Optimal system size for complex dynamics in random neural networks near criticality.
Chaos
; 23(4): 043134, 2013 Dec.
Article
em En
| MEDLINE
| ID: mdl-24387573
ABSTRACT
In this article, we consider a model of dynamical agents coupled through a random connectivity matrix, as introduced by Sompolinsky et al. [Phys. Rev. Lett. 61(3), 259-262 (1988)] in the context of random neural networks. When system size is infinite, 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 sub-critical regime for finite size systems 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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Redes Neurais de Computação
/
Modelos Neurológicos
Tipo de estudo:
Clinical_trials
Idioma:
En
Ano de publicação:
2013
Tipo de documento:
Article