Fast regular firings induced by intra- and inter-time delays in two clustered neuronal networks

Autor(es)

Sun, Xiaojuan ^[1] ; Perc, Matjaz ^{[2, 3, 4]} ; Kurths, Juergen ^{[5, 6]} ; Lu, Qishao ^[7]

Afiliação do(s) autor(es)

^[1] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876 - Peoples R China

^[2] Univ Maribor, Fac Nat Sci & Math, Koroska Cesta 160, SI-2000 Maribor - Slovenia

^[3] Univ Maribor, CAMTP Ctr Appl Math & Theoret Phys, Mladinska 3, SI-2000 Maribor - Slovenia

^[4] Complex Sci Hub, Josefstadterstr 39, A-1080 Vienna - Austria

^[5] Potsdam Inst Climate Impact Res, D-14412 Potsdam - Germany

^[6] Humboldt Univ, Inst Phys, D-12489 Berlin - Germany

^[7] Beihang Univ, Dept Dynam & Control, Beijing 100083 - Peoples R China

• Tipo de documento: Artigo Científico
• Fonte: Chaos; v. 28, n. 10 OCT 2018.
• Citações Web of Science: 9

Resumo

In this paper, we consider two clustered neuronal networks with dense intra-synaptic links within each cluster and sparse inter-synaptic links between them. We focus on the effects of intra- and inter-time delays on the spiking regularity and timing in both clusters. With the aid of simulation results, we show that intermediate intra- and inter-time delays are able to separately induce fast regular firing-spiking activity with a high firing rate as well as a high spiking regularity. Moreover, when both intra- and inter-time delays are present, we find that fast regular firings are induced much more frequently than if only a single type of delay is present in the system. Our results indicate that appropriately adjusted intra- and inter-time delays can significantly facilitate fast regular firing in neuronal networks. Based on a detailed analysis, we conjecture that this is most likely when the largest value of common divisors of the intra- and inter-time delays falls into a range where fast regular firings are induced by suitable intra-or inter-time delays alone. Published by AIP Publishing. (AU)

• Processo FAPESP: 11/50151-0 - Fenômenos dinâmicos em redes complexas: fundamentos e aplicações
• Beneficiário: Elbert Einstein Nehrer Macau
• Modalidade de apoio: Auxílio à Pesquisa - Temático