A single-cell spiking model for the origin of grid-cell patterns.

Tiziano D'Albis,Richard Kempter,Volker Steuber

doi:10.1371/journal.pcbi.1005782

Abstract

Spatial cognition in mammals is thought to rely on the activity of grid cells in the entorhinal cortex, yet the fundamental principles underlying the origin of grid-cell firing are still debated. Grid-like patterns could emerge via Hebbian learning and neuronal adaptation, but current computational models remained too abstract to allow direct confrontation with experimental data. Here, we propose a single-cell spiking model that generates grid firing fields via spike-rate adaptation and spike-timing dependent plasticity. Through rigorous mathematical analysis applicable in the linear limit, we quantitatively predict the requirements for grid-pattern formation, and we establish a direct link to classical pattern-forming systems of the Turing type. Our study lays the groundwork for biophysically-realistic models of grid-cell activity.

Highlights

Grid cells are neurons of the medial entorhinal cortex tuned to the position of the animal in the environment [1, 2]
The idea that self-motion inputs could drive spatial firing is motivated by the fact that mammals can use path integration for navigation [22], that speed and head-direction signals have been recorded within the medial entorhinal cortex (mEC) [23, 24], and that, in the rat [1, 25] but not in the mouse [26, 27], grid firing fields tend to persist in darkness
We assume that inputs are integrated linearly at the output, and that the output neuron is equipped with an intrinsic spike-rate adaptation mechanism, that is, Z1

Summary

Introduction

Grid cells are neurons of the medial entorhinal cortex (mEC) tuned to the position of the animal in the environment [1, 2]. Unlike place cells, which typically fire in a single spatial location [3, 4], grid cells have multiple receptive fields that form a strikingly-regular triangular pattern in space. The idea that self-motion inputs could drive spatial firing is motivated by the fact that mammals can use path integration for navigation [22], that speed and head-direction signals have been recorded within the mEC [23, 24], and that, in the rat [1, 25] but not in the mouse [26, 27], grid firing fields tend to persist in darkness. The attractor theory alone cannot explain how grid fields are anchored to the physical space, and how the properties of the grid patterns relate to the geometry of the enclosure [29,30,31]

Methods

Results

Discussion

Conclusion