论文标题

基于LIF模型的突触前神经元的外部电磁波激发

External Electromagnetic Wave Excitation of a PreSynaptic Neuron Based on LIF model

论文作者

Emamzadeh-Hashemi, Emad Arasteh, Mahdizadeh, Ailar

论文摘要

电磁波与人体组织的相互作用一直是电气和生物医学工程师的长期研究主题。但是,很少有出版物讨论外部EM波对神经系统神经刺激和通信的影响。实际上,复杂的生物神经通道是该领域完整和全面分析的主要障碍。神经通信响应中始终存在的挑战之一是囊泡释放概率对输入尖峰模式的依赖性。在这方面,这项研究阐明了改变外EM波激发对后突触后神经元尖峰率的后果。假定大脑中波的穿透深度不能覆盖突触后神经元。因此,我们建模了两部分化学突触的神经传递。此外,检查外部刺激影响神经传递的方式。与多个频率成分EM波不同,单色事件波不会在分散介质中面临频率转移和失真。以这种方式,在修改的泄漏的集成和火(LIF)模型中,将单个频率信号作为外部电流添加。结果表明,在LIF模型的一阶动力学系统中存在节点平衡点。当外部激发频率接近200 Hz时,就会发生折叠分叉(对于预设的LIF模型值)。本文提供的结果使我们能够为神经信号选择适当的频率激发。相应地,发现了LIF电路中元素值的截止频率依赖性。

Interaction of electromagnetic (EM) waves with human tissue has been a longstanding research topic for electrical and biomedical engineers. However, few numbers of publications discuss the impacts of external EM-waves on neural stimulation and communication through the nervous system. In fact, complex biological neural channels are a main barrier for intact and comprehensive analyses in this area. One of the everpresent challenges in neural communication responses is dependency of vesicle release probability on the input spiking pattern. In this regard, this study sheds light on consequences of changing the frequency of external EM-wave excitation on the post-synaptic neuron's spiking rate. It is assumed that the penetration depth of the wave in brain does not cover the postsynaptic neuron. Consequently, we model neurotransmission of a bipartite chemical synapse. In addition, the way that external stimulation affects neurotransmission is examined. Unlike multiple frequency component EM-waves, the monochromatic incident wave does not face frequency shift and distortion in dispersive media. In this manner, a single frequency signal is added as external current in the modified leaky integrated-andfire (LIF) model. The results demonstrate existence of a node equilibrium point in the first order dynamical system of LIF model. A fold bifurcation (for presupposed LIF model values) occurs when the external excitation frequency is near 200 Hz. The outcomes provided in this paper enable us to select proper frequency excitation for neural signaling. Correspondingly, the cut-off frequency reliance on elements' values in LIF circuit is found.

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