Examinando por Autor "Used, Javier"

Mostrando 1 - 6 de 6

A stochastic hybrid model with a fast concentration bias for chemotactic cellular attraction
(Elsevier, 2022-01) Ojer, Jaume; García López, Álvaro; Used, Javier; Fernández Sanjuán, Miguel Ángel
We reproduce the phenomenon of chemotaxis through a hybrid random walk model in two dimensions on a lattice. The dynamics of the chemoattractant is modelled using a partial differential equation, which reproduces its diffusion through the environment from its local sources. The cell is treated discretely and it is considered immersed in a medium with concentration gradients, so that its path is affected by these chemical anisotropies. Therefore, the direction taken in each iteration of the walk is given by a stochastic process that must be biased by the chemical concentrations, giving preference towards the highest values. For this purpose, we model the intensity of the bias by a single parameter, which is related to how much a cell is attracted to a source and, consequently, how efficient this source is with respect to the cellular capture. Since the model is intended for later hybridization with cellular automata models, a thorough quantitative analysis of the parameter space has been carried out. Finally, we also illustrate the efficiency of the cellular capture due to the concentration sources by using stochastic basins of attraction.
Fourier analysis of a delayed Rulkov neuron network
(Elsevier, 2019) Lozano, Roberto; Used, Javier; Fernández Sanjuán, Miguel Ángel
We have analyzed the synchronization of some different networks of chaotic Rulkov neu- rons with an electrical coupling that contains a delay. We have developed an algorithm to compute a certain delay whose result is to improve the synchronization of the net- work when it was slightly synchronized, or to get synchronized when it was desynchro- nized. Our general approach has been to use tools from signal analysis, such as Fourier and wavelet transforms. With these tools, we have characterized the behavior of the neurons for different parameters in frequency and time-frequency domains. The algorithm has been applied for two well-known network models: the small-world and Erdös-Rényi. We have also tested the algorithm by using non-homogeneous neurons affected with a parametric noise.
Noise-induced complex dynamics and synchronization in the map-based Chialvo neuron model
(Elsevier, 2023-01) Bashkirtseva, Irina; Ryashko, Lev; Used, Javier; Seoane, Jesús M.; Fernández Sanjuán, Miguel Ángel
The paper considers a stochastic version of the conceptual map-based Chialvo model of neural activity. Firstly, we focus on the parametric zone where this model exhibits monoand bistability with coexistence of equilibria and oscillatory spiking attractors forming closed invariant curves. Stochastic effects of excitement and generation of bursting are studied both numerically and analytically by confidence ellipses. A phenomenon of the noise-induced transition to chaos in a localized two-parametric zone is discussed. Besides, we also study the phenomenon of synchronization between neurons by using a two-neuron network with a small coupling. In this scenario, we have found critical values of noise for which we obtain a good performance for the synchronization between the neurons of the network.
Optimal distributions for multiplex logistic networks
(AIP Publishing, 2016-06-16) Solá, Luis E.; Used, Javier; Romance, Miguel
This paper presents some mathematical models for distribution of goods in logistic networks based on spectral analysis of complex networks. Given a steady distribution of a finished product, some numerical algorithms are presented for computing the weights in a multiplex logistic network that reach the equilibrium dynamics with high convergence rate. As an application, the logistic networks of Germany and Spain are analyzed in terms of their convergence rates.
Reducing the number of time delays in coupled dynamical systems
(Springer, 2018) Wagemakers, Alexandre; Used, Javier; Fernández Sanjuán, Miguel Ángel
Vibrational resonance in biological nonlinear maps
(Springer, 2012-08) Rajasekar, S.; Used, Javier; Wagemakers, Alexandre; Sanjuán, Miguel A.F.
We investigate vibrational resonance in two different nonlinear maps driven by a biharmonic force: the Bellows and the Rulkov map. These two maps possess dynamical features of particular interest for the study of these phenomena. In both maps, the resonance occurs at the low-frequency of the biharmonic signal as the amplitude of the high-frequency signal is varied. We also consider an array of unidirectionally coupled maps with the forcing signal applied to the first unit. In this case, a signal propagation with several interesting features above a critical value of the coupling strength is found, while the response amplitude of the ith unit is greater than the first one. This response evolves in a sigmoidal fashion with the system number i, meaning that at some point the amplitudes saturate. The unidirectional coupling acts as a low-pass filter for distant units. Moreover, the analysis of the mean residence time of the trajectory in a given region of the phase space unveils a multiresonance mechanism in the coupled map system. These results point at the relevance of the discrete-time models for the study of resonance phenomena, since analyses and simulations are much easier than for continuous-time models