Shared and differential vulnerabilities of stress and reward processing in psychosis-risk syndromes or early-stage depression - Abstract The clinical high-risk (CHR) or “prodromal” framework has provided a platform for tracking the onset of psychosis and identifying the neurodevelopmental mechanisms of risk for this disorder. It is now well established, however, that affective symptoms in CHR samples are essentially universal, persist longitudinally, and contribute to disability regardless of psychosis transition. Given the substantial neurobiological proximity of psychotic and affective disorders, the extent to which current biomarkers in CHR reflect risk for psychosis, common affective illness, or both remains largely unknown. Broadening the scope of detection to the early affective stages has potential to strengthen pathogenic models of psychosis by highlighting shared and unique vulnerability mechanisms while informing treatments that are relevant to a wider range of individuals. This study will identify shared and differential impairments of stress and reward processing among youth with psychosis-risk syndromes or early-stage depression (ESD). In a task-based fMRI design, youth with CHR, ESD, or no psychopathology will complete a probabilistic reinforcement learning paradigm before and after an acute stress manipulation. Using an established computational model we will generate estimates of theoretically relevant learning parameters, compare them across groups, and relate them to neural and hormonal data. We hypothesize that the striatum represents a shared locus of reward-based dysfunction across the early and high-risk stages of psychosis and depression, but risk-specific differences may lie within the prefrontal cortex. The results of this study will represent a significant step forward in our transdiagnostic understanding of emerging psychopathology, with implications for both generalizable and personalized intervention. By the end of the project period I will have established expertise in task-based fMRI research, independence in computational modeling of behavior, and expert knowledge of the interplay between stress, reward, and neurodevelopment across mood and psychotic disorders. Together this will provide a unique combination of clinical and methodological expertise and prepare me for my long-term goal of improving preventative intervention through longitudinal research.
