The inverse stochastic resonance in a small-world neuronal network under electromagnetic stimulation.
10.7507/1001-5515.202209021
- Author:
Huilan YANG
1
;
Shuxiang TIAN
2
;
Haijun ZHU
3
;
Guizhi XU
1
Author Information
1. School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, P. R. China.
2. Beijing Key Laboratory of Drug Dependence, National Institute on Drug Dependence, Peking University, Beijing 100191, P. R. China.
3. Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electronic & Information Engineering, Hebei University, Baoding, Hebei 071002, P. R. China.
- Publication Type:Journal Article
- Keywords:
Electromagnetic stimulation;
Inverse stochastic resonance;
Neural network;
Neural regulation
- MeSH:
Action Potentials/physiology*;
Computer Simulation;
Models, Neurological;
Stochastic Processes;
Neurons/physiology*;
Electromagnetic Phenomena
- From:
Journal of Biomedical Engineering
2023;40(5):859-866
- CountryChina
- Language:Chinese
-
Abstract:
Electromagnetic stimulation is an important neuromodulation technique that modulates the electrical activity of neurons and affects cortical excitability for the purpose of modulating the nervous system. The phenomenon of inverse stochastic resonance is a response mechanism of the biological nervous system to external signals and plays an important role in the signal processing of the nervous system. In this paper, a small-world neural network with electrical synaptic connections was constructed, and the inverse stochastic resonance of the small-world neural network under electromagnetic stimulation was investigated by analyzing the dynamics of the neural network. The results showed that: the Levy channel noise under electromagnetic stimulation could cause the occurrence of inverse stochastic resonance in small-world neural networks; the characteristic index and location parameter of the noise had significant effects on the intensity and duration of the inverse stochastic resonance in neural networks; the larger the probability of randomly adding edges and the number of nearest neighbor nodes in small-world networks, the more favorable the anti-stochastic resonance was; by adjusting the electromagnetic stimulation parameters, a dual regulation of the inverse stochastic resonance of the neural network can be achieved. The results of this study provide some theoretical support for exploring the regulation mechanism of electromagnetic nerve stimulation technology and the signal processing mechanism of nervous system.
