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Article: Single-trial detection in EEG and MEG: Keeping it linear

TitleSingle-trial detection in EEG and MEG: Keeping it linear
Authors
KeywordsBrain-computer interface (BCI)
Issue Date2003
Citation
Neurocomputing, 2003, v. 52-54, p. 177-183 How to Cite?
AbstractConventional electroencephalography (EEG) and magnetoencephalography (MEG) analysis often rely on averaging over multiple trials to extract statistically relevant differences between two or more experimental conditions. We demonstrate that by linearly integrating information over multiple spatially distributed sensors within a predefined time window, one can discriminate conditions on a trial-by-trial basis with high accuracy. We restrict ourselves to a linear integration as it allows the computation of a spatial distribution of the discriminating source activity. In the present set of experiments the resulting source activity distributions correspond to functional neuroanatomy consistent with the task (e.g. contralateral sensory-motor cortex and anterior cingulate). © 2003 Elsevier Science B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/228021
ISSN
2015 Impact Factor: 2.392
2015 SCImago Journal Rankings: 1.202

 

DC FieldValueLanguage
dc.contributor.authorParra, Lucas-
dc.contributor.authorAlvino, Chris-
dc.contributor.authorTang, Akaysha-
dc.contributor.authorPearlmutter, Barak-
dc.contributor.authorYeung, Nick-
dc.contributor.authorOsman, Allen-
dc.contributor.authorSajda, Paul-
dc.date.accessioned2016-08-01T06:44:59Z-
dc.date.available2016-08-01T06:44:59Z-
dc.date.issued2003-
dc.identifier.citationNeurocomputing, 2003, v. 52-54, p. 177-183-
dc.identifier.issn0925-2312-
dc.identifier.urihttp://hdl.handle.net/10722/228021-
dc.description.abstractConventional electroencephalography (EEG) and magnetoencephalography (MEG) analysis often rely on averaging over multiple trials to extract statistically relevant differences between two or more experimental conditions. We demonstrate that by linearly integrating information over multiple spatially distributed sensors within a predefined time window, one can discriminate conditions on a trial-by-trial basis with high accuracy. We restrict ourselves to a linear integration as it allows the computation of a spatial distribution of the discriminating source activity. In the present set of experiments the resulting source activity distributions correspond to functional neuroanatomy consistent with the task (e.g. contralateral sensory-motor cortex and anterior cingulate). © 2003 Elsevier Science B.V. All rights reserved.-
dc.languageeng-
dc.relation.ispartofNeurocomputing-
dc.subjectBrain-computer interface (BCI)-
dc.titleSingle-trial detection in EEG and MEG: Keeping it linear-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0037781982-
dc.identifier.volume52-54-
dc.identifier.spage177-
dc.identifier.epage183-

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