Computing MEG Signal Sources

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	Similar Articles Articles by J. Mikael Eklund Articles by Ruzena Bajcsy Articles by Jonathan Sprinkle Articles by Gregory V. Simpson

2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05)

Stanford, California

August 08-August 11

ISBN: 0-7695-2442-7

	ASCII Text	x
	J. Mikael Eklund, Ruzena Bajcsy, Jonathan Sprinkle, Gregory V. Simpson, "Computing MEG Signal Sources," 2005 IEEE Computational Systems Bioinformatics Conference - Workshops, pp. 332-338, 2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05), 2005.

	BibTex	x
	@article{ 10.1109/CSBW.2005.42, author = {J. Mikael Eklund and Ruzena Bajcsy and Jonathan Sprinkle and Gregory V. Simpson}, title = {Computing MEG Signal Sources}, journal ={2005 IEEE Computational Systems Bioinformatics Conference - Workshops}, volume = {0}, year = {2005}, isbn = {0-7695-2442-7}, pages = {332-338}, doi = {http://doi.ieeecomputersociety.org/10.1109/CSBW.2005.42}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - 2005 IEEE Computational Systems Bioinformatics Conference - Workshops TI - Computing MEG Signal Sources SN - 0-7695-2442-7 SP332 EP338 A1 - J. Mikael Eklund, A1 - Ruzena Bajcsy, A1 - Jonathan Sprinkle, A1 - Gregory V. Simpson, PY - 2005 KW - null VL - 0 JA - 2005 IEEE Computational Systems Bioinformatics Conference - Workshops ER -

J. Mikael Eklund, University of California, Berkeley

Ruzena Bajcsy, University of California, Berkeley

Jonathan Sprinkle, University of California, Berkeley

Gregory V. Simpson, University of California, San Francisco

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSBW.2005.42

This paper deals with the complexity of the inverse computation of brain currents from Magnetoencephalography (MEG) signals. MEG measures the magnetic field outside the head: in effect, the resultant field from the flow of current inside the brain. We describe our current techniques to perform this inverse computation (called source estimation in much of the literature), which provides a view of brain activity that is less sensitive to disturbances which affect other kinds of brain activity measurements, though much more expensive to record.

Citation:

J. Mikael Eklund, Ruzena Bajcsy, Jonathan Sprinkle, Gregory V. Simpson, "Computing MEG Signal Sources," csbw, pp.332-338, 2005 IEEE Computational Systems Bioinformatics Conference - Workshops (CSBW'05), 2005

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