Reinforcement Learning Performance and Risk for Psychosis in Youth

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Abstract

Early identification efforts for psychosis have thus far yielded many more individuals “at risk” than actually develop psychotic illness. Here, we test whether measures of reinforcement learning (RL), known to be impaired in chronic schizophrenia, are related to the severity of clinical risk symptoms. Because of the reliance of RL on dopamine-rich frontostriatal systems and evidence of dopamine system dysfunction in the psychosis prodrome, RL measures are of specific interest in this clinical population. The current study examines relationships between psychosis risk symptoms and RL task performance in a sample of adolescents and young adults (n = 70) receiving mental health services. We observed significant correlations between multiple measures of RL performance and measures of both positive and negative symptoms. These results suggest that RL measures may provide a psychosis risk signal in treatment-seeking youth. Further research is necessary to understand the potential predictive role of RL measures for conversion to psychosis.

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