Reduced positive affect alters reward learning via reduced information encoding in the Reward Positivity

Abstract

Reward Positivity (RewP) is a feedback-locked event-related potential component that is specifically elicited by rewarding feedback and scales with positive reward prediction error, a hallmark of reinforcement learning models. The RewP is also diminished in depression, suggesting that it may be a novel marker of anhedonia. Here, we examined if a sad mood induction offered an opportunity to causally induce a mood-related alteration of the RewP and reward-related learning. In Experiment 1 (N = 50 total), participants were randomly assigned to previously established sad or neutral mood induction procedures before a probabilistic selection task. This manipulation failed to induce changes in affect, suggesting that standard methods are inadequate. In Experiment 2 (N = 50 total), participants were randomly assigned to newly developed happy versus sad mood manipulations, which successfully induced large changes in affect. While the RewP was unaffected by mood induction, positive mood moderated the relationship between prediction error encoding in the RewP and reward learning, such that low positive mood and low prediction error encoding resulted in poorer reward learning. These findings provide a mechanistic example of how reduced positive affect moderates reward learning via poorer information encoding in the RewP.