Parametrically Excited Chaotic Spike Sequences and Information Aspects in an Ensemble of FitzHugh–Nagumo Neurons

Shchapin, Dmitry; Nekorkin, Vladimir I.

doi:10.1134/s0021364021060114

Cited by 5 publications

(1 citation statement)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mathematical modelling has been a guide on this way for several decades. Using the models of coupled spiking neurons the researchers have studied such important effects as synchronization of neural populations [1][2][3][4][5][6], asynchronous states [7,8], periodic collective oscillations [9][10][11], microscopic chaos [12][13][14], collective irregular dynamics [15,16], working memory [17,18] and many others.…”

mentioning

confidence: 99%

Shot noise in next-generation neural mass models

Klinshov¹,

Kirillov²

2022

Preprint

View full text Add to dashboard Cite

Recently, the so-called next-generation neural mass models have received a lot of attention of the researchers in the field of mathematical neuroscience. The ability of these models to account for the degree of synchrony in neural populations proved useful in many contexts such as the modeling of brain rhythms, working memory and spatio-temporal patterns of activity. In the present Letter we study the effects of finite size on the collective behaviour of neural networks and show that they can be captured by appropriately modified neural mass models. Namely, the finite size of the network leads to the emergence of the shot noise appearing as a stochastic term in the neural mass model. We calculate the power spectrum of the shot noise and show that it might demonstrate pronounced peaks in the frequencies comparable to the mean firing rate. Although the shot noise is weak in large massively connected networks, its impact on the collective dynamics might be crucial due to resonance effects.

show abstract

mentioning

confidence: 99%

Shot noise in next-generation neural mass models

Klinshov¹,

Kirillov²

2022

Preprint

View full text Add to dashboard Cite

show abstract

Coexisting multiple firing behaviors of fractional-order memristor-coupled HR neuron considering synaptic crosstalk and its ARM-based implementation

Ding

Chen

Yang

et al. 2022

Chaos, Solitons & Fractals

View full text Add to dashboard Cite

Constructive role of shot noise in the collective dynamics of neural networks

Klinshov

Smelov

Kirillov

2023

Chaos: An Interdisciplinary Journal of Nonlinear Science

View full text Add to dashboard Cite

Finite-size effects may significantly influence the collective dynamics of large populations of neurons. Recently, we have shown that in globally coupled networks these effects can be interpreted as additional common noise term, the so-called shot noise, to the macroscopic dynamics unfolding in the thermodynamic limit. Here, we continue to explore the role of the shot noise in the collective dynamics of globally coupled neural networks. Namely, we study the noise-induced switching between different macroscopic regimes. We show that shot noise can turn attractors of the infinitely large network into metastable states whose lifetimes smoothly depend on the system parameters. A surprising effect is that the shot noise modifies the region where a certain macroscopic regime exists compared to the thermodynamic limit. This may be interpreted as a constructive role of the shot noise since a certain macroscopic state appears in a parameter region where it does not exist in an infinite network.

show abstract

Parametrically Excited Chaotic Spike Sequences and Information Aspects in an Ensemble of FitzHugh–Nagumo Neurons

Cited by 5 publications

References 19 publications

Shot noise in next-generation neural mass models

Shot noise in next-generation neural mass models

Coexisting multiple firing behaviors of fractional-order memristor-coupled HR neuron considering synaptic crosstalk and its ARM-based implementation

Constructive role of shot noise in the collective dynamics of neural networks

Contact Info

Product

Resources

About