The influence of single neuron dynamics and network topology on time delay-induced multiple synchronous behaviors in inhibitory coupled network

Zhao, Zhiguo; Gu, Huaguang

doi:10.1016/j.chaos.2015.06.017

Cited by 34 publications

(8 citation statements)

References 76 publications

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“…Except for the autapse, excitatory or inhibitory effects such as external stimulation or coupling are identified to induce abnormal phenomena. For example, inhibitory stimulation can enhance neuronal firing 65,66 , and inhibitory coupling can enhance the firing frequency of a neuronal network [67][68][69] . Such results of abnormal activities of neural firings enrich the knowledge of neurodynamic and nonlinear dynamics.…”

Section: Different Dynamical Behaviors Induced By Slow Excitatory Feementioning

confidence: 99%

“…Based on the three viewpoints that an excitatory autapse can induce abnormal dynamical behaviors 59,[62][63][64][65][66][67][68][69] , fast-decay autapses may have similar effects to type II and III excitability 26 , and slow-decay autapses may have effects on neuronal ring patterns different from fast ones 63,64 , the influences of slow-decay excitatory autapses on firing dynamics of type II and III excitability are investigated in the present paper and compared with fast-decay excitatory autapses. Four important results are obtained.…”

Section: Different Dynamical Behaviors Induced By Slow Excitatory Feementioning

confidence: 99%

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Different dynamical behaviors induced by slow excitatory feedback for type II and III excitabilities

Zhao

2020

Sci Rep

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Neuronal excitability is classified as type I, II, or III, according to the responses of electronic activities, which play different roles. In the present paper, the effect of an excitatory autapse on type III excitability is investigated and compared to type II excitability in the Morris-Lecar model, based on Hopf bifurcation and characteristics of the nullcline. The autaptic current of a fast-decay autapse produces periodic stimulations, and that of a slow-decay autapse highly resembles sustained stimulations. Thus, both fast- and slow-decay autapses can induce a resting state for type II excitability that changes to repetitive firing. However, for type III excitability, a fast-decay autapse can induce a resting state to change to repetitive firing, while a slow-decay autapse can induce a resting state to change to a resting state following a transient spike instead of repetitive spiking, which shows the abnormal phenomenon that a stronger excitatory effect of a slow-decay autapse just induces weaker responses. Our results uncover a novel paradoxical phenomenon of the excitatory effect, and we present potential functions of fast- and slow-decay autapses that are helpful for the alteration and maintenance of type III excitability in the real nervous system related to neuropathic pain or sound localization.

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Section: Different Dynamical Behaviors Induced By Slow Excitatory Feementioning

confidence: 99%

Section: Different Dynamical Behaviors Induced By Slow Excitatory Feementioning

confidence: 99%

Different dynamical behaviors induced by slow excitatory feedback for type II and III excitabilities

Zhao

2020

Sci Rep

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“…Modeling the dynamic behavior of a network has attracted much attention in recent years [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]. Gibson et al [6] showed by paired-cell recordings that while the same type of inhibitory neurons were strongly interconnected by electrical synapses, electrical synapses between different inhibitory cell types were rare.…”

Section: Introductionmentioning

confidence: 99%

“…Several works in the literature used only chemical synaptic currents in the investigation of the synchronization behavior of networks [2,[7][8][9][10]. In the wok by Kudela et al [2], a conductance-based model was used to study the networks of synaptically connected neurons generating action potentials.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, magnetoencephalography (MEG), a functional neuroimaging technique, is used for mapping brain activity. The signals measured in EEG and MEG can be decomposed into distinct frequency bands such as 1-3 Hz (delta), 4-7 Hz (theta), [8][9][10][11][12][13][14][15] Hz (alpha), 16-31 Hz (beta), and 32-70 Hz (gamma). There is a correlation between these rhythms and behaviors [3].…”

Section: Introductionmentioning

confidence: 99%

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Modeling of time delay-induced multiple synchronization behavior of interneuronal networks with the Izhikevich neuron model

Cakir¹

2017

Turk J Elec Eng & Comp Sci

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Abstract:The synchronization behavior of the networks of fast-spiking interneurons is investigated by using one of the phenomenological neural network models, the Izhikevich model. Since electrical and chemical synapses exist within the same networks of inhibitory cells, delayed inhibitory and fast electrical synapses are coupled in the simulations. The effects of hybrid synapses in promoting synchronous activity in neural networks are investigated with short and long time delays. The distinct frequency bands observed in electroencephalography and magnetoencephalography signals are determined using the raster plots of neural networks. For quantitative comparison of activities in networks, the degree of synchrony in the network is calculated. The influences of several network parameters such as inhibitory synaptic strength, electrical synaptic strength, synaptic time constant, and time delay on the network activity are investigated.It is observed that the coupling of electrical and chemical synapses promotes multiple synchronous behaviors in the network. Another important finding is that even though the synchronization measure is highly dependent on inhibitory synaptic strengths at low electrical synaptic strength and synaptic time constant, not much dependence on inhibitory synaptic strengths is observed at high electrical synaptic strength.

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Bifurcations and enhancement of neuronal firing induced by negative feedback

Zhao

Jia

2016

Nonlinear Dyn

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The influence of single neuron dynamics and network topology on time delay-induced multiple synchronous behaviors in inhibitory coupled network

Cited by 34 publications

References 76 publications

Different dynamical behaviors induced by slow excitatory feedback for type II and III excitabilities

Different dynamical behaviors induced by slow excitatory feedback for type II and III excitabilities

Modeling of time delay-induced multiple synchronization behavior of interneuronal networks with the Izhikevich neuron model

Bifurcations and enhancement of neuronal firing induced by negative feedback

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