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dc.contributor.authorHe, Bin
dc.contributor.authorSohrabpour, Abbas
dc.contributor.authorBrown, Emery Neal
dc.contributor.authorLiu, Zhongming
dc.date.accessioned2019-12-17T21:52:26Z
dc.date.available2019-12-17T21:52:26Z
dc.date.issued2018-06
dc.identifier.issn1523-9829
dc.identifier.issn1545-4274
dc.identifier.urihttps://hdl.handle.net/1721.1/123301
dc.description.abstractBrain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications. Keywords: electrophysiological source imaging; EEG; MEG; source localization; functional connectivity; inverse problemen_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant EB021027)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant NS096761)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant MH114233)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant AT009263)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant EY023101)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant MH104402)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant EB008389)en_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant HL117664)en_US
dc.description.sponsorshipNational Science Foundation (Grant CBET-1450956)en_US
dc.description.sponsorshipNational Science Foundation (Grant DGE-1069104)en_US
dc.publisherAnnual Reviewsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1146/annurev-bioeng-062117-120853en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceProf. Brown via Courtney Crummetten_US
dc.titleElectrophysiological Source Imaging: A Noninvasive Window to Brain Dynamicsen_US
dc.typeArticleen_US
dc.identifier.citationHe, Bin et al. "Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics." Annual Review of Biomedical Engineering 20 (June 2018): 171-196. © 2018 Annual Reviewsen_US
dc.contributor.departmentHarvard University--MIT Division of Health Sciences and Technologyen_US
dc.relation.journalAnnual Review of Biomedical Engineeringen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2019-12-05T17:39:20Z
mit.journal.volume20en_US
mit.journal.issue1en_US


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