The Precision of Hippocampal Representations Predicts Incremental Value Learning across the Adult Lifespan

Abstract

Correctly assigning value to different options and leveraging this information to guide choice is a cornerstone of adaptive decision-making. Reinforcement learning (RL) has provided a computational framework to study this process, and neural signals linked to RL have been identified in the striatum and medial prefrontal cortex. More recently, hippocampal contributions to this kind of value learning have been proposed, at least under some conditions. Here, we test whether the hippocampus provides a signal of the option's identity that aids in credit assignment when learning about several perceptually similar items and evaluate how this process differs across the lifespan. A sample of 251 younger and older adults (158 F; 93 M), including a subset ( n  = 76) with simultaneous fMRI, completed an RL task in which they learned the value of four houses through trial-and-error. Older adults showed decreased accuracy, accompanied by reduced neural signaling of value at choice but not feedback. Using representational similarity analysis, we found that the precision with which choice options were represented in the posterior hippocampus during choice predicted accuracy across age groups. Despite previous evidence for neural dedifferentiation with age, we found no support for a “blurring” of these stimulus representations in older adults. Rather, we observed reduced connectivity between the posterior hippocampus and the medial PFC in older adults, and this connectivity correlated with accuracy. Taken together, these findings identify a hippocampal contribution to incremental value learning, with age-related declines driven by reduced hippocampus–mPFC connectivity rather than a systematic change in the precision of hippocampal representations.