Figure 5.

DMN aberrations in schizophrenia are specific to subnodes. Functional connectivity (RSFC) and structural co‐occurrence (VBM) measurements were used to compute sparse inverse covariance estimation separately in healthy and schizophrenic individuals (left column). We conducted intra‐network analyses (i.e., DMN subnode atlas) and across‐network analyses (i.e., DMN subnode atlas augmented by nodes of the DAN and SN). Statistically significant group differences (brown squares in middle column) between the normal and diagnosed individuals are shown as derived from sparse inverse covariance estimation. The number of subnode‐specific dysregulations (right column) is shown as counts when viewed from the DMN proper (yellow), other DMN parts (orange), DAN (light green), and SN (purple). The findings make apparent that schizophrenia pathophysiology may be relatively more driven by across‐network effects and effects outside of the DMN proper. The glass brains were created using the nilearn Python package (Abraham et al., 2014)