随机连接的神经元的稀疏网络中的相位同步在波伊索纳尖端输入的作用下
Bruno R R Boaretto1, Paulo R Protachevicz2,3, Matheus Hansen4
1Institute of Science and Technology, Universidade Federal de São Paulo, 12247-014 São José dos Campos, São Paulo, Brazil.
Chaos (Woodbury, N.Y.)
|December 11, 2023
概括
这项研究表明,当外部电流强,但通过合平衡时,神经网络会同步. 过度的电流阻止了同步,突出了化学突触网络中的复杂动态.
科学领域:
- 神经科学是一个神经科学.
- 计算神经科学是一种神经科学.
- 复杂的系统复杂的系统.
背景情况:
- 神经网络表现出由突触连接和外部刺激影响的复杂动态.
- 阶段同步是理解新兴网络行为的关键现象.
- 霍奇金-哈克斯利模型为模拟神经元活动提供了一个基本框架.
研究的目的:
- 研究导致化学突触随机连接的神经网络中的相位同步的条件.
- 分析外部电流和突触合对网络同步的影响.
- 探索神经元组合中同步和脱同步背后的机制.
主要方法:
- 使用经典的霍奇金-哈克斯利模型进行神经元动力学模拟.
- 采用一个随机连接的神经元网络与化学突触.
- 应用Poissonian尖峰的列车作为外部刺激.
- 在不同的外部电流和合强度下分析网络行为.
主要成果:
- 观察到在特定导电量范围内出现不规则的尖峰.
- 当外部电流足以进行尖端连接,但不主导合时,可以实现相位同步.
- 发现高的外部电流阻止了网络同步.
- 证明刺激部分神经元可以诱导未受刺激部分的同步.
- 通过突触合,通过网络展示了尖端活动的传播.
结论:
- 神经网络同步是外部驱动器和内部合之间的微妙平衡.
- 随机效应和当前动态在网络连贯性中起着至关重要的作用.
- 有针对性的刺激可以是诱导或控制网络同步的策略.
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