We then identified graph theory properties that varied with polygenic variation. First, resting-state connectivity matrices were entered into the GTG toolbox, which computes properties for each participant using the Brain Connectivity Toolbox (Rubinov and Sporns, 2010). Two graph properties were examined: Participation Coefficient or the extent to which a node is connected to nodes in different modules, and Within-Module Degree Z-Score or the extent to which a node is connected to other nodes within its own module. Graph properties were examined only for nodes that emerged in the NBS analysis. Properties were entered as dependent variables in robust regressions in the GTG toolbox. Predictor models were the same as NBS analyses. Significance was determined via permutation tests (5000 repetitions). False discovery rate was used to correct (across nodes) for multiple comparisons, and adjusted p-values are in brackets.
