Effects of autapse and ion channel block on the collective firing activity of Newman–Watts small-world neuronal networks

Uzun, Rukiye; Yılmaz, Ergin; Özer, Mahmut

doi:10.1016/j.physa.2017.05.049

Cited by 24 publications

(6 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[36] Excitatory autapses cause persistent firing in the motor neurons of buccal ganglia [34] and enhance burst firing in neocortical pyramidal neurons. [31] In addition, researchers have presented more roles for autapses in modulating the activities of single neurons and neuronal networks such as firing patterns, [18,38,39] resonances, [40][41][42] and synchronizations [43,44] in theoretical studies. [45][46][47] For example, the switches between class-1 and 2 excitabilities can be induced by inhibitory and excitatory autapses.…”

Section: Introductionmentioning

confidence: 99%

Negative self-feedback induced enhancement and transition of spiking activity for class-3 excitability

Zhao

2022

Chinese Phys. B

View full text Add to dashboard Cite

Post-inhibitory rebound (PIR) spike, which has been widely observed in diverse nervous systems with different physiological functions and simulated in theoretical models with class 2 excitability, presents a counterintuitive nonlinear phenomenon in that the inhibitory effect can facilitate neural firing behavior. In this study, a PIR spike induced by inhibitory stimulation from the resting state corresponding to class 3 excitability that is not related to bifurcation is simulated in the Morris-Lecar neuron. Additionally, the inhibitory self-feedback mediated by an autapse with time delay can evoke tonic/repetitive spiking from phasic/transient spiking. The dynamical mechanism for the PIR spike and the tonic/repetitive spiking is acquired with the phase plane analysis and the shape of the quasi-separatrix curve. The result extends the counterintuitive phenomenon induced by inhibition to class 3 excitability, which presents a potential function of inhibitory autapse and class 3 neuron in many neuronal systems such as the auditory system.

show abstract

Section: Introductionmentioning

confidence: 99%

Negative self-feedback induced enhancement and transition of spiking activity for class-3 excitability

Zhao

2022

Chinese Phys. B

View full text Add to dashboard Cite

show abstract

“…Neurons communicate mainly by two modalities of synaptic transmission, that is, chemical and electrical synapses (Pereda, 2014 ; Alcamí and Pereda, 2019 ), as well as by other means of communication, such as autaptic connections (Bacci and Huguenard, 2006 ) or presumably via magnetic fields (Guo S. et al, 2017 ; Ma and Tang, 2017 ). In a plethora of previous theoretical and experimental studies, it has been studied how the interplay between electrical and chemical coupling (Yilmaz et al, 2013 ; Yu et al, 2020 ), autapses (Wang et al, 2014 ; Uzun et al, 2017 ), and electromagnetic induction (Jia et al, 2019 ) affect the collective neuronal dynamics, including the coherence resonance (Balenzuela and García-Ojalvo, 2005 ; Yilmaz et al, 2016 ; Liu and Yang, 2018 ; Jia et al, 2021 ). Moreover, in recent years the research interest is shifting toward neuronal networks composed of two populations, one excitatory and the other inhibitory.…”

Section: Introductionmentioning

confidence: 99%

Interlayer Connectivity Affects the Coherence Resonance and Population Activity Patterns in Two-Layered Networks of Excitatory and Inhibitory Neurons

Ristič

Gosak

2022

Front. Comput. Neurosci.

