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首页 ★★★脑磁波no3

★★★脑磁波no3.pdf

★★★脑磁波no3

hunyuanlingtongy
2010-11-14 0人阅读 举报 0 0 暂无简介

简介:本文档为《★★★脑磁波no3pdf》,可适用于人文社科领域

運動相關腦磁波之腦部信號源動態造運動相關腦磁波之腦部信號源動態造影影ImagingCorticalSourceImagingCorticalSourceDynamicsofMovementDynamicsofMovementRelatedRelatedNeuromagneticFieldNeuromagneticField計畫編號:計畫編號:NSCNSCEE執行期限:執行期限:年年月月日至日至年年月月日日主持人:陳麗芬主持人:陳麗芬助理研究員助理研究員國立陽明大學國立陽明大學神經科學研究中心神經科學研究中心特約助理研究員特約助理研究員臺北榮民總醫院臺北榮民總醫院教學研究部教學研究部共同主持人:陳永昇共同主持人:陳永昇助理教授助理教授國立交通大學國立交通大學資訊工程學系資訊工程學系謝仁俊謝仁俊主治醫師主治醫師臺北榮民總醫院臺北榮民總醫院教學研究部教學研究部教授暨所長教授暨所長國立陽明大學國立陽明大學衛生資訊與決策研究所衛生資訊與決策研究所計畫參與人員:劉宏毅、李宗展、黃勁霖、鄭志瑜計畫參與人員:劉宏毅、李宗展、黃勁霖、鄭志瑜研究生研究生國立交通大學國立交通大學資訊工程學系資訊工程學系MEG(MEG(MagnetoEncephaloGraphyMagnetoEncephaloGraphy))VectorviewVectorview:channelsmanufacturedby:channelsmanufacturedbyElektaElektaIncinstalledinTaipeiVeteransIncinstalledinTaipeiVeteransGeneralHospitalGeneralHospitalMEGSourceModelingMEGSourceModelingzzForwardproblem:Forwardproblem:zzInput:thepositions,theamplitudeandtheInput:thepositions,theamplitudeandtheorientationsofthesourcecurrentdipolesorientationsofthesourcecurrentdipoleszzOutput:toestimatethemeasureddataOutput:toestimatethemeasureddatafromMEGsensorsfromMEGsensorszzInverseproblem:Inverseproblem:zzInput:asetofmeasureddataInput:asetofmeasureddatazzOutput:toestimatetheparametersOutput:toestimatetheparametersrepresentingthesourcecurrentdipoles,representingthesourcecurrentdipoles,includingpositions,theamplitudeandtheincludingpositions,theamplitudeandtheorientationsorientations“Sourcemodel“Equivalentcurrentdipole(ECD)“Parameters:location,amplitude,andorientation“Fix,rotating,movingdipoles“Headmodel“relatedtothecomputationofvolumecurrent“Sphericalmodel“Boundaryelementmodel(BEM)“Finiteelementmodel(FEM)ForwardModelForwardModelSourceModelSourceModelMaxwellMaxwell‘‘sequationssequations::E:electricfieldE:electricfield:dielectricconstant:dielectricconstantB:magneticfieldB:magneticfield:permeability:permeabilityJ:currentdensityJ:currentdensity:chargedensity:chargedensity()tEtB∂∂=×∇=⋅∇∂∂−=×∇=⋅∇εµερεµρSourceModel(cont)SourceModel(cont)zzHeadisaconductorconsistingofHeadisaconductorconsistingofdifferentdifferenttissuestissueszzUsingGreenUsingGreen’’stheorywithboundarystheorywithboundaryconditionwecanobtainthemagneticfieldconditionwecanobtainthemagneticfield:outwarddirectedunitnormalvector:outwarddirectedunitnormalvector:conductivityoutsidethesurface:conductivityoutsidethesurface:conductivityinsidethesurface:conductivityinsidethesurfacedd::rrrrqq()()()()()r'r'nrrBrBdSddViimiii⎟⎠⎞⎜⎝⎛×−−=∫∑=−∞σσπµ()()∫×=∞Gpdddr'r'rBJπµ()rniHeadModelHeadModelzzBoundaryBoundaryelementelementmethodmodel(BEM)methodmodel(BEM)zzSphericalheadmodelSphericalheadmodelrr:sensorposition:sensorpositionrrqq:positionofdipole:positionofdipoleqq:momentofdipole:momentofdipoleHeadModel(cont)HeadModel(cont)zzBecausetheBecausetheradialmagneticfieldiszeroradialmagneticfieldiszeroininthesphericalheadmodel,wecandirectlythesphericalheadmodel,wecandirectlysolvetheMEGforwardproblemsolvetheMEGforwardproblem()()()()()()qqqqqFFFrr,rrqrqrr,rr,rB∇⋅×−×=πµ()()()()()qqqqdddddddFddFrrrrrrrrr,rrrrrr,⎟⎠⎞⎜⎝⎛⋅⎟⎟⎠⎞⎜⎜⎝⎛⋅=∇⋅−=SourceLocalizationSourceLocalizationzzBeamformerBeamformer