在局部活跃的基于memristor的神经元的合动态
Yujiao Dong1, Rongrong Guo1, Yan Liang1
1Institute of Modern Circuit and Intelligent Information, Hangzhou Dianzi University, Hangzhou 310018, China.
Chaos (Woodbury, N.Y.)
|August 15, 2024
概括
结合相同的第三阶记忆神经元揭示了复杂的类似大脑的动态. 电阻合会诱导新的状态,网络模拟会产生奇特的时空模式,比如喜梅拉状态.
科学领域:
- 神经科学是一个神经科学.
- 复杂的系统复杂的系统.
- 非线性动力学是一种非线性动力学.
背景情况:
- 类似大脑的动态需要更高层次的复杂性.
- 记忆神经元为神经形态计算提供了一个平台.
- 了解合神经元的行为对于网络功能至关重要.
研究的目的:
- 研究对相同的第三阶记忆神经元的合效应.
- 探索不同操作模式和合强度下的动态.
- 在一个更大的网络中分析新出现的时空模式.
主要方法:
- 模拟单个和合的第三阶记忆神经元的动态.
- 应用了电阻合,并分析了在不同偏差条件下的行为.
- 利用霍夫的分叉理论来解释同步现象.
- 构建了一个具有抵抗性突触的100个神经元环网络.
主要成果:
- 不结合的神经元表现出休息状态,周期性升或混乱状态.
- 休息神经元的电阻合会诱导不均的状态 (静态/动态Smale悖论).
- 结合的尖峰/混乱神经元显示振荡死亡,异步或同步.
- 这100个神经元网络产生了嵌合体死亡,振幅嵌合体,孤独状态和异步.
结论:
- 第三阶段的记忆性神经元合产生了多样化和复杂的动态.
- 网络中的对称性打破导致了异国情调的时空模式.
- 这些发现有助于通过非线性电路理论理解神经形态网络.
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