Instabilities in Attractor Networks with Fast Synaptic Fluctuations and Partial Updating of the Neurons Activity

Simple item page
dc.creatorTorres, J. J.
dc.creatorMarro, J.
dc.creatorCortes, J. M.
dc.creatorWemmenhove, B.
dc.date2008-05-08
dc.date.accessioned2026-07-07T09:37:45Z
dc.date.available2026-07-07T09:37:45Z
dc.descriptionWe present and study a probabilistic neural automaton in which the fraction of simultaneously-updated neurons is a parameter, rho (0, 1) . For small rho, there is relaxation towards one of the attractors and a great sensibility to external stimuli and, for rho >= 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.
dc.description19 pages, 5 figures
dc.identifierhttps://arxiv.org/abs/0805.1210
dc.identifierhttp://arxiv.org/abs/0805.1210
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/160573
dc.subjectDisordered Systems and Neural Networks
dc.titleInstabilities in Attractor Networks with Fast Synaptic Fluctuations and Partial Updating of the Neurons Activity
dc.typetext

Files

Collections

arXiv