Disrupted small-world networks in schizophrenia

TLDR

The human brain is a large, sparse, complex network with efficient small‑world properties that support parallel information transfer, yet schizophrenia is associated with dysfunctional connectivity whose impact on these topological properties is unclear. The study aimed to investigate the topological properties of resting‑state brain functional networks in schizophrenia. Functional connectivity between 90 cortical and sub‑cortical regions was estimated by partial correlation from resting‑state fMRI of 31 schizophrenia patients and 31 healthy controls, and thresholded to build undirected graphs. Schizophrenia patients showed disrupted small‑world properties in many brain regions, with alterations correlating with illness duration, supporting a hypothesis of dysfunctional integration and offering potential markers for disease severity.

Abstract

The human brain has been described as a large, sparse, complex network characterized by efficient small-world properties, which assure that the brain generates and integrates information with high efficiency. Many previous neuroimaging studies have provided consistent evidence of ‘dysfunctional connectivity’ among the brain regions in schizophrenia; however, little is known about whether or not this dysfunctional connectivity causes disruption of the topological properties of brain functional networks. To this end, we investigated the topological properties of human brain functional networks derived from resting-state functional magnetic resonance imaging (fMRI). Data was obtained from 31 schizophrenia patients and 31 healthy subjects; then functional connectivity between 90 cortical and sub-cortical regions was estimated by partial correlation analysis and thresholded to construct a set of undirected graphs. Our findings demonstrated that the brain functional networks had efficient small-world properties in the healthy subjects; whereas these properties were disrupted in the patients with schizophrenia. Brain functional networks have efficient small-world properties which support efficient parallel information transfer at a relatively low cost. More importantly, in patients with schizophrenia the small-world topological properties are significantly altered in many brain regions in the prefrontal, parietal and temporal lobes. These findings are consistent with a hypothesis of dysfunctional integration of the brain in this illness. Specifically, we found that these altered topological measurements correlate with illness duration in schizophrenia. Detection and estimation of these alterations could prove helpful for understanding the pathophysiological mechanism as well as for evaluation of the severity of schizophrenia.