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Conference Paper: Temporal delays in blind identification of primary somatosensory cortex

TitleTemporal delays in blind identification of primary somatosensory cortex
Authors
KeywordsBlind source separation (BSS)
Issue Date2004
Citation
Proceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004, v. 7, p. 4222-4227 How to Cite?
AbstractBlind source separation (BSS) is an emerging statistical and data processing technique which aims to recover unobservable source signals from the observed mixtures. Second-order blind identification (SOBI) is one BSS algorithm that relies on stationary second-order statistics based on joint diagonalization of a set of covariance matrices. In simulations, the use of multiple covariance matrices computed with different time delays, τs, was beneficial for source separation, particularly when the underlying sources had highly overlapping spectra. Given the spectral overlap between actual brain sources, we experimented with different sets of temporal delays to empirically determine their effects on the isolation of electrical signals arising from a temporally and spatially well characterized brain location, the primary somatosensory cortex (SI). Using EEG data collected during median nerve stimulation, we found that the successful isolation of left and right SI activity required the use of a range of time delays and that the best separation was observed when the largest range of τs from 1 up to 300 ms was used.
Persistent Identifierhttp://hdl.handle.net/10722/228072

 

DC FieldValueLanguage
dc.contributor.authorSutherland, Matthew T.-
dc.contributor.authorLiu, Jing Yu-
dc.contributor.authorTang, Akaysha C.-
dc.date.accessioned2016-08-01T06:45:07Z-
dc.date.available2016-08-01T06:45:07Z-
dc.date.issued2004-
dc.identifier.citationProceedings of 2004 International Conference on Machine Learning and Cybernetics, 2004, v. 7, p. 4222-4227-
dc.identifier.urihttp://hdl.handle.net/10722/228072-
dc.description.abstractBlind source separation (BSS) is an emerging statistical and data processing technique which aims to recover unobservable source signals from the observed mixtures. Second-order blind identification (SOBI) is one BSS algorithm that relies on stationary second-order statistics based on joint diagonalization of a set of covariance matrices. In simulations, the use of multiple covariance matrices computed with different time delays, τs, was beneficial for source separation, particularly when the underlying sources had highly overlapping spectra. Given the spectral overlap between actual brain sources, we experimented with different sets of temporal delays to empirically determine their effects on the isolation of electrical signals arising from a temporally and spatially well characterized brain location, the primary somatosensory cortex (SI). Using EEG data collected during median nerve stimulation, we found that the successful isolation of left and right SI activity required the use of a range of time delays and that the best separation was observed when the largest range of τs from 1 up to 300 ms was used.-
dc.languageeng-
dc.relation.ispartofProceedings of 2004 International Conference on Machine Learning and Cybernetics-
dc.subjectBlind source separation (BSS)-
dc.titleTemporal delays in blind identification of primary somatosensory cortex-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-6344254777-
dc.identifier.volume7-
dc.identifier.spage4222-
dc.identifier.epage4227-

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