# Collective behavior of place and non-place neurons in the hippocampal network

arXiv: https://arxiv.org/abs/1612.08935 · HTML: https://mlsanity.com/paper/1612.08935/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Dec 2016.

## Built on by (most cited first, 2 of 2)

- [Inferring Higher-Order Couplings with Neural Networks](https://mlsanity.com/paper/2501.06108/) (2025)
- [Leader-Follower Neural Networks with Local Error Signals Inspired by Complex Collectives](https://mlsanity.com/paper/2310.07885/) (2023)

## Abstract (arXiv)

Discussions of the hippocampus often focus on place cells, but many neurons are not place cells in any given environment. Here we describe the collective activity in such mixed populations, treating place and non-place cells on the same footing. We start with optical imaging experiments on CA1 in mice as they run along a virtual linear track, and use maximum entropy methods to approximate the distribution of patterns of activity in the population, matching the correlations between pairs of cells but otherwise assuming as little structure as possible. We find that these simple models accurately predict the activity of each neuron from the state of all the other neurons in the network, regardless of how well that neuron codes for position. These and other results suggest that place cells are not a distinct sub-network, but part of a larger system that encodes, collectively, more than just place information.