Multiple source estimation using singular value decomposition on a three dimensional measurement of magnetoencephalogram

Abstract

This paper describes a computer simulation study for estimating the multiple sources in the brain based on a three dimensional measurement of magnetoencephalogram (MEG). We proposed a new method of estimation algorithm using spatio-temporal data of MEG and singular value decomposition analysis. The number of estimation source is decided by number of dominant singular value of spatio-temporal MEG data. The source localization is done as pattern matching by signal subspace of singular vectors and projection of an estimating source. The results show estimation errors with the phase difference and the distance of two dipole sources. This proposed method can estimate two sources, which are more than 2cm apart and 15 degree phase difference. We conclude this method is useful as multiple source estimation.