Striatal Prediction Error Tracking Moderates the Influence of Social Exposure on Adolescent Substance Use Curiosity.

Abstract

Adolescence is a period of social development marked by increased sensitivity to social feedback and substance use experimentation. Although reinforcement learning (RL) models provide a powerful framework for examining how individuals learn from experience, they have rarely been applied to understand how adolescents learn from social experiences or how these processes relate to real-world behavioral outcomes. In a sample of 261 youth (11.0 ± 1.6 years old), we applied computational modeling to a novel social RL fMRI paradigm. Q-learning models estimated individual differences in learning and trial-by-trial prediction errors, which were used as a parametric modulator to assess brain activity that tracked the degree to which social feedback was better or worse than expected. Among older participants (n = 73; 12.9 ± 0.9 years old), we assessed associations between RL metrics and measures of substance use propensity. Greater substance use curiosity and household exposure to substance use were both linked to weaker striatal prediction error tracking of better-than-expected outcomes. However, among youth with substance-using peers, curiosity was associated with elevated striatal prediction error signals and better positive RL performance. Findings suggest that both hypo- and hyper-sensitivity to positive reinforcement learning signals may confer an increased propensity for substance use, possibly through distinct pathways.