––AkindofspatialfilterAkindofspatialfilter––WidelyappliedinradarWidelyappliedinradarandsonarandsonar––RegardedasaRegardedasaweightedvirtualsensorweightedvirtualsensorzzLeadfieldLeadfield––AkindofsimplespatialAkindofsimplespatialfilterfilterLinearlyConstrainedMinimumLinearlyConstrainedMinimumVarianceBeamformerVarianceBeamformerzzToprovideasolutiontoinverseproblemToprovideasolutiontoinverseproblemzzTopassbrainactivitywithunitgainataTopassbrainactivitywithunitgainataspecifiedlocationwhileattenuatingspecifiedlocationwhileattenuatingactivityoriginatingatotherlocationsactivityoriginatingatotherlocationssubjecttosubjecttovanvanVeenVeen,,W:filter,W:filter,qqoo:source,y:filteroutput,H:forwardsolutiony:filteroutput,H:forwardsolutiontrtrCCyy:varianceofy:varianceofyyqoCwtrmin=ooqqhwLCMVBeamformer(cont)LCMVBeamformer(cont)zzSolvingbyLagrangemultipliersyieldsSolvingbyLagrangemultipliersyieldsx:measurementx:measurementzzRefinementRefinementtradeoffbetweenspatialspecificitytradeoffbetweenspatialspecificityandnoisesensitivityandnoisesensitivityRobinson,Robinson,μμ:Backus:BackusGilbertregularizationparameter(Gilbertregularizationparameter(<<μμ<<∞∞))ΣΣ:variancematrixofsensornoise:variancematrixofsensornoiseooooqxTqxTqqhChChw−−=ooooqxTqxTqqhChChw−−∑∑=µµSourceStrengthReconstructionSourceStrengthReconstructionzzEstimatingtheexpectationvalueoftheEstimatingtheexpectationvalueofthesourcepowersourcepowerzzNormalizationNormalizationQ:noisecovariancematrixQ:noisecovariancematrix{}^trVar−−=oooqxTqqhCh{}{}^trtrVar−−−−=oooooNqTqqxTqqhQhhChCorticalCorticalbasedNeuromagneticbasedNeuromagneticFunctionalImagingFunctionalImagingzzNetworksofcorticalneuralcellassembliesareNetworksofcorticalneuralcellassembliesarethemaingeneratorsofMEGEEGsignalsthemaingeneratorsofMEGEEGsignals((BailletBailletetal)etal)OurApproachOurApproachzzAnatomyAnatomyconstrainedconstrained––corticalsurfacecorticalsurface––normalvectornormalvectorzzReducetimecomplexityReducetimecomplexityfromO(nfromO(n)toO(n)toO(n))MRI(MagneticResonanceImaging)MRI(MagneticResonanceImaging)InstalledinTaipeiVeteransGeneralHospitalInstalledinTaipeiVeteransGeneralHospitalCorticalSurfaceReconstructionCorticalSurfaceReconstructionzzToolsTools::FreeSurfer(MITFreeSurfer(MITHavardHavardUniversity)University)Surefit(UniversityofWashington)Surefit(UniversityofWashington)TheMRIvolumeTheskullstrippedvolumeThelefthemisphere’sorigsurfaceRenderingRenderingVTK(VisualizationToolkit)VTK(VisualizationToolkit)zzAfreeandopensourcesystemforDcomputerAfreeandopensourcesystemforDcomputergraphicsgraphicszzHigherlevelofabstractionthanrenderingHigherlevelofabstractionthanrenderinglibrarieslikeOpenGLlibrarieslikeOpenGLzzAwidevarietyofvisualizationalgorithmsAwidevarietyofvisualizationalgorithmsincludingscalar,vector,textureetcincludingscalar,vector,textureetcMaterialsMaterialszzMEGrecordingsMEGrecordings––WholeWholeheadchannelsMEGsystem(headchannelsMEGsystem(VectorviewVectorview,,NeuromagNeuromag,,Finland)Finland)––SelfSelfpacedrightindexfingerliftingmovementaroundeverypacedrightindexfingerliftingmovementaroundeverysecondsseconds––HzsamplingrateHzsamplingrate––~epochs(eachfrom~epochs(eachfromsectosec)sectosec)zzMEGpreprocessingMEGpreprocessing−−SSP(SignalSpaceProjection)SSP(SignalSpaceProjection)−−EOG(ElectroEOG(ElectroOculoGramOculoGram)rejection)rejection−−BaselinecorrectionBaselinecorrection−−SynchronizedaveragingSynchronizedaveraging−−BandpassBandpassfilteringfilteringzzMRIscanningMRIscanning––SiemensMRISiemensMRI––Fieldofview:xx(mm)Fieldofview:xx(mm)––Imagevolumesize:xxImagevolumesize:xxSignalPreprocessingCorticalsurfaceReconstructionSourceLocalizationWorkflowVisualizationNeuromagneticImagingofBrainActivity•(a)EstimatedpowerSPMofbrainactivity(d)Somatosensoryrepresentation•(b)LocationofpeakpSPMinMRI(c)Reconstructedsourcewaveform¾右圖解:(a)為左腦皮質使用光束構成法進行活動源估算的活動顯著性(ρ)區域分佈(b)、(c)分別為(a)圖中具最顯著性皮質位置(圖中白點)之相對磁振造影影像及重建神經活動序列信號s該位置與文獻上手指運動相關皮質區(d)相吻合•Motorloop•ReconstructedspatiotemporaldynamicsofbrainactivityNeuromagneticImagingofBrainActivity¾右圖是從展示影片中ms至ms擷取出的張畫面紅圈標示的位置即是活化訊號最強烈區與相關腦神經生理知識中有關感覺運動系統(sensorimotorsystem)控制肢體運動時腦部活化區域之動態機轉(mechanism)(上圖)是非常吻合的由此可顯示本軟體系統能正確可靠地分析腦部活動動態分佈。ReferencesReferenceszzMosherJC,LeachyRM,andLewisPSMosherJC,LeachyRM,andLewisPS““EEGandMEG:ForwardSolutionsforInverseEEGandMEG:ForwardSolutionsforInverseMethods,Methods,””IEEETransactiononBiomedicalEngineering,IEEETransactiononBiomedicalEngineering,vol,ppvol,pp,,zzRobisonSE,andRobisonSE,andVrbaVrbaJJ““FunctionalFunctionalNeuroimagingNeuroimagingbySyntheticAperturebySyntheticApertureMagnetometryMagnetometry,,””CTFCTFSystemIncPortSystemIncPortCoquitlamCoquitlam,Canada,,Canada,zzSekiharaSekiharaKetalKetal““ReconstructingReconstructingSpatioSpatioTemporalActivitiesofNeuralSourcesUsinganMEGTemporalActivitiesofNeuralSourcesUsinganMEGVectorBeamformerTechnique,VectorBeamformerTechnique,””IEEETransactiononBiomedicalEngineering,IEEETransactiononBiomedicalEngineering,vol,no,vol,no,pppp,,zzAvillaSetalAvillaSetal““TheVTKUserTheVTKUser’’sGuide,sGuide,””KitwareKitware,Inc,,Inc,zzVanEssenDCetalVanEssenDCetal““AnIntegratedSoftwareSystemforSurfaceAnIntegratedSoftwareSystemforSurfacebasedAnalysesofCerebralbasedAnalysesofCerebralCortex,Cortex,””JournalofAmericanMedicalInformaticsAssociationJournalofAmericanMedicalInformaticsAssociation((SpecialissueontheHumanBrainSpecialissueontheHumanBrainProjectProject))vol,ppvol,pp,,zzVanVanVeenVeenBDetalBDetal““LocalizationofBrainElectricalActivityviaLinearlyConstrainLocalizationofBrainElectricalActivityviaLinearlyConstrainedMinimumedMinimumVarianceSpatialFiltering,VarianceSpatialFiltering,””IEEETransactiononBiomedicalEngineering,IEEETransactiononBiomedicalEngineering,vol,no,ppvol,no,pp,,zzSchroederW,MartinK,andSchroederW,MartinK,andLorensenLorensenBB““TheVisualizationToolkit,TheVisualizationToolkit,””rdedition,rdedition,KitwareKitware,Inc,,Inc,zzVanVanVeenVeenBD,andBuckleyKBD,andBuckleyK““Beamforming:aVersatileApproachtoSpatialFiltering,Beamforming:aVersatileApproachtoSpatialFiltering,””IEEEIEEEASSPMagazine,ASSPMagazine,vol,ppvol,pp,,zzGrossJetalGrossJetal““DynamicImagingofCoherentSources:StudyingNeuralInteractionDynamicImagingofCoherentSources:StudyingNeuralInteractionsintheHumansintheHumanBrain,Brain,””ProceedingsoftheNationalAcademyofSciences,ProceedingsoftheNationalAcademyofSciences,vol,no,ppvol,no,pp,,

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