Continuous attractor network model for conjunctive position-by-velocity tuning of grid cells.

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PLoS Computational Biology. 2014 Apr 17;10(4):e1003558. doi: 10.1371/journal.pcbi.1003558

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Continuous attractor network model for conjunctive position-by-velocity tuning of grid cells. Romani Lab

Si B, Romani S, Tsodyks M

Note: Research in this publication was not performed at Janelia.

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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.

PMID: 24743341 [PubMed - indexed for MEDLINE]

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Continuous attractor network model for conjunctive position-by-velocity tuning of grid cells.

Note: Research in this publication was not performed at Janelia.

Abstract

PMID: 24743341 [PubMed - indexed for MEDLINE]

Janelia Authors