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dc.contributor.authorChan, Huilingen_US
dc.contributor.authorChen, Yong-Shengen_US
dc.contributor.authorChey, Li-Fenen_US
dc.contributor.authorChen, Tzu-Huaen_US
dc.contributor.authorChen, I-Tzuen_US
dc.date.accessioned2014-12-08T15:22:26Z-
dc.date.available2014-12-08T15:22:26Z-
dc.date.issued2009en_US
dc.identifier.isbn978-3-642-01512-0en_US
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/11536/15885-
dc.description.abstractMagnetoencephalography and electroencephalography are non-invasive instruments that can record magnetic fields and scalp potentials, respectively, induced from neuronal activities. The recordings are, superimposed signals contributed from the whole brain. Independent component analysis (ICA) can provide a way of decomposition by maximizing, the mutual independence of separated components. Beyond the temporal profile and topography provided by ICA, this work aims to estimate and map the cortical source distribution for each component. The proposed method first constructs a source space using lead field vectors for vertices on the cortical surface. By projecting the specified components to this source space, our method provides the corresponding spatiotemporal maps for these independent brain activities. Experiments using simulated brain activities clearly demonstrate the effectiveness and accuracy of the proposed method.en_US
dc.language.isoen_USen_US
dc.titleLead Field Space Projection for Spatiotemporal Imaging of Independent Brain Activitiesen_US
dc.typeProceedings Paperen_US
dc.identifier.journalADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 3, PROCEEDINGSen_US
dc.citation.volume5553en_US
dc.citation.spage512en_US
dc.citation.epage519en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000268029200056-
Appears in Collections:Conferences Paper