Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells. (arXiv:2210.02684v1 [q-bio.NC])

The activity of the grid cell population in the medial entorhinal cortex
(MEC) of the brain forms a vector representation of the self-position of the
animal. Recurrent neural networks have been developed to explain the properties
of the grid cells by transforming the vector based on the input velocity, so
that the grid cells can perform path integration. In this paper, we investigate
the algebraic, geometric, and topological properties of grid cells using
recurrent network models. Algebraically, we study the …

arxiv bio cells grid network representation