16,507 research outputs found
System size stochastic resonance in a model for opinion formation
We study a model for opinion formation which incorporates three basic
ingredients for the evolution of the opinion held by an individual: imitation,
influence of fashion and randomness. We show that in the absence of fashion,
the model behaves as a bistable system with random jumps between the two stable
states with a distribution of times following Kramer's law. We also demonstrate
the existence of system size stochastic resonance, by which there is an optimal
value for the number of individuals N for which the average opinion follows
better the fashion.Comment: 10 pages, to appear in Physica
Selection of critical events in nuclear fragmentation
The calculation of the critical exponent Ï„ is crucial in the determination of critical phenomena in heavy ion reactions. This, however, is obscured by the unavoidable mixing of critical and noncritical events that results in nonclean signals. Here we report on a method to extract critical events from a set of mixed ones. In comparing to the traditional one, based on the so-called Campi plot, a distinct advantage is found.Fil: Dorso, Claudio Oscar. Consejo Nacional de Investigaciones CientÃficas y Técnicas; Argentina. Universidad de Buenos Aires; ArgentinaFil: Lopez, J. A.. University of Texas at El Paso; Estados Unido
The Surface Laplacian Technique in EEG: Theory and Methods
This paper reviews the method of surface Laplacian differentiation to study
EEG. We focus on topics that are helpful for a clear understanding of the
underlying concepts and its efficient implementation, which is especially
important for EEG researchers unfamiliar with the technique. The popular
methods of finite difference and splines are reviewed in detail. The former has
the advantage of simplicity and low computational cost, but its estimates are
prone to a variety of errors due to discretization. The latter eliminates all
issues related to discretization and incorporates a regularization mechanism to
reduce spatial noise, but at the cost of increasing mathematical and
computational complexity. These and several others issues deserving further
development are highlighted, some of which we address to the extent possible.
Here we develop a set of discrete approximations for Laplacian estimates at
peripheral electrodes and a possible solution to the problem of multiple-frame
regularization. We also provide the mathematical details of finite difference
approximations that are missing in the literature, and discuss the problem of
computational performance, which is particularly important in the context of
EEG splines where data sets can be very large. Along this line, the matrix
representation of the surface Laplacian operator is carefully discussed and
some figures are given illustrating the advantages of this approach. In the
final remarks, we briefly sketch a possible way to incorporate finite-size
electrodes into Laplacian estimates that could guide further developments.Comment: 43 pages, 8 figure
Synchronised firing induced by network dynamics in excitable systems
We study the collective dynamics of an ensemble of coupled identical
FitzHugh--Nagumo elements in their excitable regime. We show that collective
firing, where all the elements perform their individual firing cycle
synchronously, can be induced by random changes in the interaction pattern.
Specifically, on a sparse evolving network where, at any time, each element is
connected with at most one partner, collective firing occurs for intermediate
values of the rewiring frequency. Thus, network dynamics can replace noise and
connectivity in inducing this kind of self-organised behaviour in highly
disconnected systems which, otherwise, wouldn't allow for the spreading of
coherent evolution.Comment: 5 pages, 5 figure
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