Theta functions and optimal lattices for a grid cells model
Laurent B\'etermin (University of Vienna)

TL;DR
This paper investigates the optimality of lattice structures like triangular and FCC lattices for grid cell representations in navigation, using Fisher Information and theta functions to analyze their efficiency in 2D and 3D models.
Contribution
It introduces a mathematical framework linking lattice theta functions to Fisher Information for grid cells, providing new evidence for the optimality of certain lattice structures in neural coding.
Findings
Triangular lattice is optimal under certain Gaussian parameters.
FCC lattice is shown to be optimal in three-dimensional models.
Numerical analysis supports the optimality of these lattices in specific conditions.
Abstract
Certain types of neurons, called "grid cells", have been shown to fire on a triangular grid when an animal is navigating on a two-dimensional environment, whereas recent studies suggest that the face-centred-cubic (FCC) lattice is the good candidate for the same phenomenon in three dimensions. The goal of this paper is to give new evidences of these phenomena by considering a infinite set of independent neurons (a module) with Poisson statistics and periodic spread out Gaussian tuning curves. This question of the existence of an optimal grid is transformed into a maximization problem among all possible unit density lattices for a Fisher Information which measures the accuracy of grid-cells representations in . This Fisher Information has translated lattice theta functions as building blocks. We first derive asymptotic and numerical results showing the (non-)maximality of…
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