ArticleCognitive neurodynamics2020
Various firing activities and finite-time synchronization of an improved Hindmarsh-Rose neuron model under electric field effect.
Article in Cognitive neurodynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- Physics-informed Koopman learning approach for fixed-time synchronization of stochastic neural dynamics.Scientific reports · 2026Article
- Fast-slow dynamics in a memristive ion channel-based bionic circuit.Cognitive neurodynamics · 2024Article
- Topology identification and dynamical pattern recognition for Hindmarsh-Rose neuron model via deterministic learning.Cognitive neurodynamics · 2023Article
- Control of noise-induced coherent oscillations in three-neuron motifs.Cognitive neurodynamics · 2022Article
- A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics.Journal of bionic engineering · 2022Article
- Anti-control of periodic firing in HR model in the aspects of position, amplitude and frequency.Cognitive neurodynamics · 2021Article
- Complex bifurcation analysis and synchronization optimal control for Hindmarsh-Rose neuron model under magnetic flow effect.Cognitive neurodynamics · 2021Article
- Window of multistability and its control in a simple 3D Hopfield neural network: application to biomedical image encryption.Neural computing & applications · 2021Article
- The Study for Synchronization between Two Coupled FitzHugh-Nagumo Neurons Based on the Laplace Transform and the Adomian Decomposition Method.Neural plasticity · 2021Article
- A Synchronization Criterion for Two Hindmarsh-Rose Neurons with Linear and Nonlinear Coupling Functions Based on the Laplace Transform Method.Neural plasticity · 2021Article
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6 authors.
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Abstract
Nowadays, it is important to realize systems that can model the electrical activity of neurons taking into account almost all the properties of the intracellular and extracellular environment in which they are located. It is in this sense that we propose in this paper, the improved model of Hindmarsh-Rose (HR) which takes into account the fluctuation of the membrane potential created by the variation of the ion concentration in the cell. Considering the effect of the electric field that is produced on the dynamic behavior of neurons, the essential properties of the model such as equilibrium point and its stability, bifurcation diagrams, Lyapunov spectrum, frequency spectra, time series of the membrane potential and phase portraits are thoroughly investigated. We thus prove that Hopf bifurcation occurs in this system when the parameters are chosen appropriately. We also observe that by varying specific parameters of the electric field, the model presents a very rich and striking event, namely hysteresis phenomenon, which justifies the coexistence of multiple attractors. Besides, by applying a suitable sinusoidal excitation current, we prove that the neuron under electric field effect can present several important electrical activities including quiescent, spiking, bursting and even chaos. We propose the improved HR model under electric field effect (mHR) to study the finite-time synchronization between two neurons when performing synapse coupling across the membrane potential and the electric field coupling. As a result, we find that the synchronization between the two neurons is weakly influenced by the variation of the intensity of the electric field coupling while it is strongly impacted when the intensity of the synapse coupling is modified. From these results, it is obvious that the electric field can be another effective bridge connection to encourage the exchange and coding of the signal. Using the finite-time synchronization algorithm, we theoretically quantify the synchronization time between these neurons. Finally, Pspice simulations are presented to show the feasibility of the proposed model as well as that of the developed synchronization strategy.
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