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首页> 外文期刊>AEU: Archiv fur Elektronik und Ubertragungstechnik: Electronic and Communication >Mode transition and energy dependence of FitzHugh-Nagumo neural model driven by high-low frequency electromagnetic radiation
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Mode transition and energy dependence of FitzHugh-Nagumo neural model driven by high-low frequency electromagnetic radiation

机译:高低频电磁辐射驱动Fitzhugh-Nagumo神经模型的模式转换与能量依赖性

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The FitzHugh-Nagumo (FHN) neural model is widely used to study the dynamic characteristics of signal propagation, synchronization, stochastic resonance(SR), coherent resonance(CR), and bifurcation of neurons. Based on Helmholtz theorem and the FHN neuron model, the expression of Hamilton energy function of FHN neural model driven by high-low frequency(HLF) electromagnetic radiation is derived. The correctness and uniqueness of the analytical solution are verified by using the constraints, and the electrical activities and Hamilton energy function of neuron are discussed by numerical simulations. It is found that electrical activity mode of FHN neuron undergoes a succession transition of quiescent state, spiking state, bursting state, and mixed state by changing the parameters such as the intensity of the external forcing current, the amplitude and angular frequency of HLF signal. The electrical activities process of FHN neuron is accompanied by the storage and release of system energy, this result may provide an understanding of the coding and conversion of electrical activity from the perspective of the relevance and dependence of energy costs. (C) 2020 Elsevier GmbH. All rights reserved.
机译:Fitzhugh-Nagumo(FHN)神经模型广泛用于研究信号传播,同步,随机共振(SR),相干共振(CR)和神经元分叉的动态特性。基于Helmholtz定理和FHN神经元模型,推导了由高低频率(HLF)电磁辐射驱动的FHN神经模型Hamilton能量功能的表达。通过使用约束来验证分析解决方案的正确性和唯一性,并且通过数值模拟讨论了神经元的电气活动和汉密尔顿能量功能。发现FHN神经元的电活动模式通过改变外部强制电流的强度,HLF信号的幅度和角度频率,通过改变静态状态,尖峰状态,爆裂状态和混合状态的连续转变。 FHN神经元的电气活动过程伴随着系统能量的存储和释放,该结果可以从相关性和能源成本的相关性和依赖性的角度来了解电活动的编码和转化。 (c)2020 Elsevier GmbH。版权所有。

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