Stochastic Resonance in a Bacterium Growth System Subjected to Colored Noises

We present the logistic growth model to study the stochastic resonance （SR） in a bacterium growth system under the simultaneous action of two external multiplicative cross-correlation noises and periodic external forcing. The expression of the signal-to-noise ratio （SNR） for a bacterium growth system is derived by using the theory of SNR in the adiabatic limit. Based on SNR, we discuss the effects of self-correlation time τ1 and τ2, cross-correlation time 3-3 and cross-correlation strength λ on the SNR. It is found that the self-correlation time τ1 and τ2, and cross-correlation strength λ enhance the SR of the bacterium growth system, while cross-correlation time τ3 weakens the SR of the bacterium growth system.     

Stochastic Resonance in a Bacterium Growth System Subjected to Colored Noises

We present the logistic growth model to study the stochastic resonance (SR) in a bacterium growth system under the simultaneous action of two externalmultiplicative cross-correlation noises and periodic external forcing. The expression of the signal-to-noise ratio (SNR) for a bacterium growth system is derived by using the theory of SNR in the adiabatic limit. Based on SNR, we discuss the effects of self-correlation time τ₁ and τ₂, cross-correlationtime τ₃ and cross-correlation strength λ on the SNR. It is found that the self-correlation time τ₁ and τ₂, and cross-correlation strength λ enhance the SR of the bacterium growth system, while cross-correlation time τ₃ weakens the SR of the bacterium growth system.     

Spiking Regularity and Coherence in Complex Hodgkin-Huxley Neuron Networks

We study the effects of the strength of coupling between neurons on the spiking regularity and coherence in a complex network with randomly connected Hodgkin-Huxley neurons driven by colored noise. It is found that for the given topology realization and colored noise correlation time, there exists an optimal strength of coupling, at which the spiking regularity of the network reaches the best level, Moreover, when the temporal regularity reaches the best level, the spatial coherence of the system has already increased to a relatively high level. In addition, for the given number of neurons and noise correlation time, the values of average regularity and spatial coherence at the optimal strength of coupling are nearly independent of the topology realization. Furthermore, there exists an optimal value of colored noise correlation time at which the spiking regularity can reach its best level. These results may be helpful for understanding of the real neuron world.     

Effect of Correlated Dichotomous Noises on Stochastic Resonance in a Linear System

A linear system driven by correlated asymmetric dichotomous noises and periodic signal was investigated in the overdamped case. The exact expressions of output signal amplitude and signal-to-noise ratio (SNR) of the system were derived. By means of numerical calculations, we found that: (i) At some fixed multiplicative noise intensities, the output signal amplitude with frequency exhibits the structure of a weak peak, even no peak as the dichotomous noise is asymmetric; (ii) In the case of asymmetric dichotomous noise, the signal frequency can cause non-monotonous behavior of the output signal amplitude with respect to multiplicative noise intensity; (iii) The curve of SNR with frequency has a weak peak and a trough in the case of symmetric dichotomous noise, but no peak with asymmetric; (iv) Whether the multiplicative noise is symmetric or asymmetric, the noise can enhance response of the system; (v) The SNR increases with the correlation strength between the two noises decreasing. In addition, the plane of multiplicative noise intensity versus noise symmetric parameter was plotted.     

Stochastic Resonance in a Bistable System Subject to Non-Gaussian and Gaussian Noises

In this paper, we consider the phenomenon of stochastic resonance （SR） in a quartic bistable system under the simultaneous action of a multiplicative non-Gaussian and an additive Gaussian noises and a weak periodic signal. The expression of the signal-to-noise ratio R is derived by applying the two-state theory in adiabatic limit. We discuss the effects of the parameter q indicating the departure of the non-Gaussian noise from the Gaussian noise, the correlation time r of the non-Gaussian noise, and coupling intensity A between two noise terms on the stochastic resonance. It is found that the signM-to-noise ratio of the system, as a function of the additive noise intensity, undergoes the transition from having one peak to having two peaks, and then to having one peak again when the parameter q or the noise correlation time τ is increased. The parameter q and τ play opposite roles in the SR of the system.     

Stochastic Resonance in a Spatially Symmetric and Flashing Periodic Potential Subjected to Correlated Noises

A Brownian particle in a spatially symmetric and flashing periodic potential subjected to correlated noises is investigated. The exact expression of its current is analytically derived. The numerical results indicate that its current as a function of noise intensity exhibits two peaks in the case of positive correlations, and two vales in the case of negative correlations, i.e., a novel stochastic resonance （SR） phenomenon. The SR is attributed to the harmonic cooperation between the noises and the flashing periodic potential. The conditions under which the SR occurs are also presented.     

Coherence Resonance and Noise-Induced Synchronization in Hindmarsh-Rose Neural Network with Different Topologies

In this paper, we investigate coherence resonance （CR） and noise-induced synchronization in Hindmarsh- Rose （HR） neural network with three different types of topologies： regular, random, and small-world. It is found that the additive noise can induce CR in HR neural network with different topologies and its coherence is optimized by a proper noise level. It is also found that as coupling strength increases the plateau in the measure of coherence curve becomes broadened and the effects of network topology is more pronounced simultaneously. Moreover, we find that increasing the probability p of the network topology leads to an enhancement of noise-induced synchronization in HR neurons network.     

