A, Epicenters were defined as potential sources of pathological volume loss from which GMV reductions spread (blue) to affect structurally connected areas. To identify such regions, we simulated a spreading process using a network diffusion model (NDM). Schizophrenia data sets included participants in the BrainGluSchi (BGS) and COBRE studies. B, Using each of the 332 parcellated regions as a seed, we retained the maximum correlation between the simulated and observed GMV abnormalities (maximum r). For each contrast, we then compared maximum r values for each region to a distribution of maximum r values from 2 benchmark null models accounting for spatial autocorrelations in the deformation maps (Null-smash) and basic topological properties of the connectome (see Statistical Analysis subsection of the Methods section [NDM]). Regional epicenters with significantly greater maximum r than a spatially constrained null model (orange indicates P < .05; red, familywise error [FWE] P < .05) are shown for cross-sectional (C-F) and longitudinal (G-J) effects. Results using Null-rewire benchmark models and scatterplots of observed and estimated volume abnormalities are provided in eFigure 3 in Supplement 1.