View full text Add to dashboard Cite

The firing patterns of neuronal populations often exhibit emergent collective oscillations, which can display substantial regularity even though the dynamics of individual elements is very stochastic. One of the many phenomena that is often studied in this context is coherence resonance, where additional noise leads to improved regularity of spiking activity in neurons. In this work, we investigate how the coherence resonance phenomenon manifests itself in populations of excitatory and inhibitory neurons. In our simulations, we use the coupled FitzHugh-Nagumo oscillators in the excitable regime and in the presence of neuronal noise. Formally, our model is based on the concept of a two-layered network, where one layer contains inhibitory neurons, the other excitatory neurons, and the interlayer connections represent heterotypic interactions. The neuronal activity is simulated in realistic coupling schemes in which neurons within each layer are connected with undirected connections, whereas neurons of different types are connected with directed interlayer connections. In this setting, we investigate how different neurophysiological determinants affect the coherence resonance. Specifically, we focus on the proportion of inhibitory neurons, the proportion of excitatory interlayer axons, and the architecture of interlayer connections between inhibitory and excitatory neurons. Our results reveal that the regularity of simulated neural activity can be increased by a stronger damping of the excitatory layer. This can be accomplished with a higher proportion of inhibitory neurons, a higher fraction of inhibitory interlayer axons, a stronger coupling between inhibitory axons, or by a heterogeneous configuration of interlayer connections. Our approach of modeling multilayered neuronal networks in combination with stochastic dynamics offers a novel perspective on how the neural architecture can affect neural information processing and provide possible applications in designing networks of artificial neural circuits to optimize their function via noise-induced phenomena.

show abstract

“…For example, formation of autapse [17,18] can enhance the self-adaption of neuron to external stimuli, and an auxiliary feedback loop [19] is formed to correct the blocked signal propagation along the injured axon. Local distribution of autapse in networks can induce continuous pulses and wave fronts for regulating the spatial behaviors, [20][21][22][23] and the activation of autapse in an isolated neuron [24][25][26][27] can enable appropriate mode selection in the electrical activities. For a complete review on collective behaviors of neural networks and physical mechanism in neurodynamics, readers can find possible suggestions about model setting, pattern formation, and synchronization stability in neuron and neural networks.…”

Section: Introductionmentioning

confidence: 99%

Dynamics and coherence resonance in a thermosensitive neuron driven by photocurrent*

Liu

Zhu

et al. 2020

Chinese Phys. B

View full text Add to dashboard Cite

A feasible neuron model can be effective to estimate the mode transition in neural activities in a complex electromagnetic environment. When neurons are exposed to electromagnetic field, the continuous magnetization and polarization can generate nonlinear effect on the exchange and propagation of ions in the cell, and then the firing patterns can be regulated completely. The conductivity of ion channels can be affected by the temperature and the channel current is adjusted for regulating the excitability of neurons. In this paper, a phototube and a thermistor are used to the functions of neural circuit. The phototube is used to capture external illumination for energy injection, and a continuous signal source is obtained. The thermistor is used to percept the changes of temperature, and the channel current is changed to adjust the excitability of neuron. This functional neural circuit can encode the external heat (temperature) and illumination excitation, and the dynamics of neural activities is investigated in detail. The photocurrent generated in the phototube can be used as a signal source for the neural circuit, and the thermistor is used to estimate the conduction dependence on the temperature for neurons under heat effect. Bifurcation analysis and Hamilton energy are calculated to explore the mode selection. It is found that complete dynamical properties of biological neurons can be reproduced in spiking, bursting, and chaotic firing when the phototube is activated as voltage source. The functional neural circuit mainly presents spiking states when the photocurrent is handled as a stable current source. Gaussian white noise is imposed to detect the occurrence of coherence resonance. This neural circuit can provide possible guidance for investigating dynamics of neural networks and potential application in designing sensitive sensors.

show abstract

Effects of autapse and ion channel block on the collective firing activity of Newman–Watts small-world neuronal networks

Cited by 24 publications

References 42 publications

Negative self-feedback induced enhancement and transition of spiking activity for class-3 excitability

Negative self-feedback induced enhancement and transition of spiking activity for class-3 excitability

Interlayer Connectivity Affects the Coherence Resonance and Population Activity Patterns in Two-Layered Networks of Excitatory and Inhibitory Neurons

Dynamics and coherence resonance in a thermosensitive neuron driven by photocurrent*

Contact Info

Product

Resources

About