Emergence of Grid-like Representations by Training Recurrent Networks with Conformal Normalization

arXiv:2310.19192v2 Announce Type: replace-cross
Abstract: Grid cells in the entorhinal cortex of mammalian brains exhibit striking hexagon grid firing patterns in their response maps as the animal (e.g., a rat) navigates in a 2D open environment. In this paper, we study the emergence of the hexagon grid patterns of grid cells based on a general recurrent neural network (RNN) model that captures the navigation process. The responses of grid cells collectively form a high dimensional vector, representing the 2D self-position …

abstract arxiv brains cells cortex cs.lg emergence environment firing grid hexagon maps networks normalization paper patterns q-bio.nc rat stat.ml study training type