This analysis identifies distinct topological alterations in cortical layers of schizophrenia, implying links to clinical features.
Motivation: Traditional structural covariance networks (SCNs) are group-level constructs and consider cortex as homogeneous, limiting identification of individual abnormalities and microstructural insights in mental illness. Goal(s): To investigate abnormal individualized SCNs in schizophrenia (SCZ) across cortical depths, providing microstructural evidence for clinical features. Approach: Submillimeter isotropic DTI data was collected. A cortical-based laminar analysis was applied to divide the cortex into four equal-distance layers, followed by Jensen-Shannon divergence-based similarity (JSDs) method to construct SCNs. Results: SCZ showed alterations in global and nodal network properties across cortical depths, primarily in regions involved in cognition, motor, and sensory, with correlations to cognitive deficits and clinical symptoms. Impact: This study revealed that topological alterations in schizophrenia exhibit laminar-specific characteristics and their associations with clinical features, which might enhance our understanding of the pathophysiology of schizophrenia from a mesoscopic perspective.
No takes yet. Share an insight, caveat, or question.
Liu et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: