https://doi.org/10.1140/epjs/s11734-023-00992-5
Regular Article
Coherence resonance modulated by hybrid synapses and time delay in modular small-world neuronal networks with E–I balanced state
1
School of Information Engineering, Pioneer College of Inner Mongolia University, Inner Mongolia, 010000, Hohhot, China
2
School of Science, Beijing University of Posts and Telecommunications, 100876, Beijing, China
Received:
12
February
2023
Accepted:
9
September
2023
Published online:
16
October
2023
Neurons communicate primarily through synapses. A neuron is usually affected by multiple synapses, which could be chemical/electrical or excitatory/inhibitory ones at the same time. Here, we make the realistic assumption that a excitatory and inhibitory balanced modular small-world network is established and focuses on the effects of hybrid chemical and electrical synapses, noise and time delay on coherence resonance of the constructed network. It is found that when the ratio f of chemical synapses to electrical synapses approaches odd ratios, coherence resonance is better than those f close to even ratios for appropriate noise intensities. Furthermore, with f increasing, it is observed that effects of chemical and electrical synapses on coherence resonance are nearly opposite. It indicates that electrical synapses are more efficient than chemical ones. Meanwhile, multiple coherence resonances are observed when time delay is introduced into the network, and it is independent of f. Finally, we demonstrate that coherence resonance decreases as the number of subnetworks increases, and when the number of subnetworks is larger, the resonance behaviour weakens or vanishes with increasing f.
Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
