Part of Advances in Neural Information Processing Systems 32 (NeurIPS 2019)
Talfan Evans, Neil Burgess
Constructing and maintaining useful representations of sensory experience is essential for reasoning about ones environment. High-level associative (topological) maps can be useful for efficient planning and are easily constructed from experience. Conversely, embedding new experiences within a metric structure allows them to be integrated with existing ones and novel associations to be implicitly inferred. Neurobiologically, the synaptic associations between hippocampal place cells and entorhinal grid cells are thought to represent associative and metric structures, respectively. Learning the place-grid cell associations can therefore be interpreted as learning a mapping between these two spaces. Here, we show how this map could be constructed by probabilistic message-passing through the hippocampal-entorhinal system, where messages are scheduled to reduce the propagation of redundant information. We propose that this offline inference corresponds to coordinated hippocampal-entorhinal replay during sharp wave ripples. Our results also suggest that the metric map will contain local distortions that reflect the inferred structure of the environment according to associative experience, explaining observed grid deformations.