NDLI: Hierarchical Bayesian modeling of inter-trial variability and variational Bayesian learning of common spatial patterns from multichannel EEG

Content Provider	IEEE Xplore Digital Library
Author	Wei Wu Zhe Chen Shangkai Gao Brown, E.N.
Copyright Year	2010
Description	Author affiliation: Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China (Shangkai Gao) \|\| Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, 02139, USA (Wei Wu; Zhe Chen; Brown, E.N.)
Abstract	In numerous neuroscience studies, multichannel EEG data are often recorded over multiple trial periods under the same experimental condition. To date, little effort is aimed to learn spatial patterns from EEG data to account for trial-to-trial variability. In this paper, a hierarchical Bayesian framework is introduced to model inter-trial source variability while extracting common spatial patterns under multiple experimental conditions in a supervised manner. We also present a variational Bayesian algorithm for model inference, by which the number of sources can be determined effectively via automatic relevance determination (ARD). The efficacy of the proposed learning algorithm is validated with both synthetic and real EEG data. Using two brain-computer interface (BCI) motor imagery data sets we show the proposed algorithm consistently outperforms the common spatial patterns (CSP) algorithm while attaining comparable performance with a recently proposed discriminative approach.
Starting Page	501
Ending Page	504
File Size	215249
Page Count	4
File Format	PDF
ISBN	9781424442959
ISSN	15206149
DOI	10.1109/ICASSP.2010.5495663
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-03-14
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Brain modeling Electroencephalography Signal processing algorithms Assembly Inference algorithms Independent component analysis Neuroscience Blind source separation Data mining
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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