在FitzHugh-Nagumo模型中抑制和频率控制重复的尖刺
Hidetsugu Sakaguchi1, Keito Yamasaki1
1Interdisciplinary Graduate School of Engineering Sciences, Kyushu University, Kasuga, Fukuoka 816-8580, Japan.
Physical review. E
|August 16, 2023
概括
我们使用FitzHugh-Nagumo模型探索了控制神经元激增的方法. 高频强迫抑制了尖,而混乱的动态和反控制提供了进一步的方法来调节神经发射率.
科学领域:
- 计算神经科学是一种神经科学.
- 非线性动力学是一种非线性动力学.
- 数学生物学 数学生物学
背景情况:
- 菲茨休-纳古莫模型是神经元电活动的简化数学表示.
- 神经元输出的特点是高峰频率或发射率,这对于信息处理至关重要.
- 了解和控制这些动态对于神经科学研究和治疗干预至关重要.
研究的目的:
- 在使用非线性动力学原理的菲茨休-纳古莫模型中研究神经元尖端的控制方法.
- 分析周期性强制和反控制对尖端行为的影响.
- 探索诱导混乱和脱同步的潜力,以调节整体尖端输出.
主要方法:
- 用数值模拟来研究过渡到抑制的尖端状态.
- 进行了线性稳定性分析,以了解尖端抑制的机制.
- 该研究检查了结合的菲茨休-纳古莫方程,并使用输入输出映射分析了反控制方法.
主要成果:
- 在FitzHugh-Nagumo模型中,高频周期性阴影强迫有效地抑制了重复的尖.
- 定期强迫可以在合系统中诱导混乱的行为,导致脱同步和减少整体尖端.
- 提出的反控制方法成功地实现了所需的尖峰和爆破频率.
结论:
- 外部周期强迫是控制神经元激增的一个可行的方法,高频率提供抑制.
- 在合的神经元模型中,混乱诱导的脱同步可以调节网络输出.
- 反控制提供了一个精确的机制来调节神经元模型中特定的尖峰和爆发频率.
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