Explicitly Nonlinear Dynamic Functional Network Connectivity In Resting State FMRI Data
Sara Motlaghian, Vince Calhoun
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28 Mar 2022
Most studies on functional connectivity of fMRI data focus on linear correlation within the data and neglect the possible impact of nonlinear dynamic relationships. In this work, we propose a method to assess explicitly nonlinear dynamic functional network connectivity (dFNC) among fMRI time courses (TCs) by using normalized mutual information (NMI) within a sliding window approach.
