Mode transition in electrical activities of neuron driven by high and low frequency stimulus in the presence of electromagnetic induction and radiation

Ge, Mengyan; Jia, Ya; Xu, Ying; Yang, Lijian

doi:10.1007/s11071-017-3886-2

Cited by 151 publications

(37 citation statements)

References 57 publications

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“…In the past three decades, numerous simplified neuron models had been fantastically extended from the classical Hodgkin-Huxley model [1] to reconstruct the main dynamical characteristics of neuronal electrical activities [2][3][4][5][6][7][8], among which the two-and three-dimensional Hindmarsh-Rose (HR) neuron models are effective and available for dynamical analysis in electrical activities of biological neurons [9,10]. In the last few years, a wide variety of the HR neuron models, such as original three-dimensional HR models [10][11][12][13][14][15][16], extended or nonlinear feedback coupled HR models [17][18][19][20], time delayed HR models [20][21][22], fractional-order HR models [23,24], and memristor based HR models under electromagnetic radiations [9,[25][26][27], have been proposed and further studied by bifurcation analysis methods for understanding the dynamics of electrical activities among neurons [8]. For this reason, bifurcation analysis theory plays an essential role in describing mode transitions between spiking and bursting in the neuronal electrical activities [9][10][11][12][13][14][15][16][17][18]…”

Section: Introductionmentioning

confidence: 99%

Three‐Dimensional Memristive Hindmarsh–Rose Neuron Model with Hidden Coexisting Asymmetric Behaviors

Bao

et al. 2018

Complexity

128

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Since the electrical activities of neurons are closely related to complex electrophysiological environment in neuronal system, a novel three-dimensional memristive Hindmarsh–Rose (HR) neuron model is presented in this paper to describe complex dynamics of neuronal activities with electromagnetic induction. The proposed memristive HR neuron model has no equilibrium point but can show hidden dynamical behaviors of coexisting asymmetric attractors, which has not been reported in the previous references for the HR neuron model. Mathematical model based numerical simulations for hidden coexisting asymmetric attractors are performed by bifurcation analyses, phase portraits, attraction basins, and dynamical maps, which just demonstrate the occurrence of complex dynamical behaviors of electrical activities in neuron with electromagnetic induction. Additionally, circuit breadboard based experimental results well confirm the numerical simulations.

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Section: Introductionmentioning

confidence: 99%

Three‐Dimensional Memristive Hindmarsh–Rose Neuron Model with Hidden Coexisting Asymmetric Behaviors

Bao

et al. 2018

Complexity

128

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“…Besides noise and time delay, electromagnetic effect is also ubiquitous and it has been reported that electromagnetic effect has significant effects on electrical activities of neurons in some cases. [48][49][50] Therefore, the subjects of our future work is to investigate whether the results obtained in this paper are robust when neurons are subjected to combined SW noise and electromagnetic radiation.…”

Section: Discussionmentioning

confidence: 99%

Delay-induced synchronization transition in a small-world neuronal network of FitzHugh–Nagumo neurons subjected to sine-Wiener bounded noise

Yao

Hou

2019

Int. J. Mod. Phys. B

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Noise and delay are ubiquitous in brain and they have significant effects on neuronal network synchronization and even brain functions. Based on a small-world neuronal network of delayed FitzHugh–Nagumo (FHN) neurons subjected to sine-Wiener (SW) bounded noise, the effects of delay and SW noise on synchronization and synchronization transition are numerically investigated by calculating a synchronization measure R and plotting spatiotemporal patterns. The phenomenon of delay-induced synchronization transition is observed as delay [Formula: see text] is increased. And large self-correlation time and strength of SW noise can increase the number of delay-induced synchronization transition. In addition, delay-induced synchronization transition is robust against the change of topology structure of neuronal network and this phenomenon becomes much easier to see for small nearest neighbors k in the small-world network. Since synchronization transition may imply functional switch, our results may have important implications, and inspire future studies.

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“…Therefore, VR is also regarded as a possible mechanism for understanding how neurons extract target signals from a noisy environment. As a matter of fact, besides noise and HF force, there are many other factors that influence signal detection, such as network topology [22], autapse [23][24][25], time delay [26,27], and electromagnetic induction [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Subthreshold Periodic Signal Detection by Bounded Noise‐Induced Resonance in the FitzHugh–Nagumo Neuron

et al. 2018

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Neurons can detect weak target signals from complex background signals through stochastic resonance (SR) and vibrational resonance (VR) mechanisms. However, random phase variation of rapidly fluctuating background signals is generally ignored in classical VR or SR studies. Here, the rapidly fluctuating background signals are modeled by bounded noise with random rapidly fluctuating phase derived from Wiener process. Then, the influences of bounded noise on the weak signal detection are discussed in the FitzHugh-Nagumo (FHN) neuron. Numerical results reveal the occurrence of bounded noise-induced single-and biresonance as well as a transition between them. Randomness in phase can enhance the adaptability of neurons, but at the cost of signal detection performance so that neurons can work in more complex environments with a wider frequency range. More interestingly, bounded noise with appropriate parameters can not only optimize information transmission but also simultaneously reduce energy consumption. Finally, the potential mechanism of bounded noise is explained.

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Mode transition in electrical activities of neuron driven by high and low frequency stimulus in the presence of electromagnetic induction and radiation

Cited by 151 publications

References 57 publications

Three‐Dimensional Memristive Hindmarsh–Rose Neuron Model with Hidden Coexisting Asymmetric Behaviors

Three‐Dimensional Memristive Hindmarsh–Rose Neuron Model with Hidden Coexisting Asymmetric Behaviors

Delay-induced synchronization transition in a small-world neuronal network of FitzHugh–Nagumo neurons subjected to sine-Wiener bounded noise

Subthreshold Periodic Signal Detection by Bounded Noise‐Induced Resonance in the FitzHugh–Nagumo Neuron

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