Deterministic coherence resonance in coupled chaotic oscillators with frequency mismatch

A small mismatch between natural frequencies of unidirectionally coupled chaotic oscillators can induce coherence resonance in the slave oscillator for a certain coupling strength. This surprising phenomenon resembles “stabilization of chaos by chaos,” i.e., the chaotic driving applied to the chaotic system makes its dynamics more regular when the natural frequency of the slave oscillator is a little different than the natural frequency of the master oscillator. The coherence is characterized with the dominant component in the power spectrum of the slave oscillator, normalized standard deviations of both the peak amplitude and the interpeak interval, and Lyapunov exponents. The enhanced coherence is associated with increasing negative both the third and the fourth Lyapunov exponents, while the first and second exponents are always positive and zero, respectively

Deterministic coherence resonance in a ring of coupled chaotic oscillators

We study synchronization three unidirectionally Rössler oscillator the presence small mismatch between their natural frequencies w1< w2< w3. The forward (1 - 2 - 3 - 1) backward coupling directions are considered. As strength increases, common route to both configurations is intermittent phase imperfect perfect almost synchronization. difference scenario two only occurs couplings regime characterized with time-averaged dominant frequency power spectrum linear approximated slope dependent phases oscillators. Although more easily achieved configuration, results significant enhancement which within narrow range strengths as soon oscillators synchronize phases

A family of multimodal dynamic maps

"We introduce a family of multimodal logistic maps with a single parameter. The maps domain is partitioned in subdomains according to the maximal number of modals to be generated and each subdomain contains one logistic map. The number of members of a family is equal to the maximal number of modals. Bifurcation diagrams and basins of attraction of fixed points are constructed for the family of chaotic logistic maps.

Mathematical modeling of neuronal connexin-36 channels

Neurotransmission through electrical synapses play an important role in the spike synchrony among neurons and oscillation of neuron networks. Connexin36 (Cx36) is the principal gap junction protein of electrical synapses between inhibitory interneurons in vertebrates. Coupling strength between coupled neurons is modulated, among other factor, by the voltage difference between cell interiors, termed transjunctional voltage (Vj), in a complex manner; with the Vj gradient junctional conductance of Cx36 channels first increases instantaneously (+ 20% for + 100 mV) and then it decreases slowly to half for a similar range of Vj. The significance of this regulation by voltage, a stimulus always presents and changing, in the firing properties of coupled neurons is unknown

Selective monostability in multi-stable systems

We propose a robust method that allows a periodic or a chaotic multi-stable system to be transformed to a monostable system at an orbit with dominant frequency of any of the coexisting attractors. Our approach implies the selection of a particular attractor by periodic external modulation with frequency close to the dominant frequency in the power spectrum of a desired orbit and simultaneous annihilation of all other coexisting states by positive feedback, both applied to one of the system parameters. The method does not require any preliminary knowledge of the system dynamics and the phase space structure. The efficiency of the method is demonstrated in both a non-autonomous multi-stable laser with coexisting periodic orbits and an autonomous Rössler-like oscillator with coexisting chaotic attractors. The experiments with an erbium-doped fibre laser provide evidence for the robustness of the proposed method in making the system monostable at an orbit with dominant frequency of any preselected attractor

Noise-induced attractor annihilation in the delayed feedback logistic map

We study dynamics of the bistable logistic map with delayed feedback, under the influence of white Gaussian noise and periodic modulation applied to the variable. This system may serve as a model to describe population dynamics under finite resources in noisy environment with seasonal fluctuations. While a very small amount of noise has no effect on the global structure of the coexisting attractors in phase space, an intermediate noise totally eliminates one of the attractors. Slow periodic modulation enhances the attractor annihilation

Detecting specific oscillatory regimes in the dynamics of erbium-doped fiber laser

A method for determining the oscillatory mode occurring in an erbiumdoped fiber laser with a modulated parameter is proposed. The method is based on using a continuous wavelet transform with a mother Morlet wavelet and analyzing the energy of the wavelet spectrum that corresponds to the relevant range of time scales

Statistical Properties and Predictability of Extreme Epileptic Events

The use of extreme events theory for the analysis of spontaneous epileptic brain activity is a relevant multidisciplinary problem. It allows deeper understanding of pathological brain functioning and unraveling mechanisms underlying the epileptic seizure emergence along with its predictability. The latter is a desired goal in epileptology which might open the way for new therapies to control and prevent epileptic attacks. With this goal in mind, we applied the extreme event theory for studying statistical properties of electroencephalographic (EEG) recordings of WAG/Rij rats with genetic predisposition to absence epilepsy. Our approach allowed us to reveal extreme events inherent in this pathological spiking activity, highly pronounced in a particular frequency range. The return interval analysis showed that the epileptic seizures exhibit a highly-structural behavior during the active phase of the spiking activity. Obtained results evidenced a possibility for early (up to 7 s) prediction of epileptic seizures based on consideration of EEG statistical properties

Experimental implementation of a biometric laser synaptic sensor

We fabricate a biometric laser fiber synaptic sensor to transmit information from one neuron cell to the other by an optical way. The optical synapse is constructed on the base of an erbium-doped fiber laser, whose pumped diode current is driven by a pre-synaptic FitzHugh–Nagumo electronic neuron, and the laser output controls a post-synaptic FitzHugh–Nagumo electronic neuron. The implemented laser synapse displays very rich dynamics, including fixed points, periodic orbits with different frequency-locking ratios and chaos. These regimes can be beneficial for efficient biorobotics, where behavioral flexibility subserved by synaptic connectivity is a challenge

Increasing Human Performance by Sharing Cognitive Load Using Brain-to-Brain Interface

Brain-computer interfaces (BCIs) attract a lot of attention because of their ability to improve the brain's efficiency in performing complex tasks using a computer. Furthermore, BCIs can increase human's performance not only due to human-machine interactions, but also thanks to an optimal distribution of cognitive load among all members of a group working on a common task, i.e., due to human-human interaction. The latter is of particular importance when sustained attention and alertness are required. In every day practice, this is a common occurrence, for example, among office workers, pilots of a military or a civil aircraft, power plant operators, etc. Their routinely work includes continuous monitoring of instrument readings and implies a heavy cognitive load due to processing large amounts of visual information. In this paper, we propose a brain-to-brain interface (BBI) which estimates brain states of every participant and distributes a cognitive load among all members of the group accomplishing together a common task. The BBI allows sharing the whole workload between all participants depending on their current cognitive performance estimated from their electrical brain activity. We show that the team efficiency can be increased due to redistribution of the work between participants so that the most difficult workload falls on the operator who exhibits maximum performance. Finally, we demonstrate that the human-to-human interaction is more efficient in the presence of a certain delay determined by brain rhythms. The obtained results are promising for the development of a new generation of communication systems based on neurophysiological brain activity of interacting people. Such BBIs will distribute a common task between all group members according to their individual physical conditions