Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise.

Response of Electrical Activity in an Improved Neuron Model under Electromagnetic Radiation and Noise.
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改进的神经元模型在电磁辐射和噪声下的电活动响应

DOI:
10.3389/fncom.2017.00107
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发表时间:
2017
影响因子:
3.2
通讯作者:
Liu S
Liu S
中科院分区:
医学4区
文献类型:
--
作者:
Zhan F;Liu S

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电活动是普遍存在的神经元生物电现象,它以多种不同的方式编码生物信息的表达,构成了神经元之间信号传播的整个过程。因此,我们关注神经元的电活动,这也引起了神经科学家的广泛关注。本文主要研究了Morris-Lecar(M-L)模型在电磁辐射或高斯白色噪声作用下的电活动,该模型能较好地还原真实神经网络中神经元的真实性。首先,我们探讨了整个系统在电磁感应(EMI)和高斯白色噪声作用下的动力学响应。通过对比改进前后系统的放电响应发现,两种系统的放电行为略有不同,电磁感应可以将脉冲放电状态转化为静止放电状态,反之亦然。进一步,利用单参数和双参数分岔分析方法,研究了具有电磁感应的孤立神经元模型的突发跃迁模式和相应的周期解机制.最后,我们分析了高斯白色噪声对原系统和耦合系统的影响,这有利于了解现实神经元的实际放电特性。
Electrical activities are ubiquitous neuronal bioelectric phenomena, which have many different modes to encode the expression of biological information, and constitute the whole process of signal propagation between neurons. Therefore, we focus on the electrical activities of neurons, which is also causing widespread concern among neuroscientists. In this paper, we mainly investigate the electrical activities of the Morris-Lecar (M-L) model with electromagnetic radiation or Gaussian white noise, which can restore the authenticity of neurons in realistic neural network. First, we explore dynamical response of the whole system with electromagnetic induction (EMI) and Gaussian white noise. We find that there are slight differences in the discharge behaviors via comparing the response of original system with that of improved system, and electromagnetic induction can transform bursting or spiking state to quiescent state and vice versa. Furthermore, we research bursting transition mode and the corresponding periodic solution mechanism for the isolated neuron model with electromagnetic induction by using one-parameter and bi-parameters bifurcation analysis. Finally, we analyze the effects of Gaussian white noise on the original system and coupled system, which is conducive to understand the actual discharge properties of realistic neurons.
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