Experience-dependent contextual codes in the hippocampus

The hippocampus contains neural representations capable of supporting declarative memory. Hippocampal place cells are one such representation, firing in one or few locations in a given environment. Between environments, place cell firing fields remap (turning on/off or moving to a new location) to provide a population-wide code for distinct contexts. However, the manner by which contextual features combine to drive hippocampal remapping remains a matter of debate. Using large-scale in vivo two-photon intracellular calcium recordings in mice during virtual navigation, we show that remapping in the hippocampal region CA1 is driven by prior experience regarding the frequency of certain contexts and that remapping approximates an optimal estimate of the identity of the current context. A simple associative-learning mechanism reproduces these results. Together, our findings demonstrate that place cell remapping allows an animal to simultaneously identify its physical location and optimally estimate the identity of the environment. Combining virtual reality and large-scale calcium imaging, the authors demonstrate that hippocampal place cell remapping across contexts can be precisely predicted by the experience of the animal and approximates optimal probabilistic inference.

Automated summary

The hippocampus contains neural representations capable of supporting declarative memory, with place cells firing in specific locations in different environments. Through large-scale in vivo recordings, it was found that hippocampal remapping across contexts can be precisely predicted by the animal's experience and approximates optimal probabilistic inference. This suggests that place cell remapping allows animals to identify their physical location and estimate the identity of the environment optimally.