适应性共振和混乱的控制在一个新的记忆的一般化菲茨休-纳古莫爆发模型
I B Tagne Nkounga1, N Marwan2, F M Moukam Kakmeni3
1Fundamental Physics Laboratory, Physics of Complex System Group, Department of Physics, Faculty of Science, University of Douala, Box 24 157 Douala, Cameroon.
Chaos (Woodbury, N.Y.)
|October 2, 2023
概括
这项研究在记忆神经元模型中检查了自适应共振 (AR). 电磁感应可以优化AR信号检测,但也可能破坏混乱的动态和局部刺激.
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:
- 适应共振 (AR) 增强神经系统对刺激的反应.
- 记忆模型为模拟神经元行为提供了新的方法.
- 菲茨休-纳古莫模型对于理解神经振荡至关重要.
研究的目的:
- 为了研究适应性共振在一个memristive一般化的菲茨休-纳古莫爆发模型.
- 分析电磁感应对AR和神经元动态的影响.
- 探索局部刺激和混乱行为的出现和控制.
主要方法:
- 信号检测分析的和平衡方法.
- 两叉图和莱普诺夫指数用于研究系统动态.
- 用于检查局部激发和波包传播的复发图形分析.
主要成果:
- 在没有电磁感应的情况下,AR信号检测发生在共振峰.
- 小电磁感应优化了AR峰值;大电磁感应消除了它.
- 电磁感应调节周期翻倍,混乱运动和局部激发,这些激发以调制波包的形式传播.
结论:
- 具有记忆力的菲茨休-纳古莫模型表现出由适应强度和电磁感应影响的复杂动力学.
- 在神经模型中,电磁感应在调节共振现象和混乱行为的过程中起着至关重要的作用.
- 基于反复性的分析提供了对局部激发的复杂时空动态的洞察.
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