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Abstract:
We have previously introduced a new analysis method for fMRI data called “eigenvector centrality mapping (ECM)” (Lohmann et al, 2010). In ECM, each voxel receives a rank describing its centrality within the brain using a method similar to Google's PageRank algorithm. In this context, we have previously used spectral coherence as a similarity metric. However, this ignores phase shifts so that time series may receive high coherence values even though they are separated by large phase shifts. Here, we investigate whether changes in brain states manifest themselves not only in centrality changes of spectral coherence but also of phase alignment.
