NDLI: Sparse electromagnetic source imaging using EEG and MEG

Content Provider	IEEE Xplore Digital Library
Author	Lei Ding Han Yuan
Copyright Year	2012
Description	Author affiliation: Laureate Inst. for Brain Res., Tulsa, OK, USA (Han Yuan) \|\| Center for Biomed. Eng., Univ. of Oklahoma, Norman, OK, USA (Lei Ding)
Abstract	The present study proposed the combined use of EEG and MEG data in a new sparse electromagnetic source imaging (ESI) technique, i.e., variation-based sparse cortical current density (VB-SCCD) method. Monte Carlo simulations were conducted to investigate the performance of the proposed approach in multiple extended brain activations (up to ten) that were randomly generated. Experimental EEG and MEG data from a face recognition task were further used to evaluate the performance of VB-SCCD. The present results indicate that the proposed approach can accurately reconstruct multiple brain activations and their spatial extents. The source imaging results from real data further demonstrate it is capable to recover networked brain activations involving multiple cortical regions, which are consistent with results from functional magnetic resonance imaging in same task paradigm. The present results further indicate the capability of the proposed approach in reconstructing deep brain sources and temporal dynamics of brain sources at millisecond resolutions. It thus suggests that sparse ESI using combined EEG and MEG is a promising technique probing detailed spatiotemporal brain activations.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	6224
Ending Page	6227
File Size	722113
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6347416
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Image reconstruction Brain modeling Face recognition Magnetic resonance imaging
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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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
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