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

PLoS Comput Biol. 2017 Oct 2;13(10):e1005782. doi: 10.1371/journal.pcbi.1005782. eCollection 2017 Oct.

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.

MeSH terms

  • Action Potentials / physiology*
  • Animals
  • Computational Biology
  • Entorhinal Cortex / cytology
  • Grid Cells* / cytology
  • Grid Cells* / physiology
  • Models, Neurological*
  • Single-Cell Analysis

Grant support

This work was supported by the Deutsche Forschungsgemeinschaft (DFG) (grant numbers GRK 1589/2, KE 788/3-1) and the Bundesministerium für Bildung und Forschung (BMBF) (grant numbers 01GQ1001A, 01GQ0972) for RK. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.