Keywords: Psychiatric Disorders, Structural Connectivity, schizophrenia
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.
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