Presentation 2005/3/22
Simultaneous source current estimation of eyes and cortical activities for the removal of eye movement artifacts from MEG data
Yusuke FUJIWARA, Masaaki SATO, Okito YAMASHITA, Taku YOSHIOKA, Dai KAWAWAKI, Tomohiro SHIBATA, Kenji DOYA, Keisuke TOYAMA, Mitsuo KAWATO,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) When measuring MEG, the magnetic field generated by eye-movement is a major artifact that contaminates the MEG signals from the brain. In order to investigate brain activities related to eye movmement by MEG, it is essential to remove eye-movement artifact. As a method to remove eye-movement artifact, this report compares four methods : least square estimation, moving-dipole method, Wiener estimation and hierarchical Bayesian estimation. We found in a simulation experiment that the simultaneous estimation of both eye and brain sources by hierarchical Bayesian estimation is the best way to correct eye artifact. Moreover, we show that the hierarchical Bayesian estimation is effective for real MEG data duaring smooth-pursuit eye movement.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) MEG / eye movement / ocular artifact / source current estimation / inverse problem
Paper # NC2004-174
Date of Issue

Conference Information
Committee NC
Conference Date 2005/3/22(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair
Vice Chair
Secretary
Assistant

Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Simultaneous source current estimation of eyes and cortical activities for the removal of eye movement artifacts from MEG data
Sub Title (in English)
Keyword(1) MEG
Keyword(2) eye movement
Keyword(3) ocular artifact
Keyword(4) source current estimation
Keyword(5) inverse problem
1st Author's Name Yusuke FUJIWARA
1st Author's Affiliation Nara Institute of Science and Technology:Computational Neuroscience Labs:CREST, Japan Science and Technology Corporation()
2nd Author's Name Masaaki SATO
2nd Author's Affiliation Computational Neuroscience Labs:CREST, Japan Science and Technology Corporation
3rd Author's Name Okito YAMASHITA
3rd Author's Affiliation Computational Neuroscience Labs
4th Author's Name Taku YOSHIOKA
4th Author's Affiliation Computational Neuroscience Labs
5th Author's Name Dai KAWAWAKI
5th Author's Affiliation Nara Institute of Science and Technology:Computational Neuroscience Labs:CREST, Japan Science and Technology Corporation
6th Author's Name Tomohiro SHIBATA
6th Author's Affiliation Nara Institute of Science and Technology:Computational Neuroscience Labs:CREST, Japan Science and Technology Corporation
7th Author's Name Kenji DOYA
7th Author's Affiliation Nara Institute of Science and Technology:Computational Neuroscience Labs:CREST, Japan Science and Technology Corporation:Okinawa Institute of Science and Technology
8th Author's Name Keisuke TOYAMA
8th Author's Affiliation Technology Research Lab. Shimadzu Co.
9th Author's Name Mitsuo KAWATO
9th Author's Affiliation Nara Institute of Science and Technology:Computational Neuroscience Labs
Date 2005/3/22
Paper # NC2004-174
Volume (vol) vol.104
Number (no) 759
Page pp.pp.-
#Pages 6
Date of Issue