Localization of MEG and EEG Brain Signals by Alternating Projection

A popular approach for modeling brain activity in MEG is a set of current dipoles, where each dipole represents the combined activation of a local area of the brain. Here, we address the problem of multiple dipole localization in MEG with a novel solution called Alternating Projection (AP). The solution is sequential and iterative, and is based on minimizing the least-squares (LS) criterion by the AP algorithm. Results from simulated, phantom, and human MEG data demonstrated robust performance, with consistently superior localization accuracy than popular scanning methods belonging to the beamformer and multiple-signal classification (MUSIC) families. Importantly, the proposed solution is more robust to forward model errors resulting from head rotations and translations, as well as different cortex tessellation grids for the forward and inverse solutions, with a significant advantage in low SNR and highly correlated sources.