Novel beamformers for Multiple Correlated brain source localization and reconstruction

This paper introduces two novel beamforming algorithms, namely the Region Constrained and Multiple Correlated Source Model beamformers, designed to localize and to reconstruct highly correlated brain sources from noisy EEG data. Multiple correlated source simulations have been per formed to evaluate the performance of the proposed algorithms, using a realistic 176 x 240 x 256 finite difference head model. Our simulation results show that the Region Constrained-Multiple Correlated Source Model beamformer, obtained by combining the above two beamformers, allows us to localize three perfectly correlated brain sources with very high localization accuracy. Finally, the eigenspace version of this beamformer can be used to reconstruct three correlated brain source signals correctly from simulated noisy EEG data.