一个三次-二次现象学模型解释了神经元的脉冲发放、混沌和爆发行为。

A cubic-quadratic phenomenological model explains the spiking, chaotic and bursting behaviors of neuron.

作者信息

Qiu Shuihan, Chen Yeyuge, Di Zengru

机构信息

School of Science, Jiangsu University of Science and Technology, Zhenjiang, 212100, China.

School of Systems Science, Beijing Normal University, Beijing, 100875, China.

出版信息

Sci Rep. 2025 Apr 25;15(1):14558. doi: 10.1038/s41598-025-98381-6.

DOI:10.1038/s41598-025-98381-6

PMID:40280995

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12032110/

Abstract

In this manuscript, we present a two-dimensional phenomenological spiking neuron model. By analyzing the bifurcation diagram and phase portraits of the two-dimensional model, Andronov-Hopf bifurcation, saddle-point bifurcation and saddle-point on invariant circle bifurcation are discussed in detail. Based on the above analysis, a periodic input current is designed to simulate the basic firing mode of a single neuron. With the change of the input current frequency, the model can reproduce rich dynamical behaviors such as spike, bursts, and chaos.

摘要

在本手稿中，我们提出了一个二维现象学脉冲神经元模型。通过分析二维模型的分岔图和相图，详细讨论了安德罗诺夫 - 霍普夫分岔、鞍点分岔和不变圆上的鞍点分岔。基于上述分析，设计了一个周期性输入电流来模拟单个神经元的基本放电模式。随着输入电流频率的变化，该模型可以重现丰富的动力学行为，如脉冲、爆发和混沌。