Phase synchronization of bursting neural networks with electrical and delayed dynamic chemical couplings

Ngouonkadi, Elie Bertrand Megam; Nono, Martial Kabong; Tamba, Victor Kamdoum; Fotsin, Hilaire Bertrand

doi:10.1140/epjb/e2015-60505-7

Cited by 5 publications

(4 citation statements)

References 52 publications

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“…It is known that neurons are noisy elements, and noise arises from many different sources, such as the quasi-random release of neurotransmitters by synapses and random synaptic input from other neurons (external synaptic noise), and the random switching of the stochastic gates of ion channels (internal channel noise) (Ngouonkadi et al 2015).…”

Section: Resultsmentioning

confidence: 99%

“…It is well known that synchronization is crucial to the information transmission among coupled neurons, it is correlated with many physiological mechanisms of normal and pathological brain functions (Wang et al 2015a(Wang et al , b, 2016Banerjee et al 2016;Mehta et al 2002) as well as with several neurological diseases (Wang et al 2016;Levy et al 2000;Mormann et al 2003;Wu et al 2014), such as epilepsy and tremor in Parkinson's disease. In the past decade, synchronization phenomena in coupled neural system has been extensively studied and many synchronization phenomena have been found, such as noise-induced synchronization (Wu et al 2014;Wang et al 2015b;Zhou and Kurths 2003;Perc 2009), bursting synchronization (Ngouonkadi et al 2016), time delayinduced synchronization (Zhang et al 2014), the partial synchronization (Steur et al (2012), the phase synchronization (Yu et al 2011;Ngouonkadi et al 2015). For instance, Zhang et al (2014) studied the synchronization of time-delayed chemically coupled burst-spiking neurons with correlated noises.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, Zhang et al (2014) studied the synchronization of time-delayed chemically coupled burst-spiking neurons with correlated noises. Ngouonkadi et al (2015) reported phase synchronization of bursting neural networks with electrical and delayed dynamic chemical couplings.…”

Section: Introductionmentioning

confidence: 99%

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Cooperative effect of random and time-periodic coupling strength on synchronization transitions in one-way coupled neural system: mean field approach

2017

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The cooperative effect of random coupling strength and time-periodic coupling strengh on synchronization transitions in one-way coupled neural system has been investigated by mean field approach. Results show that cooperative coupling strength (CCS) plays an active role for the enhancement of synchronization transitions. There exist an optimal frequency of CCS which makes the system display the best CCS-induced synchronization transitions, a critical frequency of CCS which can not further affect the CCS-induced synchronization transitions, and a critical amplitude of CCS which can not occur the CCS-induced synchronization transitions. Meanwhile, noise intensity plays a negative role for the CCS-induced synchronization transitions. Furthermore, it is found that the novel CCS amplitude-induced synchronization transitions and CCS frequency-induced synchronization transitions are found.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Cooperative effect of random and time-periodic coupling strength on synchronization transitions in one-way coupled neural system: mean field approach

2017

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“…In addition, the distribution of natural frequencies, which determines the intrinsic property and classification of uncoupled oscillators, can influence the dynamics of coupled oscillators. There have been a series of works reporting on how the topological properties of the symmetric unimodal and bimodal distribution with or without time delays produce synchronization and even new dynamics [36][37][38][39][40][41][42][43][44][45]. However, in the literature, there have been only a few investigations on how the asymmetry, as well as the shift distance of the bimodal distribution of the natural frequencies, influences the elimination of synchronization in terms of the adaptive scheme with a feedback delay.…”

Section: Introductionmentioning

confidence: 99%

Adaptive elimination of synchronization in coupled oscillator

Zhou

et al. 2017

New J. Phys.

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We present here an adaptive control scheme with a feedback delay to achieve elimination of synchronization in a large population of coupled and synchronized oscillators. We validate the feasibility of this scheme not only in the coupled Kuramoto's oscillators with a unimodal or bimodal distribution of natural frequency, but also in two representative models of neuronal networks, namely, the FitzHugh-Nagumo spiking oscillators and the Hindmarsh-Rose bursting oscillators. More significantly, we analytically illustrate the feasibility of the proposed scheme with a feedback delay and reveal how the exact topological form of the bimodal natural frequency distribution influences the scheme performance. We anticipate that our developed scheme will deepen the understanding and refinement of those controllers, e.g. techniques of deep brain stimulation, which have been implemented in remedying some synchronization-induced mental disorders including Parkinson disease and epilepsy.

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Noise effects on robust synchronization of a small pacemaker neuronal ensemble via nonlinear controller: electronic circuit design

et al. 2016

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In this paper, we report on the synchronization of a pacemaker neuronal ensemble constituted of an AB neuron electrically coupled to two PD neurons. By the virtue of this electrical coupling, they can fire synchronous bursts of action potential. An external master neuron is used to induce to the whole system the desired dynamics, via a nonlinear controller. Such controller is obtained by a combination of sliding mode and feedback control. The proposed controller is able to offset uncertainties in the synchronized systems. We show how noise affects the synchronization of the pacemaker neuronal ensemble, and briefly discuss its potential benefits in our synchronization scheme. An extended Hindmarsh-Rose neuronal model is used to represent a single cell dynamic of the network. Numerical simulations and Pspice implementation of the synchronization scheme are presented. We found that, the proposed controller reduces the stochastic resonance of the network when its gain increases.

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Phase synchronization of bursting neural networks with electrical and delayed dynamic chemical couplings

Cited by 5 publications

References 52 publications

Cooperative effect of random and time-periodic coupling strength on synchronization transitions in one-way coupled neural system: mean field approach

Cooperative effect of random and time-periodic coupling strength on synchronization transitions in one-way coupled neural system: mean field approach

Adaptive elimination of synchronization in coupled oscillator

Noise effects on robust synchronization of a small pacemaker neuronal ensemble via nonlinear controller: electronic circuit design

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