2016/09/19 by Ajay Deep Kachhvah · 8 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Constant (computer programming) #Coupling (piping) #Distribution (mathematics) #Generality #Neural Networks Stability and Synchronization #Nonlinear Dynamics and Pattern Formation #Synchronization (alternating current) #Synchronization networks #Topology (electrical circuits) #Transition (genetics) #nlin.AO #physics.comp-ph #q-bio.NC #stochastic dynamics and bifurcation
paper · pdf · doi:10.1140/epjb/e2016-70572-9
published in The European Physical Journal B 90(1) (Springer Science+Business Media) · 10 pages, 9 figures
arxiv created 2016/09/19 · openalex publication_date 2017/01/01 · openalex created_date 2019/06/27 · arxiv updated 2019/12/23 · openalex updated_date 2026/08/05
Here we investigate the synchronization of networks of FitzHugh-Nagumo neurons coupled in scale-free, small-world and random topologies, in the presence of distributed time delays in the coupling of neurons. We explore how the synchronization transition is affected when the time delays in the interactions between pairs of interacting neurons are non-uniform. We find that the presence of distributed time-delays does not change the behavior of the synchronization transition significantly, vis-a-vis networks with constant time-delay, where the value of the constant time-delay is the mean of the distributed delays. We also notice that a normal distribution of delays gives rise to a transition at marginally lower coupling strengths, vis-a-vis uniformly distributed delays. These trends hold across classes of networks and for varying standard deviations of the delay distribution, indicating the generality of these results. So we conclude that distributed delays, which may be typically expected in real-world situations, do not have a notable effect on synchronization. This allows results obtained with constant delays to remain relevant even in the case of randomly distributed delays.