内在噪声揭示了神经元网络的稳定性
Marcelo Bussotti Reyes1, Ramon Huerta2, Pedro Valadão Carelli3
1Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, Santo André, Brasil.
bioRxiv : the preprint server for biology
|August 8, 2025
概括
称为中央模式生成器 (CPG) 的神经网络具有强大的稳定性. 使用自然噪声的新定量方法表明,即使经过显著的突触修饰,CPG也保持稳定.
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.
- 系统神经科学 系统神经科学
背景情况:
- 神经网络中的节律活动,特别是中央模式生成器 (CPG),对于运动控制至关重要.
- 与其他生理节奏相比,CPGs的定量稳定性分析仍未得到充分研究.
研究的目的:
- 开发和应用一种新的定量方法来评估CPG中节律活动的稳定性.
- 为了研究突触修饰对胆管CPG电路稳定性的影响.
主要方法:
- 利用CPG中固有的噪声来量化节律活动稳定性.
- 采用静止启动方法来进行可靠的置信区间估计.
- 通过动态软件实现人造突触,以扰乱 pyloric CPG.
主要成果:
- 提出的方法成功量化了CPG的稳定性.
- 切除甲状腺CPG中的强突触并没有改变其整体稳定性.
- 证实CPG稳定性能够抵御参数扰动.
结论:
- CPGs具有固有的,强大的稳定性,这在很大程度上独立于个人的突触强度.
- 开发的方法为神经电路中的定量稳定性分析提供了有价值的工具.
- 这种弹性表明神经回路的强大设计原则是节奏行为的基础.
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