Signed and unsigned reward prediction errors dynamically enhance learning and memory
Abstract
Memory helps guide behavior, but which experiences from the past are prioritized? Classic models of learning posit that events associated with unpredictable outcomes as well as, paradoxically, predictable outcomes, deploy more attention and learning for those events. Here, we test reinforcement learning and subsequent memory for those events, and treat signed and unsigned reward prediction errors (RPEs), experienced at the reward-predictive cue or reward outcome, as drivers of these two seemingly contradictory signals. By fitting reinforcement learning models to behavior, we find that both RPEs contribute to learning by modulating a dynamically changing learning rate. We further characterize the effects of these RPE signals on memory and show that both signed and unsigned RPEs enhance memory, in line with midbrain dopamine and locus-coeruleus modulation of hippocampal plasticity, thereby reconciling separate findings in the literature.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 04, 2021
- Source ID
- 10.7554/elife.61077
Entities
People
- Nina Rouhani
- Yael Niv
Organizations
- Army Research Office
- California Institute of Technology
- National Institute of Mental Health
- National Institutes of Health
- National Science Foundation
- Princeton University