Common spatial subspace decomposition applied to analysis of brain responses under multiple task conditions: a simulation study

a method, called common spatial subspace decomposition, is presented which can extract signal components specific to one condition from multiple magne toencephalography/electroencephalography data sets of multiple task conditi ons. Signal matrices or covariance matrices are decomposed using spatial fa ctors common to multiple conditions. The spatial factors and corresponding spatial filters are then dissociated into specific and common parts, accord ing to the common spatial subspace which exists among the data sets. Finall y, the signal components are extracted using the corresponding spatial filt ers and spatial factors. The relationship between this decomposition and sp atio-temporal source models is described in this paper. Computer simulation s suggest that this method can facilitate the analysis of brain responses u nder multiple task conditions and merits further application. (C) 1999 Else vier Science Ireland Ltd. All rights reserved.