A Joint Distribution Approach on Non-linear Functional Connectivity

This report summarizes experiments on exploring non-linear functional connectivity. Using resting-state functional MRI data from the HCP1200 dataset, we define nodes as 17 functional networks and edges as the joint distribution between times series pairs. Linear dependence is removed before taking the joint distribution. We then employ a test for normality on the joint distribution to find non-normal distribution patterns. However, the result from an experimental run of 10 subjects shows that: only less than 1% of edges is non-normal distributed, and the location of such edges is not consistent across subjects. From this point of view, the non-linear part seems to be governed by random noise.