Firing patterns of an improved Izhikevich neuron model under the effect of electromagnetic induction and noise

Kafraj, Mohadeseh Shafiei; Parastesh, Fatemeh; Jafari, Sajad

doi:10.1016/j.chaos.2020.109782

Cited by 85 publications

(21 citation statements)

References 30 publications

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“…In addition, the neuron-firing pattern was able to switch from a single burst to an intermittent multimodal burst in the presence of an electric field as the amplitude and frequency of the electric field increased. Kafraj et al [18] proposed and studied a modified Izhikevich model to characterize the activity of neurons in the presence of electromagnetic induction and noise. Their study revealed several complex phenomena in the proposed model.…”

Section: Introductionmentioning

confidence: 99%

Hamiltonian energy computation and complex behavior of a small heterogeneous network of three neurons: circuit implementation

et al. 2021

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Brain functions are sometimes emulated using some analog integrated circuits based on the organizational principle of natural neural networks. Neuromorphic engineering is the research branch devoted to the study and realization of such circuits with striking features. In this contribution, a novel small network of three neurons is introduced and investigated. The model is built from the coupling between two 2D Hindmarsh–Rose neurons through a 2D FitzHugh–Nagumo neuron. Thus, a heterogeneous coupled network is obtained. The biophysical energy released by the network during each electrical activity is evaluated. In addition, nonlinear analysis tools such as two-parameter Lyapunov exponent, bifurcation diagrams, the graph of the largest Lyapunov exponent, phase portraits, time series, as well as the basin of attractions are used to numerically investigate the network. It is found that the model can experience hysteresis justified by the simultaneous existence of three distinct electrical activities using the same set of parameters. Finally, the circuit implementation of the network is addressed in PSPICE to further support the obtained results.

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Section: Introductionmentioning

confidence: 99%

Hamiltonian energy computation and complex behavior of a small heterogeneous network of three neurons: circuit implementation

et al. 2021

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“…On the one hand, external electromagnetic stimulation can change the dynamic behavior of the nervous system. For example, external stimulating currents or external electric fields can affect the excitability of nervous system and the generation and conduction of nervous system information [25][26][27]. On the other hand, electrical stimulation has become an emerging means of treating neuropsychiatric diseases [28,29].…”

Section: Introductionmentioning

confidence: 99%

Bifurcation Analysis of a Two-Dimensional Neuron Model under Electrical Stimulation

Yuan

2021

Mathematical Problems in Engineering

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The two-dimensional neuron model can not only reproduce abundant firing patterns, but also satisfy the research of dynamical behavior because of its nonlinear characteristics. It is the most simplified model that includes the fast and slow variables required for neuron firing. In this paper, the dynamic characteristics of two-dimensional neuron model are described by both analytical and numerical methods, and the influence of model parameters and external stimuli on dynamic characteristics is described. The firing characteristics of the Prescott model under external electrical stimulation are studied, and the influence of electrophysiological parameters on the firing characteristics is analyzed. The saddle-node bifurcation and Hopf bifurcation characteristics are studied through the distribution of equilibrium points. It is found that there are critical saddle-node bifurcation and critical Hopf bifurcation in the Prescott model. And the value range of the key parameters that cause the critical bifurcation of the model is obtained by analytical methods.

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“…Since a new four-variable HR neural model was established by introducing a magnetic flow which regulates the membrane potential through a memristor [42], [43], the influence of electromagnetic induction on neuronal electrical activity has attracted wide attention, e.g., the impact of mixed signal stimulus on neural activity under electromagnetic radiation were investigated [44], [45]. The influence of electromagnetic induction and noise on firing patterns of an improved Izhikevich neuron model were discussed [46].…”

Section: Introductionmentioning

confidence: 99%

Synchronous Dynamics in Multilayer Memristive Neural Networks: Effect of Electromagnetic Induction

Zhou

De-min

2020

IEEE Access

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Brain has a hierarchical structure with multiple connection types. To further explore the effect of electromagnetic induction on biological neural networks, in this paper, a two-layer small-world neuronal network with electrical intra-layer connections and memristive inter-layer connections was constructed. In specially, the two layer have different spiking and bursting activities. Electrical coupling strength and electromagnetic induction coefficient are taken as control parameter. Numerical results indicate that the two-layer neurons in different discharge states can achieve synchronization and the firing patterns of the synchronized neurons are related to the electromagnetic induction. Moreover, some particular dynamical states including chimera state and bursting transition are observed in the network. Then, the mechanisms of the two burst transitions are clarified. In addition, the statistical synchronization factor and average error are introduced to measure the intra-layer and inter-layer synchronization, respectively, which reveal that electrical coupling induces and enhances the synchronization more effectively for a higher electromagnetic induction coefficient. Our obtained results indicate that the electromagnetic induction exerts significant impact in modulating the dynamic behavior of neural networks, and provide a useful guidance on the study of physiological functions related to synchronization in the brain.

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Firing patterns of an improved Izhikevich neuron model under the effect of electromagnetic induction and noise

Cited by 85 publications

References 30 publications

Hamiltonian energy computation and complex behavior of a small heterogeneous network of three neurons: circuit implementation

Hamiltonian energy computation and complex behavior of a small heterogeneous network of three neurons: circuit implementation

Bifurcation Analysis of a Two-Dimensional Neuron Model under Electrical Stimulation

Synchronous Dynamics in Multilayer Memristive Neural Networks: Effect of Electromagnetic Induction

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