Continuous Attractor Network Model for Conjunctive Position-by-Velocity Tuning of Grid Cells

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Abstract

The spatial responses of many of the cells recorded in layer II of rodent medial entorhinal cortex (MEC) show a triangular grid pattern, which appears to provide an accurate population code for animal spatial position. In layer III, V and VI of the rat MEC, grid cells are also selective to head-direction and are modulated by the speed of the animal. Several putative mechanisms of grid-like maps were proposed, including attractor network dynamics, interactions with theta oscillations or single-unit mechanisms such as firing rate adaptation. In this paper, we present a new attractor network model that accounts for the conjunctive position-by-velocity selectivity of grid cells. Our network model is able to perform robust path integration even when the recurrent connections are subject to random perturbations. © 2014 Si et al.

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Si, B., Romani, S., & Tsodyks, M. (2014). Continuous Attractor Network Model for Conjunctive Position-by-Velocity Tuning of Grid Cells. PLoS Computational Biology, 10(4). https://doi.org/10.1371/journal.pcbi.1003558

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