Interregional Functional Connectivity via Pattern Synchrony

In this study, we propose a novel approach for functional connectivity analyses, in which cross-sample entropy (c-SampEn) measures the probability of finding similar patterns in the fMRI time sequence of distinct brain regions, instead of the time synchronization of the signals. In application to two simulated data, c-SampEn algorithm show that provide a clear group distinctions. Furthermore, we also present a realistic fMRI dataset analysis in steady state, this result is contrasted with the conventional linear correlation method and exhibits a decided difference between them. We argue that c-SampEn has not only more extensive applicability than conventional linear methods, but also can provide a new, valuable complementary insight to the understanding of interregional variations across the brain