Geometry of abstract learned knowledge in the hippocampus

Nature. 2021 Jul;595(7865):80-84. doi: 10.1038/s41586-021-03652-7. Epub 2021 Jun 16.

Abstract

Hippocampal neurons encode physical variables1-7 such as space1 or auditory frequency6 in cognitive maps8. In addition, functional magnetic resonance imaging studies in humans have shown that the hippocampus can also encode more abstract, learned variables9-11. However, their integration into existing neural representations of physical variables12,13 is unknown. Here, using two-photon calcium imaging, we show that individual neurons in the dorsal hippocampus jointly encode accumulated evidence with spatial position in mice performing a decision-making task in virtual reality14-16. Nonlinear dimensionality reduction13 showed that population activity was well-described by approximately four to six latent variables, which suggests that neural activity is constrained to a low-dimensional manifold. Within this low-dimensional space, both physical and abstract variables were jointly mapped in an orderly manner, creating a geometric representation that we show is similar across mice. The existence of conjoined cognitive maps suggests that the hippocampus performs a general computation-the creation of task-specific low-dimensional manifolds that contain a geometric representation of learned knowledge.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • CA1 Region, Hippocampal / cytology
  • CA1 Region, Hippocampal / physiology
  • Calcium / metabolism
  • Decision Making
  • Female
  • Hippocampus / cytology
  • Hippocampus / physiology*
  • Knowledge*
  • Learning / physiology*
  • Male
  • Mice
  • Models, Neurological
  • Neurons / metabolism

Substances

  • Calcium