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Article: Independent components of magnetoencephalography: Localization

TitleIndependent components of magnetoencephalography: Localization
Authors
Issue Date2002
Citation
Neural Computation, 2002, v. 14, n. 8, p. 1827-1858 How to Cite?
AbstractWe applied second-order blind identification (SOBI), an independent component analysis method, to MEG data collected during cognitive tasks. We explored SOBI's ability to help isolate underlying neuronal sources with relatively poor signal-to-noise ratios, allowing their identification and localization. We compare localization of the SOBI-separated components to localization from unprocessed sensor signals, using an equivalent current dipole modeling method. For visual and somatosensory modalities, SOBI preprocessing resulted in components that can be localized to physiologically and anatomically meaningful locations. Furthermore, this preprocessing allowed the detection of neuronal source activations that were otherwise undetectable. This increased probability of neuronal source detection and localization can be particularly beneficial for MEG studies of higher-level cognitive functions, which often have greater signal variability and degraded signal-to-noise ratios than sensory activation tasks.
Persistent Identifierhttp://hdl.handle.net/10722/228015
ISSN
2015 Impact Factor: 1.626
2015 SCImago Journal Rankings: 1.207

 

DC FieldValueLanguage
dc.contributor.authorTang, Akaysha C.-
dc.contributor.authorPearlmutter, Barak A.-
dc.contributor.authorMalaszenko, Natalie A.-
dc.contributor.authorPhung, Dan B.-
dc.contributor.authorReeb, Bethany C.-
dc.date.accessioned2016-08-01T06:44:58Z-
dc.date.available2016-08-01T06:44:58Z-
dc.date.issued2002-
dc.identifier.citationNeural Computation, 2002, v. 14, n. 8, p. 1827-1858-
dc.identifier.issn0899-7667-
dc.identifier.urihttp://hdl.handle.net/10722/228015-
dc.description.abstractWe applied second-order blind identification (SOBI), an independent component analysis method, to MEG data collected during cognitive tasks. We explored SOBI's ability to help isolate underlying neuronal sources with relatively poor signal-to-noise ratios, allowing their identification and localization. We compare localization of the SOBI-separated components to localization from unprocessed sensor signals, using an equivalent current dipole modeling method. For visual and somatosensory modalities, SOBI preprocessing resulted in components that can be localized to physiologically and anatomically meaningful locations. Furthermore, this preprocessing allowed the detection of neuronal source activations that were otherwise undetectable. This increased probability of neuronal source detection and localization can be particularly beneficial for MEG studies of higher-level cognitive functions, which often have greater signal variability and degraded signal-to-noise ratios than sensory activation tasks.-
dc.languageeng-
dc.relation.ispartofNeural Computation-
dc.titleIndependent components of magnetoencephalography: Localization-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1162/089976602760128036-
dc.identifier.pmid12180404-
dc.identifier.scopuseid_2-s2.0-0036676210-
dc.identifier.volume14-
dc.identifier.issue8-
dc.identifier.spage1827-
dc.identifier.epage1858-

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