Moving towards neuro-behavioral models of the determinants of high expressed emotion during social interaction among people with schizophrenia and their families

• Applicants: Professor Dr. Philipp Kanske; Dr. Philipp Riedel
• Subject Area: Clinical Psychiatry, Psychotherapy, Child and Adolescent Psychiatry
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 547263283

Family environments critically shape the course of illness in people with schizophrenia (SZ). High expressed emotion (EE) is a measure of a specific emotional climate in a family and is a reliable predictor of relapse in SZ. SZ-relatives who exhibit high EE are for their part more distressed, more prone to depression, and more likely to face hostility. Preliminary findings show increased susceptibility to developing high EE with altered cognitive flexibility, social cognition (empathy, theory of mind) and negative self-conscious emotions (shame, guilt) – alterations that are also found in SZ. Therefore, high EE seems to reflect an interaction problem between SZ and their family, with detrimental consequences for both parties. Despite the importance of high EE, there is little research on the pathways by which it comes about. Hence, there is a lack of opportunities to advance treatment, reduce relapse rates in SZ and ultimately improve the quality of life of the families affected. This project will bring together the latest research on social cognition and emotion, state-of-the-art analysis tools, and second-person neuroscience to, for the first time, move towards a model of the determinants of high EE. We will comprehensively examine the interplay among altered cognitive flexibility, empathy, theory of mind, shame, and guilt in a sample of SZ (N=100) and one relative each (N=100). Work package 1 (WP1) tests for group differences in relatives high vs. low in EE and SZ using a wide array of established testing and novel functional MRI tasks. Neuroimaging supplements important information at the level of computational processes in the brain. WP2 tests a proposed network model of the determinants of high EE using data from WP1 in conjunction with machine learning, graph analysis, and cross-task multivoxel pattern classification. WP3 will jointly assess SZ and one of their relatives interacting in a naturalistic setting and test the degree of social understanding one has of the other family member – in relation to a high vs. low EE family environment. Recruitment will involve four psychiatric hospitals and outpatient clinics in the Dresden area. Assessment will be performed at the Neuroimaging Center and at the University Outpatient Clinic and Research Center for Psychotherapy at the Technische Universität Dresden (TUD). Data management will be carried out at the Center for Information Services and High-Performance Computing at TUD. Both applicants are firm in clinical research and treatment and will be supported by three international advisors. The project is expected to bring about short-, mid- and long-term advancements in treatment: less self-reproach and improved self-efficacy via better psychoeducation, more effective engagement of the social environment in adapted family therapies, and resolution of dysfunctional family dynamics to reduce relapse in SZ. Moreover, the project will advance our understanding of social interaction in general.

• DFG Programme: Research Grants