Adaptive Synchronization of Neural and Physical Oscillators
Abstract
Animal locomotion patterns are controlled by recurrent neural networks called central pattern generators (CPGs). Although a CPG can oscillate autonomously, its rhythm and phase must be well coordinated with the state of the physical system using sensory inputs. In this paper we propose a learning algorithm for synchronizing neural and physical oscillators with specific phase relationships. Sensory input connections are modified by the correlation between cellular activities and input signals. Simulations show that the learning rule can be used for setting sensory feedback connections to a CPG as well as coupling connections between CPGs.
Cite
Text
Doya and Yoshizawa. "Adaptive Synchronization of Neural and Physical Oscillators." Neural Information Processing Systems, 1991.Markdown
[Doya and Yoshizawa. "Adaptive Synchronization of Neural and Physical Oscillators." Neural Information Processing Systems, 1991.](https://mlanthology.org/neurips/1991/doya1991neurips-adaptive/)BibTeX
@inproceedings{doya1991neurips-adaptive,
title = {{Adaptive Synchronization of Neural and Physical Oscillators}},
author = {Doya, Kenji and Yoshizawa, Shuji},
booktitle = {Neural Information Processing Systems},
year = {1991},
pages = {109-116},
url = {https://mlanthology.org/neurips/1991/doya1991neurips-adaptive/}
}