Hierarchical network disruptions in Schizophrenia: A multi-level fMRI study of functional connectivity

We tested the hypothesis that Schizophrenia (SCZ) involves a systematic breakdown in brain network organization across different levels of graph-theoretical hierarchy.

Using resting-state fMRI from 43 SCZ patients and 63 matched healthy controls, we implemented an analytical multi-level framework. This integrated: global graph theory metrics to assess overall network topology; macronetwork metrics to measure functional specialization of large-scale systems; network-based statistics (NBS) to identify specific, altered pathways at the local level; a multigraph model to visualize hub reorganization between networks.

We revealed a coherent pattern of multi-level dysfunction. Globally, SCZ networks showed increased local clustering and connection density, indicating a shift toward a less efficient, overly segregated architecture. At the macroscale, sensory and salience networks displayed elevated local connectivity, while higher-order cognitive networks (e.g., DMN, DAN) showed reduced specialization and increased cross-talk. Locally, NBS identified a core subnetwork of weakened connectivity within temporal-orbitofrontal-cingulate circuits. The multigraph model synthesized these findings, showing a widespread reduction in the integrative role of key cognitive hubs.

Our findings establish a model of SCZ as a disorder of disintegrated brain network hierarchy, where disruptions at the level of local circuits and functional specializations collectively lead to global topological inefficiency.