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Many decisions are based on an internal model of the world. Yet, how such a model is constructed from experience and represented in memory remains unknown. We test the hypothesis that reward shapes memory for sequences of events by retroactively prioritizing memory for objects as a function of their distance from reward. Human participants encountered neutral objects while exploring a series of mazes for reward. Across six data sets, we find that reward systematically modulates memory for neutral objects, retroactively prioritizing memory for objects closest to the reward. This effect of reward on memory emerges only after a 24-hour delay and is stronger for mazes followed by a longer rest interval, suggesting a role for post-reward replay and overnight consolidation, as predicted by neurobiological data in animals. These findings demonstrate that reward retroactively prioritizes memory along a sequential gradient, consistent with the role of memory in supporting adaptive decision-making.

Expectations have a powerful influence on how we experience the world. Neurobiological and computational models of learning suggest that dopamine is crucial for shaping expectations of reward and that expectations alone may influence dopamine levels. However, because expectations and reinforcers are typically manipulated together, the role of expectations per se has remained unclear. We separated these two factors using a placebo dopaminergic manipulation in individuals with Parkinson's disease. We combined a reward learning task with functional magnetic resonance imaging to test how expectations of dopamine release modulate learning-related activity in the brain. We found that the mere expectation of dopamine release enhanced reward learning and modulated learning-related signals in the striatum and the ventromedial prefrontal cortex. These effects were selective to learning from reward: neither medication nor placebo had an effect on learning to avoid monetary loss. These findings suggest a neurobiological mechanism by which expectations shape learning and affect.

Learning is essential for adaptive decision making. The striatum and its dopaminergic inputs are known to support incremental reward-based learning, while the hippocampus is known to support encoding of single events (episodic memory). Although traditionally studied separately, in even simple experiences, these two types of learning are likely to co-occur and may interact. Here we sought to understand the nature of this interaction by examining how incremental reward learning is related to concurrent episodic memory encoding. During the experiment, human participants made choices between two options (colored squares), each associated with a drifting probability of reward, with the goal of earning as much money as possible. Incidental, trial-unique object pictures, unrelated to the choice, were overlaid on each option. The next day, participants were given a surprise memory test for these pictures. We found that better episodic memory was related to a decreased influence of recent reward experience on choice, both within and across participants. fMRI analyses further revealed that during learning the canonical striatal reward prediction error signal was significantly weaker when episodic memory was stronger. This decrease in reward prediction error signals in the striatum was associated with enhanced functional connectivity between the hippocampus and striatum at the time of choice. Our results suggest a mechanism by which memory encoding may compete for striatal processing and provide insight into how interactions between different forms of learning guide reward-based decision making., (Copyright © 2014 the authors 0270-6474/14/3414901-12$15.00/0.)