Iterative MUSIC for Highly Correlated MEG Source Localization: A Simulation Study

This study presented an iterative MUSIC (Multiple Signal Classification) for highly correlated MEG source localization. By suppressing the equivalent source, the approximate source location information was obtained. And then, by iteratively suppressing source found in the last iteration, eventually, both of the sources were identified. The method is designed for two source case. Compared with other similar method, the presented one does not have to know a prior information about source locations. Based on a theoretical model, it mines such information factually already included in original data itself.