Properties of spontaneously formed clusters of synchronous dynamics in a structureless network of noisy excitable neurons connected via delayed diffusive couplings are studied in detail. Several tools have been applied to characterize the synchronization clusters and to study their dependence on the neuronal and the synaptic parameters. Qualitative explanation of the cluster formation is discussed. The interplay between the noise, the interaction time-delay and the excitable character of the neuronal dynamics is shown to be necessary and sufficient for the occurrence of the synchronization clusters. We have found the two-cluster partitions where neurons are firmly bound to their subsets, as well as the three-cluster ones, which are dynamical by nature. The former turn out to be stable under small disparity of the intrinsic neuronal parameters and the heterogeneity in the synaptic connectivity patterns.
TY - JOUR
AU - Franović, Igor
AU - Todorović, Kristina
AU - Vasović, Nebojša
AU - Burić, Nikola
PY - 2012
UR - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1647
AB - Properties of spontaneously formed clusters of synchronous dynamics in a structureless network of noisy excitable neurons connected via delayed diffusive couplings are studied in detail. Several tools have been applied to characterize the synchronization clusters and to study their dependence on the neuronal and the synaptic parameters. Qualitative explanation of the cluster formation is discussed. The interplay between the noise, the interaction time-delay and the excitable character of the neuronal dynamics is shown to be necessary and sufficient for the occurrence of the synchronization clusters. We have found the two-cluster partitions where neurons are firmly bound to their subsets, as well as the three-cluster ones, which are dynamical by nature. The former turn out to be stable under small disparity of the intrinsic neuronal parameters and the heterogeneity in the synaptic connectivity patterns.
PB - Amer Inst Physics, Melville
T2 - Chaos
T1 - Cluster synchronization of spiking induced by noise and interaction delays in homogenous neuronal ensembles
VL - 22
IS - 3
DO - 10.1063/1.4753919
ER -
@article{
author = "Franović, Igor and Todorović, Kristina and Vasović, Nebojša and Burić, Nikola",
year = "2012",
abstract = "Properties of spontaneously formed clusters of synchronous dynamics in a structureless network of noisy excitable neurons connected via delayed diffusive couplings are studied in detail. Several tools have been applied to characterize the synchronization clusters and to study their dependence on the neuronal and the synaptic parameters. Qualitative explanation of the cluster formation is discussed. The interplay between the noise, the interaction time-delay and the excitable character of the neuronal dynamics is shown to be necessary and sufficient for the occurrence of the synchronization clusters. We have found the two-cluster partitions where neurons are firmly bound to their subsets, as well as the three-cluster ones, which are dynamical by nature. The former turn out to be stable under small disparity of the intrinsic neuronal parameters and the heterogeneity in the synaptic connectivity patterns.",
publisher = "Amer Inst Physics, Melville",
journal = "Chaos",
title = "Cluster synchronization of spiking induced by noise and interaction delays in homogenous neuronal ensembles",
volume = "22",
number = "3",
doi = "10.1063/1.4753919"
}
Franović, I., Todorović, K., Vasović, N.,& Burić, N.. (2012). Cluster synchronization of spiking induced by noise and interaction delays in homogenous neuronal ensembles. in Chaos
Amer Inst Physics, Melville., 22(3).
https://doi.org/10.1063/1.4753919
Franović I, Todorović K, Vasović N, Burić N. Cluster synchronization of spiking induced by noise and interaction delays in homogenous neuronal ensembles. in Chaos. 2012;22(3).
doi:10.1063/1.4753919 .
Franović, Igor, Todorović, Kristina, Vasović, Nebojša, Burić, Nikola, "Cluster synchronization of spiking induced by noise and interaction delays in homogenous neuronal ensembles" in Chaos, 22, no. 3 (2012),
https://doi.org/10.1063/1.4753919 . .
