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《Dynamic Changes of ICA-Derived EEG Functional Connectivity in the Resting State》由會(huì)員上傳分享，免費(fèi)在線閱讀，更多相關(guān)內(nèi)容在學(xué)術(shù)論文-天天文庫(kù)。
1、rHumanBrainMapping34:852–868(2013)rDynamicChangesofICA-DerivedEEGFunctionalConnectivityintheRestingState1,2*TomasRos,1,31Jean-LonChen,andJohnH.Gruzelier1DepartmentofPsychology,Goldsmiths,UniversityofLondon,London,UnitedKingdom2DepartmentofPhysicalMedicine&Rehabilitation,ChangGungMemorialHospitala
2、ndCollegeofMedicine,ChangGungUniversity,Tao-Yuan,Taiwan3DepartmentofPsychiatry,UniversityofWesternOntario,London,Ontario,CanadarrAbstract:Anemergingissueinneuroscienceishowtoidentifybaselinestate(s)andaccompanyingnetworkstermedrestingstatenetworks(RSNs).Althoughindependentcomponentanalysis(ICA)in
3、fMRIstudieshaselucidatedsynchronousspatiotemporalpatternsduringcognitivetasks,lessisknownaboutthechangesinEEGfunctionalconnectivitybetweeneyesclosed(EC)andeyesopen(EO)states,twotraditionallyusedbaselineindices.Hereweinvestigatedhealthysubjects(n?27)inECandEOemployingafour-stepanalyticapproachtoth
4、eEEG:(1)groupICAtoextractindependentcomponents(ICs),(2)standardizedlow-resolutiontomographyanalysis(sLORETA)forcorticalsourcelocalizationofICnetworknodes,followedby(3)graphtheoryforfunctionalconnectivityestimationofepochwiseICband-power,and(4)circumscribingICsimilaritymeasuresviahierarchicalclust
5、eranalysisandmultidimensionalscaling(MDS).Ourproof-of-conceptresultsonalpha-bandpowerdemonstrate?vestatisticallyclusteredgroupswithfrontal,central,parietal,occipitotemporal,andoccipitalsources.Importantly,duringEOcomparedwithEC,graphanalysesrevealedtwosalientfunctionalnetworkswithfrontoparietalco
6、nnectivity:amoremedialnetworkwithnodesinthemPFC/precuneuswhichoverlapswiththedefault-modenetwork(DMN),andamorelateralizednetworkcomprisingthemiddlefrontalgyrusandinferiorparietallobule,coin-cidingwiththedorsalattentionnetwork(DAN).Furthermore,aseparateMDSanalysisofICssupportedtheemergenceofapatte
7、rnofincreasedproximity(sharedinformation)betweenfrontalandparietalclustersspeci?callyfortheEOstate.Weproposethatthedisclosedcomponentgroupsandtheirsource-derivedEEGfunctionalconnectivitymapsmaybeavaluablemethodforeluci
