Linear Spatial Weighting for Single Trial Detection in Encephalography

Medientyp: E-Book
Titel: Linear Spatial Weighting for Single Trial Detection in Encephalography
Beteiligte: Parra, Lucas [Verfasser:in]; Alvino, Chris [Sonstige Person, Familie und Körperschaft]; Tang, Akaysha [Sonstige Person, Familie und Körperschaft]; Pearlmutter, Barak [Sonstige Person, Familie und Körperschaft]; Yeung, Nick [Sonstige Person, Familie und Körperschaft]
Erschienen: [S.l.]: SSRN, [2018]
Erschienen in: Computer Science Preprint Archive ; Vol. 2002, Issue 2, pp 151-157
Umfang: 1 Online-Ressource (7 p)
Sprache: Englisch
Entstehung:
Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 2002 erstellt
Beschreibung: Conventional 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)
Zugangsstatus: Freier Zugang

Nur in Feld suchen: