Emergent elasticity in the neural code for space

Abstract

We develop a theoretical model, grounded in known properties of neural dynamics and synaptic plasticity, that can fuse information gathered from the past history of velocity and sequence of encountered landmarks during exploratory behavior, to construct a self-consistent internal representation of space. Moreover, through model reduction techniques, we obtain conceptual insights into how consistent internal spatial representations naturally emerge through an elastic relaxation process in an effective spring–particle system. We verify several experimentally testable predictions of our model involving the spatial behavior of grid cells in the medial entorhinal cortex, as well as suggest additional experiments.

Document Details

Document Type
Pub Defense Publication
Publication Date
Nov 27, 2018
Source ID
10.1073/pnas.1805959115

Entities

People

  • Kiah Hardcastle
  • Lisa M. Giocomo
  • Samuel A Ocko
  • Surya Ganguli

Organizations

  • Esther A. & Joseph Klingenstein Fund
  • James S. McDonnell Foundation
  • McKnight Foundation
  • National Institute of Mental Health
  • New York Stem Cell Foundation
  • Office of Naval Research
  • Simons Foundation
  • Stanford University
  • Whitehall Foundation

Tags

Readers

  • Computer Vision.
  • Neuroscience
  • Theoretical Analysis.

Technology Areas

  • Space