Solvent Suppression in Intermolecular Magnetic Resonance Spectra Multiple-Quantum Coherence Nuclear with Only z-axis Gradients

The solvent peak in the intermolecular multiple-quantum coherence spectra can be suppressed by either applying pulse field gradients or spinning sample along the magic angle direction （φ = 54.7）. However, these two methods also suppress the signals of the solute. We design two pulse sequences with only z-axis gradients to suppress the solvent peak without reducing the intensity of solute signals. Compared to the former pulse sequence, the latter pulse sequence is insensitive to the imperfection of pulse flip angles. When the flip angles of the second pulse sequence are purposely deviated 1/10 from the optimal values, the solvent peak is still weak. Theoretical expressions, experimental observations and computer simulations demonstrate that the two methods can be used to effectively suppress solvent peak in intermolecular multiple-quantum coherence spectra.     

Stochastic Resonance in Finely Dispersed Magnetics: a Comparison of Discrete and Continuous Models

The phenomenon of a stochastic resonance in a system of single-domain particles with easy-axis magnetic anisotropy is treated theoretically for the thermally activated system. The results of calculations for the discrete model based on the control equation for the Kramers transition rates of the magnetic moment vector and for the continuous model based on numerical solution of the Fokker–Planck equation with a periodic drift term are analyzed. The phase shifts between input and output signals and the values of the signal-to-noise ratio calculated for iron superparamagnetic particles in the context of these two models are compared.     

Correlated Noises in a Prey-Predator Ecosystem

We investigate a Volterra ecosystem driven by correlated noises. The fluctuation in the death rate of the predator induces an increase of population density of the predators. The fluctuation in the growth rate of the prey, however, leads the predators to decay. It is reported that the predators undergo sensitivity to a random environment, whereas the preys exhibit a surprising endurance to the same stochastic factor. The predators are of better stability under strong correlation of noises.     

Strange Nonchaotic Attractors in a Time-Delay System

A nonchaotic attractor is observed in an infinite-dimensional system which is related to optical bistability and described by a nonlinear time-delay differential equation. The observed nonchaotic attractor is characterized by the strange trajectory of attractor but with negative value for the largest Lyapunov exponent, as well as the Fourier power spectra.     

Effect of Correlated Noises in a Genetic Model

The Stratonovich stochastic differential equation is used to analyze genotype selection in the presence ot correlatecl Gaussian white noises. We study the steady state properties of the genotype selection and discuss the effects of the correlated noises. It is found that the degree of correlation of the noises can be used to select one type of genes from another type of mixing genes. The strong selection of genes caused by a large value of multiplicative noise intensity can be weakened by the intensive negative correlation.     

Neuron participation in a synchrony-encoding assembly

Background  

Synchronization of action potentials between neurons is considered to be an encoding process that allows the grouping of various and multiple features of an image leading to a coherent perception. How this coding neuronal assembly is configured is debated. We have previously shown that the magnitude of synchronization between excited neurons is stimulus-dependent. In the present investigation we compare the levels of synchronization between synchronizing individual neurons and the synchronizing pool of cells to which they belong.     

Neuron participation in a synchrony-encoding assembly

Background

Caenorhabditis elegans actively crawls down thermal gradients until it reaches the temperature of its prior cultivation, exhibiting what is called cryophilic movement. Implicit in the worm's performance of cryophilic movement is the ability to detect thermal gradients, and implicit in regulating the performance of cryophilic movement is the ability to compare the current temperature of its surroundings with a stored memory of its cultivation temperature. Several lines of evidence link the AFD sensory neuron to thermotactic behavior, but its precise role is unclear. A current model contends that AFD is part of a thermophilic mechanism for biasing the worm's movement up gradients that counterbalances the cryophilic mechanism for biasing its movement down gradients.

Results

We used tightly-focused femtosecond laser pulses to dissect the AFD neuronal cell bodies and the AFD sensory dendrites in C. elegans to investigate their contribution to cryophilic movement. We establish that femtosecond laser ablation can exhibit submicrometer precision, severing individual sensory dendrites without causing collateral damage. We show that severing the dendrites of sensory neurons in young adult worms permanently abolishes their sensory contribution without functional regeneration. We show that the AFD neuron regulates a mechanism for generating cryophilic bias, but we find no evidence that AFD laser surgery reduces a putative ability to generate thermophilic bias. In addition, although disruption of the AIY interneuron causes worms to exhibit cryophilic bias at all temperatures, we find no evidence that laser killing the AIZ interneuron causes thermophilic bias at any temperature.

Conclusion

We conclude that laser surgical analysis of the neural circuit for thermotaxis does not support a model in which AFD opposes cryophilic bias by generating thermophilic bias. Our data supports a model in which the AFD neuron gates a mechanism for generating cryophilic bias.     

Absorption-Dispersion Properties in a Four-Level Atomic System with Vacuum-Induced Coherence

We discuss and analyze absorption-dispersion response for the probe field in a typical four-level atomic system with vacuum-induced coherence (VIC) arising from the cross coupling pathways associated with a pair of upper excited hyperfine levels. We find that VIC effect can preserve electromagnetically induced transparency (FIT) by using the detailed numerical simulations based on the density-matrix equations and analytical calculations in the dressed-state picture. We also show that the atomic hyperfine structure cannot be a hindrance to obtaining EIT.     

Absorption-Dispersion Properties in a Four-Level Atomic System with Vacuum-Induced Coherence

We discuss and analyze absorption-dispersion response for the probe field in a typical four-level atomic system with vacuum-induced coherence (VIC) arising from the cross coupling pathways associated with a pair of upper excited hyperfine levels. We find that VIC effect can preserve electromagnetically induced transparency (EIT) by using the detailed numerical simulations based on the density-matrix equations and analytical calculations in the dressed-state picture. We also show that the atomic hyperfine structure cannot be a hindrance to obtaining EIT.