Regional connectivity effects were corrected for multiple comparisons using a false-positive adjustment, 1/N = .013, where N = the number of comparisons, which implies that, on average, there was ≤ 1 false positive per analysis (19,44). Edgewise connectivity effects were characterized using the network-based statistic (45). To compute the network-based statistic, an analysis of variance was fitted to each of the (N2−N)/2 = 3003 edges (correlation values) in the {78 × 78} functional connectivity matrix, yielding a p value matrix representing the probability of rejecting the null hypothesis for each effect at each edge. A component-forming threshold, K, was applied to each p value matrix, and the size of each connected component in these thresholded matrices was computed. A connected component represents a subnetwork of edges that can be linked to each other via suprathreshold connections. The size of the observed components was compared with a null distribution of maximal component sizes obtained through permutation testing to obtain component-wise p values corrected for multiple comparisons (46). The method identifies connected subnetworks of edges showing a particular effect of a size
