title: Stochastic cellular automata model of neural networks.
abstract: We propose a stochastic dynamical model of noisy neural networks with complex architectures and discuss activation of neural networks by a stimulus, pacemakers, and spontaneous activity. This model has a complex phase diagram with self-organized active neural states, hybrid phase transitions, and a rich array of behaviors. We show that if spontaneous activity (noise) reaches a threshold level then global neural oscillations emerge. Stochastic resonance is a precursor of this dynamical phase transition. These oscillations are an intrinsic property of even small groups of 50 neurons.
authors.affiliation: Departamento de Física da Universidade de Aveiro, I3N, 3810-193 Aveiro, Portugal.
authors.forename: A V
authors.initials: AV
authors.lastname: Goltsev
authors.forename: F V
authors.initials: FV
authors.lastname: de Abreu
authors.forename: S N
authors.initials: SN
authors.lastname: Dorogovtsev
authors.forename: J F F
authors.initials: JF
authors.lastname: Mendes
mesh_terms: D000818:Animals; D001703:Biophysics / Q000379:methods*; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net; D009474:Neurons / Q000378:metabolism / Q000502:physiology*; D009991:Oscillometry / Q000379:methods*; D011336:Probability; D051381:Rats; D013269:Stochastic Processes; D013569:Synapses / Q000378:metabolism; D013816:Thermodynamics