Removal of spurious coherence in MEG source-space coherence analysis

摘要

Lately, source-space coherence analysis has been applied to estimate functional connectivity using MEG/EEG data. Source space analysis involves solving the inverse problem, estimating the time courses of specific brain regions, and then examining the coherence across the estimated time courses. However, source-space coherence analysis is confounded by the leakage properties of the inverse algorithm, as manifested by a large seed peak (seed blur) in the resulting coherence images. This seed peak 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 which explains how the use of imaginary part can remove this spurious coherence. We then present results of computer simulations and experiments using resting-state MEG data which demonstrate the validity of our analysis.