Source localization algorithm based on topographic matching pursuit
Spatio-temporal decomposition methods in combination with source localization algorithms can contribute to an improved description and allocation of neural activity from electrical and magnetic multichannel measurements. We introduce a new algorithm, which combines Topographic Matching Pursuit as spatio-temporal decomposition method with a dipole-source localization. The new algorithm is applied to EEG-data obtained from a photic driving experiment with eleven volunteers. In comparison to a hitherto published Multichannel Matching Pursuit (MMP) source localization the new algorithm shows, for a Mirrored-Dipole configuration, higher Goodness-of-Fit values, if temporal asynchrony exists in the EEG-channels. We conclude that the suggested algorithm is more appropriate for source reconstruction in case of temporal asynchrony than MMP-based procedures used so far.