dc.creatorWEI, W
dc.creatorPEREZ, G
dc.creatorCERDEIRA, HA
dc.date1993
dc.dateAPR
dc.date2014-12-16T11:32:09Z
dc.date2015-11-26T16:27:52Z
dc.date2014-12-16T11:32:09Z
dc.date2015-11-26T16:27:52Z
dc.date.accessioned2018-03-28T23:08:50Z
dc.date.available2018-03-28T23:08:50Z
dc.identifierPhysical Review E. American Physical Soc, v. 47, n. 4, n. 2893, n. 2898, 1993.
dc.identifier1063-651X
dc.identifierWOS:A1993KZ50700084
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/63565
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/63565
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/63565
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1269305
dc.descriptionThe time-interval sequences and the spatiotemporal patterns of the firings of a coupled neuronal network are investigated in this paper. For a single neuron stimulated by an external stimulus I, the time-interval sequences show a low-frequency firing of bursts of spikes and a reversed period-doubling cascade to a high-frequency repetitive firing state as the stimulus I is increased. For two neurons coupled to each other through the firing of the spikes, the complexity of the time-interval sequences becomes simple as the coupling strength increases. A network with a large number of neurons shows a complex spatiotemporal pattern structure. As the coupling strength increases, the number of phase-locked neurons increases and the time-interval diagram shows temporal chaos and a bifurcation in the space. The dynamical behavior is also verified by the behavior of the Lyapunov exponent.
dc.description47
dc.description4
dc.description2893
dc.description2898
dc.languageen
dc.publisherAmerican Physical Soc
dc.publisherCollege Pk
dc.publisherEUA
dc.relationPhysical Review E
dc.relationPhys. Rev. E
dc.rightsaberto
dc.sourceWeb of Science
dc.subjectVisual-cortex
dc.subjectModel
dc.subjectOscillations
dc.subjectSynchronization
dc.subjectEquations
dc.subjectChaos
dc.subjectCat
dc.titleDYNAMIC BEHAVIOR OF THE FIRINGS IN A COUPLED NEURONAL SYSTEM
dc.typeArtículos de revistas


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