Cortical Dipole Imaging for Multiple Signal Sources Considering Time-Varying Non-Uniform Noise

Abstract

Cortical dipole imaging is one of the spatial enhancement techniques from the scalp electroencephalogram. We investigated the 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 by computer simulations and experimental studies 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 and to visualize individual signal sources. The proposed imaging technique was applied to human experimental data of visual evoked potentials. We obtained reasonable results that coincide to physiological knowledge.