A cubic-quadratic phenomenological model explains the spiking, chaotic and bursting behaviors of neuron
Shuihan Qiu, Yeyuge Chen, Zengru Di
TL;DR
This paper introduces a new neuron model that can simulate spiking, bursting, and chaotic behaviors using a two-dimensional mathematical framework.
Contribution
The novel contribution is a two-dimensional phenomenological model that captures diverse neuron dynamics through bifurcation analysis.
Findings
The model exhibits Andronov-Hopf and saddle-point bifurcations.
Periodic input currents can reproduce spiking, bursting, and chaotic behaviors.
The model's behavior changes with input current frequency.
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.
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Taxonomy
TopicsNeural dynamics and brain function · stochastic dynamics and bifurcation · Chaos control and synchronization