Parra, Lucas C. and Alvino, Chris and Tang, Akaysha and Pearlmutter, Barak A. and Yeung, Nick and Osman, Allen and Sajda, Paul (2003) Single-trial detection in EEG and MEG: Keeping it linear. Neurocomputing, 52. pp. 177-183. ISSN 0925-2312

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Abstract

Conventional electroencephalography (EEG) and magnetoencephalography (MEG) analysis often rely on averaging over multiple trials to extract statistically relevant di7erences between two or more experimental conditions. We demonstrate that by linearly integrating information over multiple spatially distributed sensors within a prede9ned 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).

Item Type:	Article
Keywords:	Linear integration; High-density electroencephalography; EEG; Magnetoencephalography; MEG; Single-trial analysis; Brain–computer interface; BCI;
Academic Unit:	Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	5538
Identification Number:	https://doi.org/10.1016/S0925-2312(02)00821-4
Depositing User:	Barak Pearlmutter
Date Deposited:	04 Nov 2014 11:09
Journal or Publication Title:	Neurocomputing
Publisher:	Elsevier
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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