Desynchronization in diluted neural networks

dc.creatorZillmer, R.
dc.creatorLivi, R.
dc.creatorPoliti, A.
dc.creatorTorcini, A.
dc.date2006-03-07
dc.date2006-06-15
dc.date.accessioned2026-07-07T07:02:11Z
dc.date.available2026-07-07T07:02:11Z
dc.descriptionThe 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.
dc.description11 pages, 13 figures, submitted to Phys. Rev. E
dc.identifierhttps://arxiv.org/abs/cond-mat/0603154
dc.identifierhttp://arxiv.org/abs/cond-mat/0603154
dc.identifierPhys. Rev. E 74 (2006) 036203
dc.identifierdoi:10.1103/PhysRevE.74.036203
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/108515
dc.subjectDisordered Systems and Neural Networks
dc.titleDesynchronization in diluted neural networks
dc.typetext

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