Desynchronization in diluted neural networks
Abstract
The dynamical behaviour of a weakly diluted fully-inhibitory network of pulse-coupled spiking neurons is investigated. Upon increasing the coupling strength, a transition from regular to stochastic-like regime is observed. In the weak-coupling phase, a periodic dynamics is rapidly approached, with all neurons firing with the same rate and mutually phase-locked. The strong-coupling phase is characterized by an irregular pattern, even though the maximum Lyapunov exponent is negative. The paradox is solved by drawing an analogy with the phenomenon of ``stable chaos'', i.e. by observing that the stochastic-like behaviour is "limited" to a an exponentially long (with the system size) transient. Remarkably, the transient dynamics turns out to be stationary.
Cite
@article{arxiv.cond-mat/0603154,
title = {Desynchronization in diluted neural networks},
author = {R. Zillmer and R. Livi and A. Politi and A. Torcini},
journal= {arXiv preprint arXiv:cond-mat/0603154},
year = {2007}
}
Comments
11 pages, 13 figures, submitted to Phys. Rev. E