Wave emitting and propagation induced by autapse in a forward feedback neuronal network

Ma, Jun; Song, Xiaoqiu; Tang, Jun; Wang, Chunni

doi:10.1016/j.neucom.2015.04.056

Cited by 115 publications

(27 citation statements)

References 62 publications

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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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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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“…The external forcing current and other bifurcation parameters [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26] are used to investigate the transition between modes of electrical activities and dynamical response because the excitability of neuron can be changed by external electric stimuli effectively. For example, Wang et al [10,11] studied the fact that neuron electrical activities can be modulated by an external electric field and the responses of three classes of Morris-Lecar neurons to sinusoidal inputs and synaptic pulse-like stimuli.…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, the relevant topics about neurodynamics and neuronal network have been investigated widely by the known neuron models [20][21][22][23][24][25][26][27][28][29]. For example, Jun et al Complexity [20] investigated dynamic characteristics of the fractionalorder Hindmarsh-Rose (HR) neuronal model, and the results showed possible differences in dynamic characteristic between the fractional-order HR neuronal model and an integer-ordered model.…”

Section: Introductionmentioning

confidence: 99%

“…Guo et al [21] found that both excitatory and electrical autapses increase the occurrence of burst firing, thus reducing neuronal firing regularity. It is also found that a time delay could decrease and suppress the chaotic state in the case of inhibitory chemical selfconnections with a proper autaptic intensity [22][23][24]. Yi et al [25] constructed the fact that neuron can exhibit different spiking patterns, even chaotic behaviors, depending on the values of stimulus frequencies.…”

Section: Introductionmentioning

confidence: 99%

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Mixed Stimulus-Induced Mode Selection in Neural Activity Driven by High and Low Frequency Current under Electromagnetic Radiation

et al. 2017

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The electrical activities of neurons are dependent on the complex electrophysiological condition in neuronal system, the threevariable Hindmarsh-Rose (HR) neuron model is improved to describe the dynamical behaviors of neuronal activities with electromagnetic induction being considered, and the mode transition of electrical activities in neuron is detected when external electromagnetic radiation is imposed on the neuron. In this paper, different types of electrical stimulus impended with a highlow frequency current are imposed on new HR neuron model, and mixed stimulus-induced mode selection in neural activity is discussed in detail. It is found that mode selection of electrical activities stimulated by high-low frequency current, which also changes the excitability of neuron, can be triggered owing to adding the Gaussian white noise. Meanwhile, the mode selection of the neuron electrical activity is much dependent on the amplitude of the high frequency current under the same noise intensity, and the high frequency response is selected preferentially by applying appropriate parameters and noise intensity. Our results provide insights into the transmission of complex signals in nerve system, which is valuable in engineering prospective applications such as information encoding.

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“…When autapse connection is triggered, the electrical activities and dynamical response will be changed [16][17][18]. Furthermore, autapse driving in the network can regulate the collective behaviors of network by generating continuous pulse or wave fronts, thus synchronization; pattern selection can be realized [19][20][21][22]. Readers can find brief survey for neurodynamics and dynamics in neuronal network in [23] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Autaptic Modulation of Electrical Activity in a Network of Neuron-Coupled Astrocyte

Guo

Tang

et al. 2017

Complexity

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Autapse connection is considered on a biological neuron coupled by astrocyte, and the effect of autapse driving-induced response in electrical activities is investigated. In this paper, a simple network is developed on the Hodgkin-Huxley (HH) neuron coupled by astrocyte and the autapse effect is also considered. The modulation of autapse connected to HH neuron can change the membrane potential by applying time-delayed feedback along a close loop. It is found that the self-adaption of autapse driving can make the network of neuron-astrocyte generate different modes of electrical activities, and oscillating behavior of Ca 2+ and IP 3 setting is controlled. This new network model can give potential understanding about self-adaption of neuron to external forcing when the coupling of astrocyte and autapse is considered.

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Wave emitting and propagation induced by autapse in a forward feedback neuronal network

Cited by 115 publications

References 62 publications

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

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

Mixed Stimulus-Induced Mode Selection in Neural Activity Driven by High and Low Frequency Current under Electromagnetic Radiation

Autaptic Modulation of Electrical Activity in a Network of Neuron-Coupled Astrocyte

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