Abstract

Place cells and grid cells in the hippocampal formation are thought to integrate sensory and self-motion information into a representation of estimated spatial location, but the precise mechanism is unknown. We simulated a parallel attractor system in which place cells form an attractor network driven by environmental inputs and grid cells form an attractor network performing path integration driven by self-motion, with inter-connections between them allowing both types of input to influence firing in both ensembles. We show that such a system is needed to explain the spatial patterns and temporal dynamics of place cell firing when rats run on a linear track in which the familiar correspondence between environmental and self-motion inputs is changed. In contrast, the alternative architecture of a single recurrent network of place cells (performing path integration and receiving environmental inputs) cannot reproduce the place cell firing dynamics. These results support the hypothesis that grid and place cells provide two different but complementary attractor representations (based on self-motion and environmental sensory inputs, respectively). Our results also indicate the specific neural mechanism and main predictors of hippocampal map realignment and make predictions for future studies.

Highlights

  • The place cells in the rat hippocampus show strong behavioral correlates by firing only when the animal visits a particular localised region of the surrounding environment (O’Keefe and Dostrovsky, 1971; O’Keefe, 1976)

  • In this study we investigate whether the integration of environmental and self-motion information into a representation of an estimated position could result from a reciprocal interaction between recurrent networks of place cells and grid cells (O’Keefe and Burgess, 2005; Laptev, 2008)

  • During moderate self-motion and sensory information mismatches, after a pronounced initial delay, the place cell activity bump was continuously shifted through intervening positions until its location was in agreement with the sensory inputs provided by the Boundary Vector Cells (BVCs) tuned to the approaching end of the track

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Summary

Introduction

The place cells in the rat hippocampus show strong behavioral correlates by firing only when the animal visits a particular localised region of the surrounding environment (O’Keefe and Dostrovsky, 1971; O’Keefe, 1976) These place cells provide a population code for spatial position. As the animal moves around a particular environment, the firing pattern of place cells is continuously updated, reflecting the current position of the animal This continuous shifting of neural representation could be driven by at least two types of information— perceptual from the environment and internally generated concerning the rat’s own movements, and takes place even in total darkness (O’Keefe, 2007). Another type of spatially selective cells was found in the subiculum by Lever et al (2009), and is referred to as Boundary Vector Cells (BVCs), due to the fact that a particular BVC fires maximally

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