The value of confidence: Confidence prediction errors drive value-based learning in the absence of external feedback.

ABSTRACT: Reinforcement learning algorithms have a long-standing success story in explaining the dynamics of instrumental conditioning in humans and other species. While normative reinforcement learning models are critically dependent on external feedback, recent findings in the field of perceptual learning point to a crucial role of internally-generated reinforcement signals based on subjective confidence, when external feedback is not available. Here, we investigated the existence of such confidence-based learning signals in a key domain of reinforcement-based learning: instrumental conditioning. We conducted a value-based decision making experiment which included phases with and without external feedback and in which participants reported their confidence in addition to choices. Behaviorally, we

SUBMITTER: Ptasczynski LE 

PROVIDER: S-EPMC9560614 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature