Resting data were preprocessed using the Graph Theory GLM (GTG) toolbox version 0.44 (www.nitrc.org/projects/metalab_gtg; RRID: SCR_014075) (Spielberg et al., 2015). Data were motion corrected, detrended (linear and quadratic), bandpass filtered (retaining 0.01–0.10Hz), and the mean global, ventricular, and white matter signals were partialled out, along with estimated motion parameters. Timeseries for FreeSurfer nodes were extracted by calculating mean signal across the node for each time point, for each EPI run. Timeseries for the EPI runs were concatenated after mean-centering each timeseries within run, and a 68×68 Pearson correlation matrix was created for each participant. Before graph properties were computed, each participant’s connectivity matrix was thresholded to include only positive weights and normalized via division by the median positive weight for each matrix (excluding zeros). Normalization was performed to remove bias due to individual differences in overall network weight. Graph theory networks, including modules, were derived from a data-driven approach based on the current sample. Details about module membership are provided in Supplemental Methods.
