Social Prediction Error Project

Description: Adolescence is a period of social development marked by increased sensitivity to social feedback and substance use experimentation. Reinforcement learning (RL) models provide a framework to examine how adolescents learn from social experiences and how these processes relate to behavior. In a sample of 261 youth (11.0±1.6 years old), we applied computational modeling to a novel fMRI social RL paradigm. Q-learning models captured individual differences in learning and trial-by-trial prediction errors, which were used to index neural social prediction error signals. Among older participants (n=73; 12.9±0.9 years old), we assessed associations between social RL metrics and substance use curiosity. Greater curiosity and household substance use exposure were linked to reduced striatal prediction error signaling. However, among youth with substance-using peers, curiosity was associated with elevated prediction error signaling and heightened social RL performance. Findings suggest that both hypo- and hyper-sensitivity to social reinforcement may confer an increased propensity for substance use, possibly through distinct pathways.