Instabilities in attractor networks with fast synaptic fluctuations and partial updating of the neurons activity

J J Torres; J Marro; J M Cortes; B Wemmenhove

doi:10.1016/j.neunet.2008.07.002

Instabilities in attractor networks with fast synaptic fluctuations and partial updating of the neurons activity

Neural Netw. 2008 Nov;21(9):1272-7. doi: 10.1016/j.neunet.2008.07.002. Epub 2008 Jul 25.

Authors

J J Torres¹, J Marro, J M Cortes, B Wemmenhove

Affiliation

¹ Institute "Carlos I" for Theoretical and Computational Physics, and Departamento de Electromagnetismo y Física de la Materia, Universidad de Granada, E-18071, Granada, Spain. jtorres@onsager.ugr.es

PMID: 18701255
DOI: 10.1016/j.neunet.2008.07.002

Abstract

We present and study a probabilistic neural automaton in which the fraction of simultaneously-updated neurons is a parameter, rhoin(0,1). For small rho, there is relaxation towards one of the attractors and a great sensibility to external stimuli and, for rho > or = rho(c), itinerancy among attractors. Tuning rho in this regime, oscillations may abruptly change from regular to chaotic and vice versa, which allows one to control the efficiency of the searching process. We argue on the similarity of the model behavior with recent observations, and on the possible role of chaos in neurobiology.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Algorithms
Humans
Models, Neurological*
Models, Statistical*
Neural Networks, Computer*
Neurons / physiology*
Nonlinear Dynamics*
Synapses / physiology*