Hippocampal and striatal involvement in cognitive tasks: a computational model

Abstract: The hippocampus and the striatum support episodic and procedural memory, respectively, and "place" and "response" learning within spatial navigation. Recently this dichotomy has been linked to "model-based" and "model-free" reinforcement learning. Here we present a well-constrained neural model of how both systems support spatial navigation, and apply the same model to more abstract problems such as sequential decision making. In particular, we show that if a task can be transformed into a Markov Decision Process, the machinery provided by the hippocampus and striatum can be utilized to solve it. These results show how the hippocampal complex can represent non-spatial problems, including context, probabilities and action-dependent information, in support of "model-based" reinforcement learning to complement learning within the striatum.