A hexagonal Fourier model of grid cells. Issue 1 (19th November 2018)

• Record Type: Journal Article
• Authors: Rodríguez‐Domínguez, Ulises; Caplan, Jeremy B.
• Is Part Of: Hippocampus. Volume 29:Issue 1(2019)
• Page Start: 37
• Page End: 45
• Publication Date: 2018-11-19
• Subjects: context -- entorhinal cortex -- Fourier transform -- grid cells -- information compression; Hippocampus (Brain) -- Periodicals; 612.825
• DOI: 10.1002/hipo.23028
• Languages: English
• ISSNs: 1050-9631

Abstract

Abstract: Grid cells in rat medial entorhinal cortex are widely thought to play a major role in spatial behavior. However, the exact computational role of the population of grid cells is not known. Here we provide a descriptive model, which nonetheless considers biologically feasible mechanisms, whereby the grid cells are viewed as a two‐dimensional Fourier basis set, in hexagonal coordinates, with restricted availability of basis functions. With known properties imposed in the model parameters, we demonstrate how various empirical benchmark findings are straight‐forward to understand in this model. We also explain how complex computations, inherent in a Fourier model, are feasible in the medial entorhinal cortex with simple mechanisms. We further suggest, based on model experiments, that grid cells may support a form of lossy compression of contextual information, enabling its representation in an efficient manner. In sum, this hexagonal Fourier model suggests how the entire population of grid cells may be modeled in a principled way, incorporates biologically feasible mechanisms and provides a potentially powerful interpretation of the relationship between grid‐cell activity and contextual information beyond spatial knowledge. This enables various phenomena to be modeled with relatively simple mechanisms, and leads to novel and testable predictions.