An efficient coding theory for a dynamic trajectory predicts non-uniform allocation of entorhinal grid cells to modules

PLoS Comput Biol. 2017 Jun 19;13(6):e1005597. doi: 10.1371/journal.pcbi.1005597. eCollection 2017 Jun.


Grid cells in the entorhinal cortex encode the position of an animal in its environment with spatially periodic tuning curves with different periodicities. Recent experiments established that these cells are functionally organized in discrete modules with uniform grid spacing. Here we develop a theory for efficient coding of position, which takes into account the temporal statistics of the animal's motion. The theory predicts a sharp decrease of module population sizes with grid spacing, in agreement with the trend seen in the experimental data. We identify a simple scheme for readout of the grid cell code by neural circuitry, that can match in accuracy the optimal Bayesian decoder. This readout scheme requires persistence over different timescales, depending on the grid cell module. Thus, we propose that the brain may employ an efficient representation of position which takes advantage of the spatiotemporal statistics of the encoded variable, in similarity to the principles that govern early sensory processing.

MeSH terms

  • Animals
  • Computer Simulation
  • Entorhinal Cortex / physiology*
  • Grid Cells / physiology*
  • Models, Neurological*
  • Orientation / physiology*
  • Rats
  • Space Perception / physiology*
  • Spatial Navigation / physiology*
  • Spatio-Temporal Analysis

Grant support

This research was supported by the Israel Science Foundation grant No. 1733/13 and (in part) by grant No. 1978/13 We acknowledge support from the Gatsby Charitable Foundation The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.