Social cognitive networks and social cognitive performance across individuals with schizophrenia spectrum disorders and healthy controls

Abstract Background Schizophrenia spectrum disorders (SSDs) feature social cognitive deficits, though their neural basis remains unclear. Social cognitive performance may relate to neural circuit activation patterns more than diagnosis, which would have important prognostic and therapeutic implications. The present study aimed to determine how functional connectivity within and between social cognitive networks relates to social cognitive performance across individuals with SSDs and healthy controls. Methods Participants with SSDs (N=164) and healthy controls (N=117) completed the Empathic Accuracy (EA) task during functional magnetic resonance imaging, and lower-level (e.g., emotion recognition) and higher-level (e.g., theory of mind) social cognitive measures outside the scanner. Functional connectivity during the EA task was analyzed using background connectivity and graph theory. Data-driven social cognitive networks were identified across participants. Regression analyses were used to examine network connectivity-performance relationships across individuals. Positive and negative within- and between-network connectivity strength were also compared in poor versus good social cognitive performers, and SSD versus control groups. Results Three social cognitive networks were identified: motor resonance, affect sharing, and mentalizing. Regression and group-based analyses demonstrated reduced between-network negative connectivity, or segregation, and greater within- and between-network positive connectivity in worse social cognitive performers. There were no significant effects of diagnostic group on within- or between-network connectivity. Conclusions These findings suggest that the neural circuitry of social cognitive performance may exist dimensionally. Across participants, better social cognitive performance was associated with greater segregation between social cognitive networks, whereas poor versus good performers may compensate via hyperconnectivity within and between social cognitive networks.