The importance of agency in human reward processing

Abstract

Converging evidence suggests that reinforcement learning (RL) signals exist within the human brain and that they play a role in the modification of behaviour. According to RL theory, prediction errors are used to update values associated with actions and/or predictive cues, thus facilitate decision-making. For example, the reward positivity—a feedback-sensitive component of the event-related brain potential (ERP)—is thought to index an RL prediction error. An unresolved question, however, is whether or not action is required to elicit a reward positivity. Reinforcement learning theory would predict that the reward positivity should diminish or disappear in the absence of action, but evidence for this claim is conflicting. To investigate the impact of cue, choice, and action on the amplitude of the reward positivity, we altered a two-armed bandit task by systematically removing these factors. The reward positivity was greatly reduced or absent in the altered versions of the task. This result highlights the key role of agency in producing learning signals, such as the reward positivity.