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.

11 pages, 13 figures, submitted to Phys. Rev. E

References in corpus (4)

• Desynchronized stable states in diluted neural networks
• Desynchronization in diluted neural networks
• A new approach to partial synchronization in globally coupled rotators
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• Stability of the splay state in pulse--coupled networks
• The simplest problem in the collective dynamics of neural networks: Is synchrony stable?
• Spectral fluctuations of billiards with mixed dynamics: from time series to superstatistics
• Stability of splay states in globally coupled rotators
• Influence of synaptic interaction on firing synchronization and spike death in excitatory neuronal networks