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arXiv · 1301.3779

Optimal system size for complex dynamics in random neural networks near criticality

Gilles Wainrib·Luis Carlos García del Molino
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Abstract

In this Letter, we consider a model of dynamical agents coupled through a random connectivity matrix, as introduced in [Sompolinsky et. al, 1988] in the context of random neural networks. It is known that increasing the disorder parameter induces a phase transition leading to chaotic dynamics. We observe and investigate here a novel phenomenon in the subcritical regime : the probability of observing complex dynamics is maximal for an intermediate system size when the disorder is close enough to criticality. We give a more general explanation of this type of system size resonance in the framework of extreme values theory for eigenvalues of random matrices.

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Gilles Wainrib, Luis Carlos García del Molino. 2013-01-16. Optimal system size for complex dynamics in random neural networks near criticality. https://doi.org/10.1063/1.4841396

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