We conceive a new recurrence quantifier for time series based on the concept of information entropy, in which probabilities are associated with presence microstates defined matrix as small binary submatrices. The methodology to compute entropy has advantages compared traditional entropies literature, namely, good correlation maximum Lyapunov exponent system and weak dependence vicinity threshold parameter. Furthermore, method works adequately even segments data, bringing consistent results...

Abstract Sleep plays a crucial role in the regulation of body homeostasis and rhythmicity mammals. Recently, specific component sleep structure has been proposed as part its homeostatic mechanism, named micro-arousal. Here, we studied unique progression dynamic behavior cortical hippocampal local field potentials (LFPs) during slow-wave sleep-related to motor-bursts (micro-arousals) mice. Our main results comprised: (i) an abrupt drop LFP amplitude preceding micro-arousals which persisted...

We considered a clustered network of bursting neurons described by the Huber-Braun model. In upper level we used connectivity matrix cat cerebral cortex network, and in lower each area (or cluster) is modelled as small-world network. There are two different coupling strengths related to inter- intracluster dynamics. Each cycle composed quiescent period followed rapid chaotic sequence spikes, defined geometric phase which enables us investigate onset synchronized bursting, state neuron start...

Anomalous phase synchronization describes a phenomenon occurring even for the weakly coupled network and characterized by non-monotonous dependence of strength on coupling strength. Its existence may support theoretical framework to some neurological diseases, such as Parkinson’s episodes seizure behavior generated epilepsy. Despite success controlling or suppressing anomalous in neural networks applying external perturbations inducing ambient changes, origin well mechanisms behind...

The recurrence analysis of dynamic systems has been studied since Poincaré's seminal work. Since then, several approaches have developed to study properties in nonlinear dynamical systems. In this work, we the recently entropy microstates. We propose a new quantifier, maximum (Smax). concept uses diversity microstates plot and is able set automatically optimum neighborhood (ϵ-vicinity), turning free vicinity parameter. addition, ϵ turns out be novel quantifier itself. apply Smax...

Abstract Extracting relevant properties of empirical signals generated by nonlinear, stochastic, and high-dimensional systems is a challenge complex research. Open questions are how to differentiate chaotic from stochastic ones, quantify nonlinear and/or high-order temporal correlations. Here we propose new technique reliably address both problems. Our approach follows two steps: first, train an artificial neural network (ANN) with flicker (colored) noise predict the value parameter,...

Recurrence analysis and its quantifiers are strongly dependent on the evaluation of vicinity threshold parameter, i.e., to regard two points close enough in phase space be considered as just one. We develop a new way optimize order assure higher level sensitivity recurrence allow detection even small changes dynamics. It is used promote tool detect nonstationary behavior time signals or profiles. show that ability provides information about present status physical process responsible...

Electroencephalogram (EEG) data is often analyzed from a Brain Complexity (BC) perspective, having successfully been applied to study the brain in both health and disease. In this study, we employed recurrence entropy quantify BC associated with neurophysiology of movement by comparing resting state cycling movement. We measured EEG 24 healthy adults, placed electrodes on occipital, parietal, temporal frontal sites, right left sides. measurements were performed for states eyes closed open....

Arousals can be roughly characterized by punctual intrusions of wakefulness into sleep. In a standard perspective, using human electroencephalography (EEG) data, arousals are associated to slow-wave rhythms and K-complex brain activity. The physiological mechanisms that give rise during sleep not yet fully understood. Moreover, subtle body movement patterns, which may characterize both in animals, usually detectable eye perception general present studies. this paper, we focus attention on...

Here we investigate the mechanism for explosive synchronization (ES) of a complex neural network composed nonidentical neurons and coupled by Newman-Watts small-world matrices. We find range nonlocal connection probabilities which displays an abrupt transition to phase synchronization, characterizing ES. The behind ES is following: As coupling parameter varied in distinct neurons, likely occur due bistable regime, namely chaotic nonsynchronized regular phase-synchronized state space. In this...

We investigate the role of bistability in synchronization a network identical bursting neurons coupled through an generic electrical mean-field scheme. These can exhibit distinct multistable states and, particular, bistable behavior is observed when their sodium conductance varied. With this, we consider three different initialization compositions: (i) whole same periodic state; (ii) half periodic, chaotic; (iii) and state. show that reach phase (PS) for all coupling strengths, while small...

We study the stability of asymptotic states displayed by a complex neural network. focus on loss stationary state networks using recurrence quantifiers as tools to diagnose local and global stabilities well multistability coupled Numerical simulations network composed 1024 neurons in small-world connection scheme are performed model Braun et al. [Int. J. Bifurcation Chaos 08, 881 (1998)], which is modified from Hodgkin-Huxley [J. Phys. 117, 500 (1952)]. To validate analyses, results compared...

It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the also diminish occurring in weakly coupled network topology. We consider a of 2000 thermally sensitive identical neurons, based on model Hodgkin–Huxley topology, with probability adding non local connection equal p=0.001. Based experimental protocols synchronization, as well dynamics, make use (i)...

Efficient diagnostics of breast cancer requires fast digital mammographic image processing. Many lesions, both benign and malignant, are barely visible to the untrained eye accurate reliable methods We propose a new method analysis that meets needs. It uses concept spatial recurrence as basis quantification analysis, which is extension well-known time analysis. The recurrence-based quantifiers able evidence lesions in way good best standard processing available, but with better control over...

We study the dynamical proprieties of phase synchronization and intermittent behavior neural systems using a network networks structure based on an experimentally obtained human connectome for healthy Alzheimer-affected brains. consider composed 78 subareas (subnetworks) coupled with mean-field potential scheme. Each subnetwork is characterized by small-world topology, 250 bursting neurons simulated through Rulkov model. Using Kuramoto order parameter we demonstrate that brains display...

In this paper we study how hyperbolic and nonhyperbolic regions in the neighborhood of a resonant island perform an important role allowing or forbidding stickiness phenomenon around islands conservative systems. The vicinity is composed areas that almost prevent trajectory to visit edge. For some specific parameters tiny channels are embedded area associated fixed points localized islands. Such allow be injected inner portion vicinity. When crosses barrier imposed by regions, it spends long...

The connection architecture plays an important role in the synchronization of networks, where presence local and nonlocal structures are found many systems, such as neural ones. Here, we consider a network composed chaotic bursting oscillators coupled through Watts-Strogatz-small-world topology. influence coupling strength rewiring connections is studied when topology varied from regular to small-world random. In this scenario, show two distinct nonstationary transitions phase...

Abstract A fundamental question of data analysis is how to distinguish noise corrupted deterministic chaotic dynamics from time-(un)correlated stochastic fluctuations when just short length available. Despite its importance, direct tests chaos vs stochasticity in finite time series still lack a definitive quantification. Here we present novel approach based on recurrence analysis, nonlinear deal with data. The main idea the identification microstates and permutation patterns are affected by...

The transition to phase synchronized states of neural networks with bursting dynamics may have nonstationary characteristics, as well sensitivity initial conditions. Here, we analyze the paradigmatic network composed neurons Rulkov investigate dynamic properties transitions synchronization displayed by under two different topologies connection matrices, namely, small-world and random ones. Our analyses both architectures reveal that topology display higher sensibility conditions, contrarily...