一类新的光电神经元模型及其动力学

刘勇; 徐万江; 马军; Faris ALZAHRANI; Aatef HOBINY

doi:10.1631/FITEE.1900606

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一类新的光电神经元模型及其动力学

常规文章 | Updated：2022-05-19

- 一类新的光电神经元模型及其动力学
- A new photosensitive neuron model and its dynamics
- 信息与电子工程前沿（英文） 2020年21卷第9期页码：1387-1396
- Affiliations：
  
  School of Mathematics and Statistics, Yancheng Teachers University, Yancheng 224002, China
  Department of Physics, Lanzhou University of Technology, Lanzhou 730050, China
  School of Science, Chongqing University of Posts and Telecommunications, Chongqing 430065, China
  NAAM-Research Group, Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Author bio：
  
  Jun MA, E-mail: hyperchaos@163.com; hyperchaos@lut.edu.cn
- Funds：
  
  Project supported by the National Natural Science Foundation of China (No. 11672122) and the Hongliu First-Class Disciplines Development Program of Lanzhou University of Technology, China
- DOI：10.1631/FITEE.1900606
  中图分类号： TN710;O59
- 收稿：2019-11-09，
  
  修回：2020-;3-31，
  
  网络出版：2020-04-21，
  
  纸质出版：2020-09
- Accepted：
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刘勇, 徐万江, 马军, 等. 一类新的光电神经元模型及其动力学[J]. 信息与电子工程前沿（英文）, 2020,21(9):1387-1396.

Yong LIU, Wan-jiang XU, Jun MA, et al. A new photosensitive neuron model and its dynamics[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(9): 1387-1396.
刘勇, 徐万江, 马军, 等. 一类新的光电神经元模型及其动力学[J]. 信息与电子工程前沿（英文）, 2020,21(9):1387-1396. DOI： 10.1631/FITEE.1900606.

Yong LIU, Wan-jiang XU, Jun MA, et al. A new photosensitive neuron model and its dynamics[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(9): 1387-1396. DOI： 10.1631/FITEE.1900606.

摘要

生物神经元可感知多种外界刺激信号，这些信号可被转化为等效的电流来驱动神经元。因此，神经元的膜电位可通过外刺激调控呈现各类放电模式。实际上，可靠的神经元模型应考虑内在的生物物理效应以及功能性编码。一个重要且有趣的问题是弄清外界信号转录过程的物理机制。外界信号通常被转化为等效的跨膜电流或信号源以诱发动作电位。提出一个光电神经元模型以表达其非线性编码过程和外界光信号驱动神经元的电活动响应。在该模型中，使用一个光电管激活一个简单的FitzHugh-Nagumo（FHN）神经元电路，并施加外界光信号（光照）于光电管产生时变电流源或电压源以驱动神经元电路。这种光电管耦合的神经元电路能探测和感知外界光信号，其作用类似于人工电子眼。通过分岔详细分析神经元模态迁移和放电斑图特征。通过调制神经元电路的光电流，神经元膜电位序列可呈现静息态、尖峰放电、簇放电和混沌特征。这些结果可为进一步研究神经动力学和神经电路提供参考。

Abstract

Biological neurons can receive inputs and capture a variety of external stimuli

which can be encoded and transmitted as different electric signals. Thus

the membrane potential is adjusted to activate the appropriate firing modes. Indeed

reliable neuron models should take intrinsic biophysical effects and functional encoding into consideration. One fascinating and important question is the physical mechanism for the transcription of external signals. External signals can be transmitted as a transmembrane current or a signal voltage for generating action potentials. We present a photosensitive neuron model to estimate the nonlinear encoding and responses of neurons driven by external optical signals. In the model

a photocell (phototube) is used to activate a simple FitzHugh-Nagumo (FHN) neuron

and then external optical signals (illumination) are imposed to excite the photocell for generating a time-varying current/voltage source. The photocell-coupled FHN neuron can therefore capture and encode external optical signals

similar to artificial eyes. We also present detailed bifurcation analysis for estimating the mode transition and firing pattern selection of neuronal electrical activities. The sampled time series can reproduce the main characteristics of biological neurons (quiescent

spiking

bursting

and even chaotic behaviors) by activating the photocell in the neural circuit. These results could be helpful in giving possible guidance for studying neurodynamics and applying neural circuits to detect optical signals.

关键词

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