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 τ 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 Científicas 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