The role of coupling and external current in two coupled Hodgkin–Huxley neurons

This research studies the properties of two coupled Hodgkin-Huxley neurons. The influence of coupling strength as well as individual parameters of the neurons (i.e., initial conditions and external current values) have been studied. A Pearson correlation coefficient is used to estimate the synchrony degree between the neurons. It was found that the two neurons can be synchronized fairly easily in different regimes based on the combination of parameters: for some cases, the neurons are synchronous in a self-oscillating regime, but for other combinations, a single-spike regime becomes prevalent. It was also discovered that the synchronization regime can be controlled both by the external current value of each neuron and the coupling strength value. The obtained results can be profitable for future research of complex networks of artificial neurons.

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Publication Details

Journal
Chaos An Interdisciplinary Journal of Nonlinear Science
Published
2025-02-01
DOI
https://doi.org/10.1063/5.0243433
Citations
2
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
2.86
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article

The role of coupling and external current in two coupled Hodgkin–Huxley neurons

Galina I. Strelkova, Tatiana R. Bogatenko, Konstantin Sergeev
2 citations
Chaos An Interdisciplinary Journal of Nonlinear Science
Neural dynamics and brain function
2.86
article

The role of coupling and external current in two coupled Hodgkin–Huxley neurons

Galina I. Strelkova, Tatiana R. Bogatenko, Konstantin Sergeev
article en
2 citations

Abstract

This research studies the properties of two coupled Hodgkin-Huxley neurons. The influence of coupling strength as well as individual parameters of the neurons (i.e., initial conditions and external current values) have been studied. A Pearson correlation coefficient is used to estimate the synchrony degree between the neurons. It was found that the two neurons can be synchronized fairly easily in different regimes based on the combination of parameters: for some cases, the neurons are synchronous in a self-oscillating regime, but for other combinations, a single-spike regime becomes prevalent. It was also discovered that the synchronization regime can be controlled both by the external current value of each neuron and the coupling strength value. The obtained results can be profitable for future research of complex networks of artificial neurons.

Chaos An Interdisciplinary Journal of Nonlinear ScienceVol. 35(2)
Saratov State University (RU)
Openalex Percentile: Top 12%
Neural dynamics and brain function
2.86
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