arXiv subjects

T. Pereira

Publications and source records attributed to T. Pereira.

9 recordsLinked to original sources

arXiv2010

Global synchronization of bursting neurons in clustered networks

We investigate the collective dynamics of bursting neurons on clustered network. The clustered network is composed of subnetworks each presenting a small-world property, and in a given subnetwork each neuron has a probability to be connected to the other subnetworks. We give bounds for the critical coupling strength to obtain global burst synchronization in terms of the network structure, i.e., intracluster and intercluster probabilities connections. As the heterogeneity in the network is reduced the network global synchronization is improved. We show that the transitions to global synchrony may be abrupt or smooth depending on the intercluster probability.

nlin.CD↗

arXiv2008

Network Mutual Information and Synchronization under Time Transformations

We investigate the effect of general time transformations on the phase synchronization (PS) phenomenon and the mutual information rate (MIR) between pairs of nodes in dynamical networks. We demonstrate two important results concerning the invariance of both PS and the MIR. Under time transformations PS can neither be introduced nor destroyed and the MIR cannot be raised from zero. On the other hand, for proper time transformations the timing between the cycles of the coupled oscillators can be largely improved. Finally, we discuss the relevance of our findings for communication in dynamical networks.

cond-mat.stat-mech↗

arXiv2007

Inferior Bounds for Phase Synchronization

An approach is presented for coupled chaotic systems, estimating an inferior bound value for the absolute phase difference, in order to say that phase synchronization is present. This approach shows that synchronicity in phase implies synchronicity in the time of events. This is used to derive an equation to detect phase synchronization, based on the absolute difference between the time of these events. A phase based on the vector field is also introduced. It can be used to calculate the frequency of attractors with non-coherent phase dynamics.

physics.class-ph↗

arXiv2007

Non-transitive maps in phase synchronization

Concepts from the Ergodic Theory are used to describe the existence of non-transitive maps in attractors of phase synchronous chaotic systems. It is shown that for a class of phase-coherent systems, e.g. the sinusoidally forced Chua's circuit and two coupled R{ö}ssler oscillators, phase synchronization implies that such maps exist. These ideas are also extended to other coupled chaotic systems. In addition, a phase for a chaotic attractor is defined from the tangent vector of the flow. Finally, it is discussed how these maps can be used to real time detection of phase synchronization in experimental systems.

physics.class-ph↗

arXiv2007

Global Bifurcation Destroying The Experimental Torus T2

We show experimentally the scenario of a two-frequency torus $T^2$ breakdown, in which a global bifurcation occurs due to the collision of a torus with an unstable periodic orbit, creating a heteroclinic saddle connection, followed by an intermittent behavior.

nlin.CD↗

arXiv2007

General Framework for phase synchronization through localized sets

We present an approach which enables to identify phase synchronization in coupled chaotic oscillators without having to explicitly measure the phase. We show that if one defines a typical event in one oscillator and then observes another one whenever this event occurs, these observations give rise to a localized set. Our result provides a general and easy way to identify PS, which can also be used to oscillators that possess multiple time scales. We illustrate our approach in networks of chemically coupled neurons. We show that clusters of phase synchronous neurons may emerge before the onset of phase synchronization in the whole network, producing a suitable environment for information exchanging. Furthermore, we show the relation between the localized sets and the amount of information that coupled chaotic oscillator can exchange.

cond-mat.stat-mech↗

arXiv2007

Onset of Phase Synchronization in Neurons Conneted via Chemical Synapses

We study the onset of synchronous states in realistic chaotic neurons coupled by mutually inhibitory chemical synapses. For the realistic parameters, namely the synaptic strength and the intrinsic current, this synapse introduces non-coherences in the neuronal dynamics, yet allowing for chaotic phase synchronization in a large range of parameters. As we increase the synaptic strength, the neurons undergo to a periodic state, and no chaotic complete synchronization is found.

cond-mat.stat-mech↗

arXiv2007

Detecting phase synchronization by localized maps: Application to neural networks

We present an approach which enables to state about the existence of phase synchronization in coupled chaotic oscillators without having to measure the phase. This is done by observing the oscillators at special times, and analyzing whether this set of points is localized. In particular, we show that this approach is fruitful to analyze the onset of phase synchronization in chaotic attractors whose phases are not well defined, as well as, in networks of non-identical spiking/bursting neurons connected by chemical synapses.

cond-mat.stat-mech↗

arXiv2005

Phase Synchronization and invariant measures in sinusoidally perturbed chaotic systems

We show that, in periodically perturbed chaotic systems, Phase Synchronization appears, associated to a special type of stroboscopic map, in which not only averages quantities are equal to invariants of the perturbation, the angular frequency, but also it exists a very large number of non-transient transformations, possibly infinity. In cases where there is not phase synchronization there is either only transitive transformations on the attractor, or a finite number of non-transitive transformations. We base our statements in experimental and numerical results from the sinusoidally perturbed Chua's circuit.

cond-mat.stat-mech↗