Predictive coding of reward in the hippocampus

Anticipating future outcomes is a fundamental task of the brain^1-3. This process requires learning the states of the world as well as the transitional relationships between those states. In rodents, the hippocampal spatial cognitive map is thought to be one such internal model⁴. However, evidence for predictive coding^5,6 and reward sensitivity^7-10 in the hippocampal neuronal representation suggests that its role extends beyond purely spatial representation. How this reward representation evolves over extended experience remains unclear. Here we track the evolution of the hippocampal reward representation over weeks as mice learn to solve a cognitively demanding reward-based task. We find several lines of evidence, both at the population and the single-cell level, indicating that the hippocampal representation becomes predictive of reward as the mouse learns the task over several weeks. Both the population-level encoding of reward and the proportion of reward-tuned neurons decrease with experience. At the same time, the representation of features that precede the reward increases with experience. By tracking reward-tuned neurons over time, we find that their activity gradually shifts from encoding the reward itself to representing preceding task features, indicating that experience drives a backward-shifted reorganization of neural activity to anticipate reward. We show that a temporal difference model of place fields¹¹ recapitulates these results. Our findings underscore the dynamic nature of hippocampal representations, and highlight their role in learning through the prediction of future outcomes.