Adaptive Synchronization of Neural and Physical Oscillators
Adaptive Synchronization of Neural and Physical Oscillators
复制标题
神经和物理振荡器的自适应同步
DOI：
--
复制
发表时间：
1991
期刊：
影响因子：
--
通讯作者：
S. Yoshizawa
中科院分区：
文献类型：
--
作者：
K. Doya;S. Yoshizawa
动物的运动模式由称为中枢模式生成器(CPGs)的递归神经网络控制。虽然CPG可以自主振荡，但它的节奏和相位必须与使用感官输入的物理系统的状态很好地协调。本文提出了一种学习算法，用于同步具有特定相位关系的神经振荡器和物理振荡器。感觉输入连接被细胞活动和输入信号之间的相关性所修正。仿真结果表明，该学习规则可用于设置CPG的感觉反馈连接以及CPG之间的耦合连接。
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.