两个适应性合的Theta神经元的共同进化动态
Felix Augustsson1, Erik A Martens1
1Centre for Mathematical Sciences, Lund University, Märkesbacken 4, 223 62 Lund, Sweden.
Chaos (Woodbury, N.Y.)
|November 14, 2024
概括
神经网络中的自适应合可以导致复杂的行为,如同步和混乱. 这项研究分析了合强度的适应性如何影响两个Theta神经元的动态,揭示了对网络行为的新见解.
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.
- 网络科学 网络科学
背景情况:
- 偶联的振荡器和神经网络显示复杂的合作动态,对于诸如大脑活动和电网稳定性等现象至关重要.
- 共同进化的网络,在混合时间尺度上的网络和网络的动态,是一个越来越感兴趣的领域.
研究的目的:
- 为了研究两个自适应合的Theta神经元的集体行为,而没有自我相互作用.
- 通过双叉分析和模拟,了解合强度适应性的不同水平如何影响网络动态.
主要方法:
- 两叉分析以确定稳定区域和动态.
- 数字模拟以探索自适应合强度 (a) 的影响.
主要成果:
- 在非适应性极限中,分叉分析显示了稳定的静止和尖端区域,具有各种模式锁定配置.
- 增加的适应性 (a) 扩大了阿诺德的舌头,导致了多稳定的配置和潜在的周期翻倍布成混乱.
结论:
- 合强度的适应性水平显著塑造了神经网络的集体动态.
- 研究结果提供了关于神经元通信,同步机制以及适应性网络的数学理论的见解.
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