Abnormal topological organization of structural brain networks in schizophrenia

Abstract

Schizophrenia is a debilitating mental disorder characterized by disturbances of thought and emotion as well as neurocognitive deficits. It is hypothesized that the core symptoms of schizophrenia arise from the inability to integrate neural processes segregated across distributed brain regions. Graph theory allows us to verify this hypothesis at large-scale structural network level. In this study, a sample of 101 schizophrenic patients and 101 healthy controls was included. We sought to investigate the abnormality of network topological organization in patients with schizophrenia by using the cortical thickness measurement from magnetic resonance imaging. Brain networks were constructed by thresholding cortical thickness correlation matrices of 78 regions and analyzed using graph theoretical approaches. Compared to healthy controls, patients showed increased characteristic path length and clustering coefficient in the structural cortical networks. Moreover, schizophrenia patients were associated with reduced nodal centrality in several regions of the default network and increased nodal centrality mainly in primary cortex and paralimbic cortex regions. These findings suggest that the structural networks of schizophrenic patients have a less optimal topological organization, resulting in reduced capacity to integrate information across brain regions.