A data-driven approach to identify the neural and cognitive basis of social functioning in health and first episode psychosis

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Project Summary/Abstract: The research and training plan for this Fellowship will provide the applicant with significant and foundational training in cognitive neuroscience, advanced computational approaches and neuroimaging analysis to support her long-term career goal of becoming an independent researcher dedicated to enhancing functional recovery in schizophrenia. A core feature of schizophrenia is severe disability in social functioning, which places a high burden on individuals and society. Effective treatment development for social functioning deficits is hindered by the lack of well-defined neural and cognitive treatment targets. Recent advances suggest cortical loss in prefrontal and cingulate cortices may be linked to poor functioning in chronic schizophrenia, however the relationship between specific neural targets and social functioning in first episode psychosis (FEP), when individuals may have greater ability to engage in substantial recovery, is largely unknown. Further, social cognition deficits are strongly linked to poor functioning, but the relationship between cortical loss in social cognitive brain regions and social functioning remains to be established. The purpose of this study is to employ data-driven approaches to identify neural and social cognitive markers of social functioning in health and FEP to inform treatment target identification. This cross-sectional, secondary analysis leverages two unique datasets – a large sample of healthy young adults from the Human Connectome Project (n=1113), and a sample of FEP participants enrolled in an ongoing clinical trial at the University of Minnesota (n=40). Specific Aim 1 - examine the relationships between gray matter volume and cortical thickness, social cognition and social functioning in healthy young adults using data driven approaches - will answer two research questions: 1a) what brain regions estimate better social functioning in healthy young adults, using regression-based machine learning analysis? and 1b) Is the relationship between social functioning and measures of gray matter volume and cortical thickness mediated by social cognition? We will then translate these findings to an FEP sample in Aim 2 - characterize the relationship between gray matter volume and cortical thickness and social functioning in FEP. This research will be supported by the applicant’s comprehensive training plan, her interdisciplinary mentoring team, and an ideal training environment due to its sophisticated neuroimaging and health informatics resources. This research is expected to advance our understanding of the complex relationships between the brain, social cognition and social functioning, which could lead to more targeted interventions for functional deficits in schizophrenia, alleviating suffering and addressing a critical public health need. The training will position the applicant to continue her trajectory to an independent career in translational cognitive neuroscience to enhance functional recovery through the development of neuroscience-informed interventions.