经颅磁声电刺激下修正Hindmarsh-rose耦合模型的理论分析

Q4 Engineering
Liang Guo, Shuai Zhang, Jian-kang Wu, Xinyu Gao, Mingkang Zhao, Guizhi Xu
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引用次数: 0

摘要

经颅磁声电刺激(TMAES)是一种利用超声波和静态磁场在神经组织内产生电流来调节神经元放电活动的新技术。现有的神经元模型只能模拟单个神经元,对TMAES的耦合神经元模型研究较少。大脑皮层中的大多数神经元不是孤立的,而是相互连接的。研究耦合神经元的信息传递是十分必要的。神经元耦合突触的类型包括电突触和化学突触。不考虑化学突触的神经元模型是不全面的。在这里,我们修改了Hindmarsh-Rose (HR)模型来模拟TMAES下最小的神经系统-两个神经元耦合的电突触和化学突触。描述两个神经元之间突触耦合的环境变量和神经系统的非线性也被考虑在内。神经系统的放电行为可以通过改变强度或调制频率来调节。结果表明,在一定的参数范围内,通过改变刺激的调制频率和强度,调节神经元的兴奋性,缩短化学突触后神经元的反应时间,加速信息传递,可以增加耦合神经元的放电频率。此外,神经元放电频率对刺激参数具有选择性。这些结果证明了TMAES对神经元放电频率特性的可能的理论调控机制。本研究为大规模神经网络建模奠定了基础,可作为TMAES实验和临床应用的理论依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Theoretical Analysis of Coupled Modified Hindmarsh-rose Model Under Transcranial Magnetic-acoustic Electrical Stimulation
Transcranial magnetic-acoustic electrical stimulation (TMAES) is a new technology with ultrasonic waves and a static magnetic field to generate an electric current in nerve tissues to modulate neuronal firing activities. The existing neuron models only simulate a single neuron, and there are few studies on coupled neurons models about TMAES. Most of the neurons in the cerebral cortex are not isolated but are coupled to each other. It is necessary to study the information transmission of coupled neurons. The types of neuron coupled synapses include electrical synapse and chemical synapse. A neuron model without considering chemical synapses is not comprehensive. Here, we modified the Hindmarsh-Rose (HR) model to simulate the smallest nervous system—two neurons coupled electrical synapses and chemical synapses under TMAES. And the environmental variables describing the synaptic coupling between two neurons and the nonlinearity of the nervous system are also taken into account. The firing behavior of the nervous system can be modulated by changing the intensity or the modulation frequency. The results show that within a certain range of parameters, the discharge frequency of coupled neurons could be increased by altering the modulation frequency, and intensity of stimulation, modulating the excitability of neurons, reducing the response time of chemical postsynaptic neurons, and accelerating the information transferring. Moreover, the discharge frequency of neurons was selective to stimulus parameters. These results demonstrate the possible theoretical regulatory mechanism of the neurons' firing frequency characteristics by TMAES. The study establishes the foundation for large-scale neural network modeling and can be taken as the theoretical basis for TMAES experimental and clinical application.
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来源期刊
International Journal of Circuits, Systems and Signal Processing
International Journal of Circuits, Systems and Signal Processing Engineering-Electrical and Electronic Engineering
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