Fig. 3: Overlap between the group, treatment and interaction findings and the large-scale canonical resting-state networks (RSNs).

We calculated the percentage of overlap between our result maps—which included binary masks of all cortical regions showing differences in nodal metrics (for group, treatment and interaction effects, separately)—and the large-scale RSNs described in the atlas from Yeo et al. [64]. As subcortical structures are not covered by the Yeo atlas, these were omitted from our result maps to prevent artificial reduction of the overlap estimate. The Yeo atlas includes a coarse parcellation of 7 canonical RSNs: the default-mode (DMN), dorsal attention (DAN), frontoparietal (FPN), limbic (LIM), somatomotor (SOM), visual (VIS) and ventral attention (VAN) networks. We created a proxy DKA>Yeo atlas for each of the 7 Yeo RSNs by combining individual DKA regions, allocating each to a single RSN based on the RSN for which each region had the highest number of overlapping vertices based on the confusion matrix from a previous study [100]. Overlap was quantified using the Dice-kappa coefficient, which measures the percentage of voxels of each RSN overlapping with our group/treatment/interaction effect maps. In the upper section, we provide an overview of all regions where we found group, treatment or interaction effects, irrespective of the specific graph metric, rendered in a 3D glass brain (semi-transparent) surface model. In the lower section, we provide a heatmap summarising the percentage of overlap (Dice-kappa coefficient) between our results and each of the 7 networks, with each network rendered in a 3D glass brain (semi-transparent) surface model. Note that despite the visualisation, regions belonging to the different RSNs do not overlap, for example, the FPN contains the rostral and caudal middle frontal gyri, whereas the DMN contains the superior and inferior frontal gyri, which are difficult to differentiate in rendered models.