AI Article Synopsis

  • The hippocampus uses recurrent connectivity to help recall memories and spatial information, with place cells showing selective firing based on location.
  • This study models the CA3 region as a recurrent autoencoder, able to reconstruct sensory experiences from noisy inputs, leading to the emergence of place cells when agents navigate simulated environments.
  • Key findings highlight phenomena like remapping and orthogonality of spatial representations, along with predictions about how changing sensory contexts and network connectivity will affect how place fields are formed and maintained.

Article Abstract

The vertebrate hippocampus is believed to use recurrent connectivity in area CA3 to support episodic memory recall from partial cues. This brain area also contains place cells, whose location-selective firing fields implement maps supporting spatial memory. Here we show that place cells emerge in networks trained to remember temporally continuous sensory episodes. We model CA3 as a recurrent autoencoder that recalls and reconstructs sensory experiences from noisy and partially occluded observations by agents traversing simulated arenas. The agents move in realistic trajectories modeled from rodents and environments are modeled as continuously varying, high-dimensional, sensory experience maps (spatially smoothed Gaussian random fields). Training our autoencoder to accurately pattern-complete and reconstruct sensory experiences with a constraint on total activity causes spatially localized firing fields, i.e., place cells, to emerge in the encoding layer. The emergent place fields reproduce key aspects of hippocampal phenomenology: a) remapping (maintenance of and reversion to distinct learned maps in different environments), implemented via repositioning of experience manifolds in the network's hidden layer, b) orthogonality of spatial representations in different arenas, c) robust place field emergence in differently shaped rooms, with single units showing multiple place fields in large or complex spaces, and d) slow representational drift of place fields. We argue that these results arise because continuous traversal of space makes sensory experience temporally continuous. We make testable predictions: a) rapidly changing sensory context will disrupt place fields, b) place fields will form even if recurrent connections are blocked, but reversion to previously learned representations upon remapping will be abolished, c) the dimension of temporally smooth experience sets the dimensionality of place fields, including during virtual navigation of abstract spaces.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11343115PMC
http://dx.doi.org/10.1101/2024.08.11.607484DOI Listing

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