Coding advantage of grid cell orientation under noisy conditions
Dong CheniD, Kai-Jia Sun, Liang WangiD, Zhanjun ZhangiD, Ying‐Cheng LaiiD, Nikolai AxmacheriD, Wen-Xu WangiD
Abstract
Grid cells constitute a crucial component of the \"GPS\" in the mammalian brain. Recent experiments revealed that grid cell activity is anchored to environmental boundaries. More specifically, these results revealed a slight yet consistent offset of 8 degrees relative to boundaries of a square environment. The causes and possible functional roles of this orientation are still unclear. Here we propose that this phenomenon maximizes the spatial information conveyed by grid cells. Computer simulations of the grid cell network reveal that the universal grid orientation at 8 degrees optimizes spatial coding specifically in the presence of noise. Our model also predicts the minimum number of grid cells in each module. In addition, analytical results and a dynamical reinforcement learning model reveal the mechanism underlying the noise-induced orientation preference at 8 degrees. Together, these results suggest that the experimentally observed common orientation of grid cells serves to maximize spatial information in the presence of noise.\n\nAuthor summarySpatial navigation depends on several specialized cell types including place and grid cells. Grid cells have multiple firing fields that are arranged in a regular hexagonal pattern. The axes of this pattern are anchored to environmental boundaries at a universal angle of 8{degrees}. Here, we combine computer simulations of the grid cell network with analytical derivations and a reinforcement learning model to explain the functional relevance of this universal grid cell orientation. We show that spatial information provided by grid cells is maximized at the experimentally observed grid orientation within a broad parameter range. This relationship occurs only in the presence of noise. The model allows for several experimentally testable predictions including the number of grid cells.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 1
- Organism
- Assay
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Grid cells encode local head direction
Klára Z. Gerlei, Jessica Passlack, … Matthew F. Nolan·bioRxiv·Feb 27, 2020
- Spatial periodicity in grid cell firing is explained by a neural sequence code of 2-D trajectories
Rebecca R.G., Giorgio A. Ascoli, … Holger Dannenberg·eLifePeer-reviewed·May 21, 2025
- A Memory Model of Rodent Spatial Navigation: Place Cells are Memories Arranged in a Grid and Grid Cells are Non-spatial
David E. Huber·bioRxiv·Dec 30, 2023
- A computational model that explores the effect of environmental geometries on grid cell representations
Samyukta Jayakumar, Rukhmani Narayanamurthy, … V. Srinivasa Chakravarthy·bioRxiv·Jun 19, 2017
- Environmental anchoring of grid-like representations minimizes spatial uncertainty during navigation
Tobias Navarro Schröder, Benjamin W. Towse, … Christian F. Doeller·bioRxiv·Jan 4, 2020
- A simple model of the co-emergence of grid and place fields
Zhaoze Wang, Genela Morris, … Vijay Balasubramanian·bioRxiv·May 22, 2026