they relate to WM to increase the present understanding of the relation between cortical thickness and improvements in WM during childhood. • Working memory (WM) changes rapidly in early childhood, but it remains unclear how cortical regions that support these abilities in adults relate to WM changes in children. • Cortical thickness may be a useful measure in investigating this association, as age-related changes in cortical thickness may support improvements in cognitive abilities as a result of synaptic pruning and increased myelination (Sowell et al., 2004). • However, only limited research has investigated how cortical thickness relates to WM abilities in childhood. For example, Kharitonova and colleagues (2013) found that thickness in superior parietal cortex (SPC), but not anterior cingulate cortex (ACC), related to WM. However, SPC did not mediate the relation between age and WM. • The present study extends this research by investigating the relation between performance on a digit span task and cortical thickness of speciDic areas related to WM: ACC, SPC, superior frontal cortex (SFC), and middle frontal cortex (MFC). 1. Desikan, R., Segonne, F., Fischl, B., Quinn, B., Dickerson, B., Blacker, D…Killiany, R. (2006). An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage, 31(3), 968-80. 2. Fischl, B. (2012). FreeSurfer. NeuroImage, 62, 774–781. doi:10.1016/j.neuroimage. 2012.01.021. 3. Gathercole, S., & Adams, A. (1993). Phonological working memory in very young children. Developmental Psychology, 29(4), 770-78. 4. Hayes, (2013). Introduction to mediation, moderation, and condition process analysis: A regression-based approach. New York: Guilford Press. 5. Kharitonova, M., Martin, R., Gabrieli, J., & Sheridan, M. (2013). Cortical gray-matter thinning is associated with age-related improvements on executive function tasks. Developmental Cognitive Neuroscience, 6, 61-71. 6. Sowell, E.R., Thompson, P.M., Leonard, C.M., Welcome, S.E., & Kan, E., Toga, A.W. (2004). Longitudinal mapping of cortical thickness and brain growth in normal children. The Journal of Neuroscience, 24(38), 8223-31. For questions or comments, please contact [email protected] Results: Age-Cortical Thickness Associations • A mediation model was tested using Hayes’ SPSS Process macro (Hayes, 2013). Separate models were run with age as the predictor, each ROI as the mediator, and Digit Span Score as the dependent variable. SigniGicant mediation was observed for the model with ACC as the mediator. SpeciGically, there was a signiGicant indirect effect of age on Digit Span Score through ACC thickness, b = 0.008, SE=0.01, CI [0.0019, 0.0191]. Age ROI ACC SPC SFC MFC Digit Span Performance Results: Mediation Analysis Results: Cortical Thickness-WM Associations ACC SFC Acknowledgements We would like to acknowledge support from the National Science Foundation and the National Institutes of Health (Grant number RO1 HD079518-04). MFC 0 0.2 0.4 0.6 0.8 1 1.2 3 4 5 6 7 8 9 10 Digit Span Score Age (yrs) r(181)=.57, p < .001 Results: Age-Digit Span Associations SPC ACC SPC SFC b=-0.05, SE=0.01, p<0.001 b=-0.02, SE=0.008, p=0.008 b=-0.02, SE=0.009, p=0.03 ACC Thickness SPC Thickness SFC Thickness Age Age Age ACC b=-0.27, SE=0.06, p<0.01 ACC Thickness SFC b=-0.22, SE=0.07, p=<0.01 SFC Thickness b=-0.24, SE=0.08, pr=-0.21, p=0.004 SPC Thickness SPC MFC b=-0.26, SE=0.07, pr=-0.17, p=0.03 MFC Thickness Digit Span Score Digit Span Score Digit Span Score Digit Span Score
Transcript of Morgan Botdorf & Tracy Riggins University of Maryland ... Documents/Botdorf_Riggins_Relations... ·...
• Participantscompletedaforwarddigitspantask(Gathercole&Adams,1993).
• Participant’sDigitSpanScorewasmeasuredastheproportionofsequencescorrectlyrecalled.
• AbivariatecorrelationshowedthatDigitSpanScorewassigniGicantlyandpositivelycorrelatedwithage.
• ThefollowingROIswerecreatedbyaveragingcorticalthicknessvaluesforareasofinterest:
• ACC:left/rightrostralanteriorcingulatecortexandcaudalanteriorcingulatecortex
• SPC:left/rightsuperiorparietalcortex• SFC:left/rightsuperiorfrontalcortex• MFC:left/rightrostralmiddlefrontalcortexandcaudalmiddlefrontalcortex
• Associationsbetweencorticalthicknessanddigitspanperformancewereexaminednext.• SeparatelinearregressionswererunenteringeachROIasthepredictorandDigitSpanScoreasthedependentvariable.
• Covariates:Totalgraymattervolumeandgender.• CorticalthicknessineachROIwasasigniGicantpredictorofDigitSpanScore,suchthatthosewithathinnercortexinthespeciGiedareasperformedbetterthanthosewithathickercortex.
• Associationsbetweenageandcorticalthicknesswereexplored.• SeparatelinearregressionswererunenteringageasthepredictorandeachROIasthedependentvariable.
• Covariates:Totalgraymattervolumeandgender.• AgewasasigniGicantpredictorofACCvolume,SPCvolume,SFCvolume,butnotMFCvolume.
Methods
Introduction
Relationsbetweenworkingmemoryandcorticalthicknessinfrontalandparietalregionsinearlychildhood
MorganBotdorf&TracyRigginsUniversityofMaryland,CollegePark
Participants• 181childrenaged4-8years(M=6.27,SD=1.49years,92females)completedthestudy.
