Estimation of cortical dipole distributions for multiple signal sources based on ICA

Cortical dipole imaging is one of the spatial enhancement techniques from the scalp electroencephalogram. We investigated the cortical dipole imaging for multiple signal sources under time-varying non-uniform noise conditions. The effects of incorporating statistical information of noise into the spatiotemporal inverse filter were examined in three sphere volume conductor model. The parametric projection filter that incorporated with noise covariance was applied to the inverse problem of EEG measurements. The noise covariance matrix was estimated by applying independent component analysis to the scalp potentials. The spatial filter was expanded to apply to the time-varying non-uniform noise conditions such as eye blink artifact. Moreover, multiple dipole distributions were introduced to extract individual signal sources. The proposed imaging technique was applied to human experimental data of visual evoked potentials.