A neural-level model of spatial memory and imagery

Elife. 2018 Sep 4;7:e33752. doi: 10.7554/eLife.33752.

Abstract

We present a model of how neural representations of egocentric spatial experiences in parietal cortex interface with viewpoint-independent representations in medial temporal areas, via retrosplenial cortex, to enable many key aspects of spatial cognition. This account shows how previously reported neural responses (place, head-direction and grid cells, allocentric boundary- and object-vector cells, gain-field neurons) can map onto higher cognitive function in a modular way, and predicts new cell types (egocentric and head-direction-modulated boundary- and object-vector cells). The model predicts how these neural populations should interact across multiple brain regions to support spatial memory, scene construction, novelty-detection, 'trace cells', and mental navigation. Simulated behavior and firing rate maps are compared to experimental data, for example showing how object-vector cells allow items to be remembered within a contextual representation based on environmental boundaries, and how grid cells could update the viewpoint in imagery during planning and short-cutting by driving sequential place cell activity.

Keywords: computational model; episodic memory; neuroscience; none; scene construction; spatial cognition; spatially selective cells; trace cells.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Humans
  • Imagery, Psychotherapy*
  • Models, Neurological*
  • Neurons / physiology
  • Spatial Memory*
  • Temporal Lobe / physiology
  • Video Recording