Current density estimation with time-invariant spatial filter in MEG analysis

Shinpei Okawa, Satoshi Honda

Research output: Contribution to conferencePaperpeer-review


A spatial filter which does not utilize prior and temporal information is proposed for MEG (magnetoencephalography) analysis. Stochastic characteristics of the current density distribution estimated with a spatial filter is considered to improve the estimation. Second and fourth order cumulants are utilized to design a spatial filter. A numerical experiment shows the fourth order cumulants are effective for localization.

Original languageEnglish
Number of pages5
Publication statusPublished - 2005 Dec 1
EventSICE Annual Conference 2005 - Okayama, Japan
Duration: 2005 Aug 82005 Aug 10


OtherSICE Annual Conference 2005


  • Higher-order statistics
  • Inverse problem
  • Magnetoencephalography
  • Spatial filter

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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