A minimalistic representation model for head direction system
Neurons and Cognition
2025-06-04 v2 Artificial Intelligence
Computer Vision and Pattern Recognition
Machine Learning
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 , 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.
Cite
@article{arxiv.2411.10596,
title = {A minimalistic representation model for head direction system},
author = {Minglu Zhao and Dehong Xu and Deqian Kong and Wen-Hao Zhang and Ying Nian Wu},
journal= {arXiv preprint arXiv:2411.10596},
year = {2025}
}
Comments
Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci 2025)