Resting-state networks in schizophrenia.

Schizophrenia has been conceptualized as a disorder of altered brain connectivity (i.e. dysconnectivity). Until relatively recently, it was not feasible to test dysconnectivity hypotheses of schizophrenia in vivo. Resting-state functional magnetic resonance imaging (fMRI) is a powerful tool for mapping functional networks of the brain, such as the default mode network (DMN), and investigating the systems-level pathology of neurological and psychiatric disorders. In this article, we review the latest findings from resting-state fMRI studies on schizophrenia. Despite the wide array of methods used and heterogeneity of patient samples, several tentative conclusions may be drawn from the existing literature. 1) Connectivity of the DMN is altered in schizophrenia. Findings vary across studies; however, a majority of investigations reported hyper-connectivity of the DMN. 2) Resting-state connectivity of the prefrontal cortex (PFC) is reduced in schizophrenia, particularly intra-PFC connectivity. 3) Cortical-subcortical networks, including thalamocortical, frontolimbic, and cortico-cerebellar networks are altered in schizophrenia. 4) Preliminary findings indicate that functional connectivity within auditory/language networks and the basal ganglia is related to specific clinical symptoms, including auditory- verbal hallucinations and delusions. 5) Whole-brain network topology measures based on graph theory indicate that functional brain networks in schizophrenia are characterized by reduced small-worldness, lower degree connectivity of brain hubs, and decreased modularity. 6) Some of the alterations in functional connectivity observed in probands are present in unaffected relatives, raising the possibility that functional dysconnectivity is an endophenotype related to genetic risk for schizophrenia. Combined, these findings provide broad support for dysconnectivity theories of schizophrenia. We conclude our review with a discussion of the limitations of the existing literature and potentially important areas of future research.