NDLI: Semi-blind identification of movement-related magnetoencephalogram components using a classification approach

Content Provider	IEEE Xplore Digital Library
Author	Hesse, Christian W. Heskes, Tom Jensen, Ole
Copyright Year	2008
Description	Author affiliation: F.C. Donders Centre for Cognitive Neuroimaging, Radboud University Nijmegen, Kapittelweg 29, 6525 EN The Netherlands (Hesse, Christian W.; Jensen, Ole) \|\| Institute for Computing and Information Sciences, Radboud University Nijmegen, Toernooiveld 1, 6525 ED, The Netherlands (Heskes, Tom)
Abstract	Many biomedical signal processing applications involving the analysis of multi-channel electrophysiological recordings, such as the magnetoencephalogram (MEG) and electroencephalogram (EEG), increasingly employ blind source separation (BSS) techniques to estimate signal components reflecting artifacts and neurophysiological activity. While much research focuses on developing methods for automatic removal of artefact sources, comparatively little effort has been spent on trying to identify neurophysiological sources of interest, which is especially challenging in the absence of prior knowledge about their spatial or time-freqency characteristics. This work presents a method for identifying source signals exhibiting systematic and reliable time-frequency differences over clearly defined epochs associated with different “system-states”. The proposed method uses annotated data and a classification approach to identify those sources which individually reflect significant differences between epochs (classes). Applied to segments of 275-channel MEG data from a visuo-motor task in which left, right or no finger movements occurred, the method selects only a small number of sources whose scalp topographies are consistent with primary sensorimotor cortical areas.
Starting Page	2618
Ending Page	2621
File Size	506597
Page Count	4
File Format	PDF
ISBN	9781424418145
ISSN	1557170X
DOI	10.1109/IEMBS.2008.4649737
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-08-20
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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