Synchronization in Phase-Coupled Kuramoto Oscillator Networks with Axonal Delay and Synaptic Plasticity
arXiv:1307.8398 · doi:10.1103/PhysRevE.89.032906
Abstract
We explore both analytically and numerically an ensemble of coupled phase-oscillators governed by a Kuramoto-type system of differential equations. However, we have included the effects of time-delay (due to finite signal-propagation speeds) and network plasticity (via dynamic coupling constants) inspired by the Hebbian learning rule in neuroscience. When time-delay and learning effects combine, novel synchronization phenomena are observed. We investigate the formation of spatio-temporal patterns in both one- and two-dimensional oscillator lattices with periodic boundary conditions and comment on the role of dimensionality.
9 pages, 8 figures
References in corpus (1)
Cited by in corpus (14)
- Multi-clusters in networks of adaptively coupled phase oscillators networks
- Birth and stabilization of phase clusters by multiplexing of adaptive networks
- Hierarchical frequency clusters in adaptive networks of phase oscillators
- Development of structural correlations and synchronization from adaptive rewiring in networks of Kuramoto oscillators
- Describing synchronization and topological excitations in arrays of magnetic spin torque oscillators through the Kuramoto model
- Solitary states in adaptive nonlocal oscillator networks
- Effect of repulsive links on frustration in attractively coupled networks
- Beta-rhythm oscillations and synchronization transition in network models of Izhikevich neurons: effect of topology and synaptic type
- Analytical prediction of specific spatiotemporal patterns in nonlinear oscillator networks with distance-dependent time delays
- Exotic states induced by co-evolving connection weights and phases in complex networks
- Effects of Synaptic and Myelin Plasticity on Learning in a Network of Kuramoto Phase Oscillators
- The stability of fixed points for a Kuramoto model with Hebbian interactions
- Phase synchronization of coupled bursting neurons and the generalized Kuramoto model
- Emergence of solitary and chimera states in adaptive pendulum networks under diverse learning rules