Removal of spurious coherence in MEG source-space coherence analysis.

Abstract

Source-space coherence analysis has become a popular method to estimate functional connectivity based on MEG/EEG. Source-space analysis involves solving the inverse problem, estimating the time courses of specific brain regions, and then examining the coherence between activities at different brain regions. However, source-space coherence analysis can be confounded by spurious coherence caused due to the leakage properties of the inverse algorithm employed. Such spurious coherence is typically manifested as an artifactual large peak around the seed voxel, called seed blur, in the resulting coherence images. This seed blur often obscures important details of brain interactions. This paper proposes the use of the imaginary part of the coherence to remove the spurious coherence caused by the leakage of an imaging algorithm. We present a theoretical analysis that explains how the use of imaginary part can remove this spurious coherence. We then present results from both computer simulations and experiments using resting-state MEG data which demonstrate the validity of our analysis.