Presentation 2003/3/10
Estimation of current distribution in brain from MEG data based on variational Bayes
Taku YOSHIOKA, Masa-aki SATO, Shigeki KAJIWARA, Keisuke TOYAMA,
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Abstract(in English) We haveproposed a variational Bayes method for estimating current source distribution from MEG data. In the method, we introduce a hierarchical prior which assumes that the current sources are localized in the several brain area and the current distribution is continuous. The fMRI data can be also incorporated into the hierarchical prior. In this report, we have done commit er simulation by using the cortex model obtained by MRI measurement. The simulation results shows the effectiveness of our method.
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Keyword(in English) MEG / Current source estimation / Variational Bayes method / Hierarchical prior
Paper # NC2002-149
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Committee NC
Conference Date 2003/3/10(1days)
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Registration To Neurocomputing (NC)
Language JPN
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Title (in English) Estimation of current distribution in brain from MEG data based on variational Bayes
Sub Title (in English)
Keyword(1) MEG
Keyword(2) Current source estimation
Keyword(3) Variational Bayes method
Keyword(4) Hierarchical prior
1st Author's Name Taku YOSHIOKA
1st Author's Affiliation Graduate School of Information Science, Nara Institute of Science and Technology:Human Information Science Laboratries, ATR International()
2nd Author's Name Masa-aki SATO
2nd Author's Affiliation Human Information Science Laboratries, ATR International:CREST, Japan Science and Technology Corporation
3rd Author's Name Shigeki KAJIWARA
3rd Author's Affiliation Technology Research Laboratory, Shimadzu Corporation
4th Author's Name Keisuke TOYAMA
4th Author's Affiliation Technology Research Laboratory, Shimadzu Corporation
Date 2003/3/10
Paper # NC2002-149
Volume (vol) vol.102
Number (no) 729
Page pp.pp.-
#Pages 6
Date of Issue