Synchronizations in small-world networks of spiking neurons: Diffusive versus sigmoid couplings
arXiv:cond-mat/0505543 · doi:10.1103/PhysRevE.72.056139
Abstract
By using a semi-analytical dynamical mean-field approximation previously proposed by the author [H. Hasegawa, Phys. Rev. E, {\bf 70}, 066107 (2004)], we have studied the synchronization of stochastic, small-world (SW) networks of FitzHugh-Nagumo neurons with diffusive couplings. The difference and similarity between results for {\it diffusive} and {\it sigmoid} couplings have been discussed. It has been shown that with introducing the weak heterogeneity to regular networks, the synchronization may be slightly increased for diffusive couplings, while it is decreased for sigmoid couplings. This increase in the synchronization for diffusive couplings is shown to be due to their local, negative feedback contributions, but not due to the shorten average distance in SW networks. Synchronization of SW networks depends not only on their structure but also on the type of couplings.
arXiv comment17 pages, 8 figures, accepted in Phys. Rev. E with some changes
References in corpus (14)
- Statistical mechanics of complex networks
- Evolution of networks
- Synchronization in small-world systems
- Renormalization group analysis of the small-world network model
- Heterogeneity in oscillator networks: Are smaller worlds easier to synchronize?
- Fast Response and Temporal Coding on Coherent Oscillations in Small-World Networks
- Network Synchronization, Diffusion, and the Paradox of Heterogeneity
- Synchronization on small-world networks
- Enhancing complex-network synchronization
- Global and local synchrony of coupled neurons in small-world networks
- Dynamical mean-field theory of spiking neuron ensembles: response to a single spike with independent noises
- Dynamical mean-field theory of noisy spiking neuron ensembles: Application to the Hodgkin-Huxley model
- Dynamical mean-filed approximation to small-world networks of spiking neurons: From local to global, and/or from regular to random couplings
- Phase ordering on small-world networks with nearest-neighbor edges
Cited by in corpus (5)
- Maximum Performance at Minimum Cost in Network Synchronization
- A view of Neural Networks as dynamical systems
- Mean field approximation of two coupled populations of excitable units
- Generalized Rate-Code Model for Neuron Ensembles with Finite Populations
- Stationary and dynamical properties of finite -unit Langevin models subjected to multiplicative noises