Negative symptoms and resting-state functional connectivity across psychotic and mood disorders: A systematic literature review

Negative symptoms are strongly linked to disability and distress across psychotic and mood disorders. Current treatments are ineffective due to a limited understanding of their neurological bases. Dysconnectivity is thought to contribute to these symptoms, which makes studying resting state functional connectivity promising for developing effective interventions. This review identified 40 studies that investigated the relationships between node-based resting-state functional connectivity (specifically network and graph theory analyses) and negative symptoms across psychotic disorders (i.e., schizophrenia/schizoaffective disorder) and mood disorders with psychotic features (i.e., bipolar and major depressive disorders). There were indications that negative symptoms are related to the connectivity of several resting-state networks in schizophrenia and schizoaffective disorder, including the lateral frontoparietal, midcingulo-insular, medial frontoparietal, pericentral/somatomotor, occipital, and dorsal frontoparietal networks. There were suggestions that negative symptoms are associated with decreased functional segregation and clustering of neural connections. Nevertheless, it is important to interpret these findings with restraint, given the limitations and contradictions in the existing literature. Lastly, no studies were found that investigated negative symptoms and functional connectivity in individuals with major depressive disorder with psychotic features, and very minimal research has been done on individuals with bipolar disorder with psychotic features. Future studies should employ methods that account for negative symptoms’ heterogeneity (e.g., ecological momentary assessment), increase validity and reliability of resting state functional connectivity methods (e.g., naturalistic stimuli and individual-specific methods), and promote cohesion in the literature (e.g., consistent network taxonomy). Moreover, future research should explore the transdiagnostic nature of these relationships to inform effective clinical interventions.