• Participantswerepartofalargerstudyexaminingthedevelopmentofepisodicmemoryinearlychildhood.
MRIData• T1-weightedhighresolution(1mm3)anatomicalimageswereacquiredfromaSiemens3Tscannerwitha32-channelcoilattheMarylandNeuroimagingCenterusingastandardstructuralMRIscansequence.
• Freesurferv5.1(Fischl,2012)wasusedtocalculatecorticalthicknessvolumesandtotalgraymattervolume.TheDesikan-Killianyatlaswasusedforcorticalparcellation(Desikanetal.,2006).
• BoundarylinesbetweenCSF,graymatter,andwhitematterwerevisuallyinspectedtoensureaccuracy.Manualeditsweremadewhennecessary.
Methods:MRIData
Discussion
References
• Theseresultssuggestthateveninearlychildhood,thereareassociationsbetweenWMabilitiesandthicknessincorticalareasknowntosupportWMinadults.
• AgewasnegativelyassociatedwiththethicknessofACC,SPC,SFC,butnotMFC.
• ThicknessineachROIwasnegativelyassociatedwithWMasmeasuredbyDigitSpan.
• ConsistentwithKharitonova’sGindings(2013),ourresultssupportarelationbetweenSPCandWM,butdidnotsupportamediation.However,ourresultsdidsuggestthatACCisnotonlyassociatedwithWM,butmediatestherelationbetweenageandWM.
• FutureresearchshouldfocusoninvestigatinglongitudinalchangesinthesecorticalareasastheyrelatetoWMtoincreasethepresentunderstandingoftherelationbetweencorticalthicknessandimprovementsinWMduringchildhood.
• Workingmemory(WM)changesrapidlyinearlychildhood,butitremainsunclearhowcorticalregionsthatsupporttheseabilitiesinadultsrelatetoWMchangesinchildren.
• Corticalthicknessmaybeausefulmeasureininvestigatingthisassociation,asage-relatedchangesincorticalthicknessmaysupportimprovementsincognitiveabilitiesasaresultofsynapticpruningandincreasedmyelination(Sowelletal.,2004).
• However,onlylimitedresearchhasinvestigatedhowcorticalthicknessrelatestoWMabilitiesinchildhood.Forexample,Kharitonovaandcolleagues(2013)foundthatthicknessinsuperiorparietalcortex(SPC),butnotanteriorcingulatecortex(ACC),relatedtoWM.However,SPCdidnotmediatetherelationbetweenageandWM.
• ThepresentstudyextendsthisresearchbyinvestigatingtherelationbetweenperformanceonadigitspantaskandcorticalthicknessofspeciDicareasrelatedtoWM:ACC,SPC,superiorfrontalcortex(SFC),andmiddlefrontalcortex(MFC).
1. Desikan,R.,Segonne,F.,Fischl,B.,Quinn,B.,Dickerson,B.,Blacker,D…Killiany,R.(2006).AnautomatedlabelingsystemforsubdividingthehumancerebralcortexonMRIscansintogyralbasedregionsofinterest.Neuroimage,31(3),968-80.
2. Fischl,B.(2012).FreeSurfer.NeuroImage,62,774–781.doi:10.1016/j.neuroimage.2012.01.021.
3. Gathercole,S.,&Adams,A.(1993).Phonologicalworkingmemoryinveryyoungchildren.DevelopmentalPsychology,29(4),770-78.
4. Hayes,(2013).Introductiontomediation,moderation,andconditionprocessanalysis:Aregression-basedapproach.NewYork:GuilfordPress.
5. Kharitonova,M.,Martin,R.,Gabrieli,J.,&Sheridan,M.(2013).Corticalgray-matterthinningisassociatedwithage-relatedimprovementsonexecutivefunctiontasks.DevelopmentalCognitiveNeuroscience,6,61-71.
6. Sowell,E.R.,Thompson,P.M.,Leonard,C.M.,Welcome,S.E.,&Kan,E.,Toga,A.W.(2004).Longitudinalmappingofcorticalthicknessandbraingrowthinnormalchildren.TheJournalofNeuroscience,24(38),8223-31.
Forquestionsorcomments,[email protected]
Results:Age-CorticalThicknessAssociations
• AmediationmodelwastestedusingHayes’SPSSProcessmacro(Hayes,2013).Separatemodelswererunwithageasthepredictor,eachROIasthemediator,andDigitSpanScoreasthedependentvariable.SigniGicantmediationwasobservedforthemodelwithACCasthemediator.SpeciGically,therewasasigniGicantindirecteffectofageonDigitSpanScorethroughACCthickness,b=0.008,SE=0.01,CI[0.0019,0.0191].
Age
ROIACCSPCSFCMFC
DigitSpanPerformance
Results:MediationAnalysis
Results:CorticalThickness-WMAssociations
ACC
SFC
AcknowledgementsWewouldliketoacknowledgesupportfromtheNationalScienceFoundationandtheNationalInstitutesofHealth(GrantnumberRO1HD079518-04).
MFC
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Age(yrs)
r(181)=.57,p<.001
Results:Age-DigitSpanAssociations
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SPC SFCb=-0.05,SE=0.01,p<0.001
b=-0.02,SE=0.008,p=0.008 b=-0.02,SE=0.009,p=0.03
ACCThickness
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b=-0.27,SE=0.06,p<0.01
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b=-0.22,SE=0.07,p=<0.01
SFCThickness
b=-0.24,SE=0.08,pr=-0.21,p=0.004
SPCThickness
SPC MFC
b=-0.26,SE=0.07,pr=-0.17,p=0.03
MFCThickness
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DigitSpanScore
DigitSpanScore
DigitSpanScore
