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Birhythmic oscillations and global stability analysis of a conductance-based neuronal model under ion channel fluctuations

By drawing inspiration from existing polynomial models for neurons, we make use of the Moris Lecar system to derive a new two dimensional birhythmic conductance-based neuronal model for nerves. The analysis of fixed points and their stability indicates that its dynamics strongly depends on the param...

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Published in:Chaos, solitons and fractals solitons and fractals, 2022-06, Vol.159, p.112126, Article 112126
Main Authors: I.B., Tagne nkounga, F.M., Moukam kakmeni, R., Yamapi
Format: Article
Language:English
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Summary:By drawing inspiration from existing polynomial models for neurons, we make use of the Moris Lecar system to derive a new two dimensional birhythmic conductance-based neuronal model for nerves. The analysis of fixed points and their stability indicates that its dynamics strongly depends on the parameters of the newly nonlinear terms introduced. Using Lindsted's method, it is observed that the neuronal system can exhibit coexistence of attractors. These coexisting attractors are on the one hand the subthreshold oscillation and on the other hand the spike generation well known in neuronal systems. After introducing the effects of the channel fluctuations in the form of a Gaussian white noise, the global stability of the attractors is analyzed. The effective active energy barrier also called threshold potential is obtained. This threshold potential is the one needed by neuron to switch from one attractor to another. The probability distribution is also studied analytically and numerically, using the Fokker–Planck type equation derived from the new model and the Monte Carlo methods. It is observed that the system physiological parameters and the intensity of the noise plays an important role in the probability of neuron to switch from the subthreshold attractor to the spiking one and vice versa. •We investigate the effects of ions channels fluctuations in a conductance-based neuronal model.•The model reveals the excitable character of the cell membrane by a coexistence of two different attracting modes named resting (small amplitude) and action potential (large amplitude), influenced by the variation of conductance coefficients.•The effects of ions fluctuations on the pseudo-potential prove that the opening and closing of ions channels modified the conductance coefficients of ions.•Escape time, residence time and energy barrier studied show the possible rhythmic transition in a quantified time between coexisting states (time interspike).•They also reveal the importance of conductance coefficients as well as the extracellular and intracellular ions variations in the neuronal system.•The PDF reveals versus the conductance coefficients, the most probable dynamic of the neuronal system in a resting state or in an action potential.
ISSN:0960-0779
1873-2887
DOI:10.1016/j.chaos.2022.112126