Solution for MEG inverse problem using Signal Space Separation and Magnetic Field Tomography

Tadashi Kitahara, Satoshi Honda

研究成果: Conference contribution

抄録

Magnetic Field Tomography (MFT) is a source localization method for Magnetoencephalography (MEG), a non-invasive method to observe the brain activity. MFT just requires the source to be a linear combination of lead fields that describe the distribution of the sensitivity of each sensor, while other commonly used MEG source localization methods such as equivalent current dipole (ECD) fitting or the beamformer require some more inappropriate assumptions. However, less requirements on the source results in a huge amount of computational load in MFT. In this paper, the reduction of the computational load for MFT was achieved by considering the coefficients of multipolar expansion as the measurements of virtual sensors. These coefficients are obtained by performing Signal Space Separation (SSS) in which the exclusion of external magnetic field generated by the external sensor arrays is enabled. Based on our simulation, the calculation time was reduced from 6 hours to about 10 seconds preserving the source localization ability.

本文言語English
ホスト出版物のタイトル2011 International Symposium on Computational Models for Life Sciences, CMLS-11
ページ178-185
ページ数8
DOI
出版ステータスPublished - 2011 7 13
イベント2011 International Symposium on Computational Models for Life Sciences, CMLS-11 - Toyama City, Japan
継続期間: 2011 10 112011 10 13

出版物シリーズ

名前AIP Conference Proceedings
1371
ISSN(印刷版)0094-243X
ISSN(電子版)1551-7616

Other

Other2011 International Symposium on Computational Models for Life Sciences, CMLS-11
国/地域Japan
CityToyama City
Period11/10/1111/10/13

ASJC Scopus subject areas

  • 物理学および天文学(全般)

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