A minimalistic representation model for head direction system
Keywords: U(1) rotation symmetry group, Group representation, Recurrent neural network, Path integration
TL;DR: We present a minimalistic representation model to learn a high-dimensional representation of head direction that captures essential properties of HD cells.
Abstract: We present a minimalistic representation model for the head direction (HD) system, aiming to learn a high-dimensional representation of head direction that captures essential properties of HD cells. Our model is a representation of rotation group $U(1)$, and we study both the fully connected version and convolutional version. We demonstrate the emergence of Gaussian-like tuning profiles and a 2D circle geometry in both versions of the model. We also demonstrate that the learned model is capable of accurate path integration.
Submission Number: 64
Loading