MEG analysis with spatial filter and multiple linear regression

Shinpei Okawa, Satoshi Honda

研究成果: Paper査読

1 被引用数 (Scopus)

抄録

A spatial filterlor MEG analysis which does not utilize any temporal and prior information is proposed. The spatial filter is normalized to satisfy the criterion which is derived from the definition of the spatial filter. Due to the normalization, the spatial filter outputs the largest value at its target position. Furthermore, the current density distribution estimated with spatial filter is localized with Mallows Cp statistic which selects an optimum regression model. Some numerical experiments verify that this method estimates almost correct positions of dipoles. It is also confirmed that new method we propose gives more reliable estimation than the conventional method which decides dipole on the position of the largest current density estimated with spatial filter iteratively.

本文言語English
ページ1981-1985
ページ数5
出版ステータスPublished - 2004
外部発表はい
イベントSICE Annual Conference 2004 - Sapporo, Japan
継続期間: 2004 8月 42004 8月 6

Other

OtherSICE Annual Conference 2004
国/地域Japan
CitySapporo
Period04/8/404/8/6

ASJC Scopus subject areas

  • 制御およびシステム工学
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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