noise and free of major artifacts (Allen et al., 2011). These 39 components were considered the RSNs of interest. Spatial maps of the 39 components were z-transformed in order to identify the main brain areas included in each RSN. Time courses were then filtered using a band-pass filter 0.01 to 0.15 Hz. Finally, resting state functional network connectivity (rsFNC) matrices were calculated for each subject based on the correlation coefficients between the time courses of all possible pairs formed with the 39 chosen components. Spike time courses were censored from the calculation of correlation coefficients.
