基于Hodgkin-Huxley模型的神经元网络信息编码模式对比-《中国医学物理学杂志》

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Title:: Comparative study on the information encoding mode of neuronal networks based on Hodgkin-Huxley model

文章编号:: 1005-202X（2024）02-0212-08

作者:: 刘瑾琬; 逯迈; 兰州交通大学光电技术与智能控制教育部重点实验室，甘肃兰州 730070

Author(s):: LIU Jinwan; LU Mai; Key Laboratory of Optoelectronic Technology and Intelligent Control (Ministry of Education), Lanzhou Jiaotong University, Lanzhou 730070, China

关键词:: Hodgkin-Huxley模型; 神经元网络; 数值模拟; 平均频率编码; 峰峰间隔编码

Keywords:: Keywords: Hodgkin-Huxley model neuronal network numerical simulation average frequency encoding interspike interval encoding

分类号:: R318；Q811.2

DOI:: DOI:10.3969/j.issn.1005-202X.2024.02.014

文献标志码:: A

摘要:: 目的：基于Hodgkin-Huxley（HH）神经元模型的神经元网络信息编码模式提出两类不同的信息编码方法对比。方法：采取HH神经元模型和化学突触，利用数值模拟的方法搭建不同拓扑结构的生物神经元网络，通过平均频率编码和峰峰间隔编码（ISIs）两种信息编码方法对比研究在正弦波信号和随机音频信号刺激下平均频率编码和ISIs编码的特异性，分析不同刺激信号下神经元网络的信息编码模式。结果：神经元网络的信息编码模式与刺激信号类型具有相关性：当刺激信号为连续的周期信号时，神经元网络会产生与刺激信号对应的具有周期性的放电序列；当刺激信号为随机信号时，神经元网络的放电率会随着刺激信号强度发生变化，刺激信号强度越大，动作电位发放率越高。在同一刺激信号下，神经元网络的拓扑结构会影响神经元网络放电序列的时间结构。结论：神经元网络信息编码模式与刺激信号相关，不同拓扑结构的神经元网络放电序列时间结构不同。ISIs编码方法精确度更高，包含的信息量更大，与平均频率编码相结合的编码方法能够有效表达神经元网络在刺激信号下信息编码模式的动态改变。

Abstract:: Abstract: Objective To propose two different types of information encoding methods for the information encoding mode of neuronal networks based on Hodgkin-Huxley (HH) model. Methods The biological neuronal networks with different topologies were built with numerical simulations using HH model and chemical synapses. The specificities of two information encoding methods, namely average frequency encoding and interspike interval encoding, under the stimulus of sinusoidal signals and random audio signals were investigated, and the information encoding mode of neuronal networks stimulated by different signals was also analyzed. Results The information encoding mode of the neuronal networks was correlated with the stimulus signal type. When being stimulated by a continuous periodic signal, the neuronal network would generate a discharge sequence with periodicity corresponding to the stimulus signal. When the stimulus signal was a random signal, the discharge rate of the neuronal network would change with the stimulus signal intensity, and the higher the stimulus signal intensity was, the higher the action potential discharge rate was. Under the same stimulus signal, the temporal structure of the neuronal network discharge sequence was affected by the topology of the neuronal network. Conclusion The information encoding mode of neuronal networks is correlated with the stimulus signal, and the temporal structure of the discharge sequence of neuronal networks with different topologies is different. Interspike interval encoding has higher accuracy and contains more information, and the combination with the average frequency encoding can effectively express the dynamic change of the information encoding mode of neuronal networks under the stimulus.

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《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

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