Random networks of spiking neurons: instability in the Xenopus tadpole moto-neural pattern

A large network of integrate-and-fire neurons is studied analytically when the synaptic weights are independently randomly distributed according to a Gaussian distribution with arbitrary mean and variance. The relevant order parameters are identified, and it is shown that such network is statistically equivalent to an ensemble of independent integrate-and-fire neurons with each input signal given by the sum of a self-interaction deterministic term and a Gaussian colored noise. The model is able to reproduce the quasisynchronous oscillations, and the dropout of their frequency, of the central nervous system neurons of the swimming Xenopus tadpole. Predictions from the model are proposed for future experiments.     

Transmission of noise coded versus additive signals through a neuronal ensemble

Neuronal populations receive signals through temporally inhomogeneous spike trains which can be approximated by an input consisting of a time dependent mean value (additive signal) and noise with a time dependent intensity (noise coded signal). We compare the linear response of an ensemble of model neurons to these signals. Our analytical solution for the mean activity demonstrates the high efficiency of the transmission of a noise coded signal in a broad frequency band. For both kinds of signal we show that the transmission by the ensemble reveals stochastic resonance as well as a nonmonotonous dependence on the driving frequency.     

Improvement of signal transmission through spike-timing-dependent plasticity in neural networks

We explore the effects of spike-timing-dependent plasticity (STDP) on weak signal transmission in a noisy neural network. We first consider the network where an ensemble of independent neurons, which are subjected to a common weak signal, are connected in parallel to a single postsynaptic neuron via excitatory synapses. STDP can make the signal transmission more efficient, and this effect is more prominent when the presynaptic activities exhibit some correlations. We further consider a two-layer network where there are only couplings between two layers and find that postsynaptic neurons can fire synchronously under suitable conditions. Both the reliability and timing precision of neuronal firing in the output layer are remarkably improved with STDP. These results indicate that STDP can play crucial roles in information processing in nervous systems.Received: 23 March 2004, Published online: 12 July 2004PACS: 87.18.Sn Neural networks - 87.17.Aa Theory and modeling; computer simulation     

Stability, bifurcations, and dynamics of global variables of a system of bursting neurons

An approximate mean field model of an ensemble of delayed coupled stochastic Hindmarsh-Rose bursting neurons is constructed and analyzed. Bifurcation analysis of the approximate system is performed using numerical continuation. It is demonstrated that the stability domains in the parameter space of the large exact systems are correctly estimated using the much simpler approximate model.     

仿生鳍条姿态测量及其误差分析

在复杂环境下齿轮箱信号往往会淹没在噪声信号中,特征向量难以提取。为了有效的进行故障诊断,提出了基于最大相关反褶积(MCKD)总体平均经验模态分解(EEMD)近似熵和双子支持向量机(TWSVM)的齿轮箱故障诊断方法。首先采用MCKD方法对强噪声信号进行滤波处理,在采用EEMD方法对齿轮箱信号进行分解,分解后得到本征模函数(IMF)分量进行近似熵求解,得到齿轮特征向量,最后将其输入到TWSVM分类器中进行故障识别。仿真实验表明,采用MCKD-EEMD方法能够有效的提取原始信号,与其他分类器相比,TWSVM的计算时间短,分类效果好等优点。     

Echo responses of an ensemble of cold atoms in optical lattices

The dynamics of an ultracold dilute boson gas in an optical lattice is described in the framework of the Bose-Hubbard model in which the parameters of the system are controlled by light. Within this model, an ensemble of Bose-Einstein condensates trapped in cells of a double optical lattice generates an echo response in the quantum-mechanical probability current. The echo signal is excited by biharmonic radiation pulses under two-photon (Raman) resonance conditions. The time profile of the echo signal and the role played by the inhomogeneous broadening and the interaction of atoms in the formation of the boson echo are discussed.     

基于MCKD-EEMD近似熵和TWSVM的齿轮箱故障诊断

在复杂环境下齿轮箱信号往往会淹没在噪声信号中,特征向量难以提取;为了有效地进行故障诊断,提出了基于最大相关反褶积(MCKD)总体平均经验模态分解(EEMD)近似熵和双子支持向量机(TWSVM)的齿轮箱故障诊断方法;首先采用MCKD方法对强噪声信号进行滤波处理,在采用EEMD方法对齿轮箱信号进行分解,分解后得到本征模函数(IMF)分量进行近似熵求解,得到齿轮特征向量,最后将其输入到TWSVM分类器中进行故障识别;仿真实验表明,采用MCKD-EEMD方法能够有效地提取原始信号,与其他分类器相比,TWSVM的计算时间短,分类效果好等优点。     

Analysis of the Spectral Composition of Fluorescence from Laser-Excited Cold Atomic Clouds

A consistent quantum approach is used to calculate the signal of fluorescence from a laser-excited cold atomic ensemble. The possibility of analyzing the spectral composition of this nonstationary signal is investigated. Application of wavelet transforms is shown to be a very efficient method that allows achieving a good spectral or temporal resolution, depending on specific problem. On the basis of this approach, the spectral composition of fluorescence and its dynamics after excitation are studied. The spectral properties of the secondary emission of the ensemble are compared for different directions and polarizations.     

Stochastic resonance on Newman-Watts networks of Hodgkin-Huxley neurons with local periodic driving

We study the phenomenon of stochastic resonance on Newman-Watts small-world networks consisting of biophysically realistic Hodgkin-Huxley neurons with a tunable intensity of intrinsic noise via voltage-gated ion channels embedded in neuronal membranes. Importantly thereby, the subthreshold periodic driving is introduced to a single neuron of the network, thus acting as a pacemaker trying to impose its rhythm on the whole ensemble. We show that there exists an optimal intensity of intrinsic ion channel noise by which the outreach of the pacemaker extends optimally across the whole network. This stochastic resonance phenomenon can be further amplified via fine-tuning of the small-world network structure, and depends significantly also on the coupling strength among neurons and the driving frequency of the pacemaker. In particular, we demonstrate that the noise-induced transmission of weak localized rhythmic activity peaks when the pacemaker frequency matches the intrinsic frequency of subthreshold oscillations. The implications of our findings for weak signal detection and information propagation across neural networks are discussed.     

Stacking interactions in denaturation of DNA fragments

A mesoscopic model for heterogeneous DNA denaturation is developed in the framework of the path integral formalism. The base pair stretchings are treated as one-dimensional, time-dependent paths contributing to the partition function. The size of the paths ensemble, which measures the degree of cooperativity of the system, is computed versus temperature consistently with the model potential physical requirements. It is shown that the ensemble size strongly varies with the molecule backbone stiffness providing a quantitative relation between stacking and features of the melting transition. The latter is an overall smooth crossover which begins from the adenine-thymine-rich portions of the fragment. The harmonic stacking coupling shifts, along the T -axis, the occurrence of the multistep denaturation but it does not change the character of the crossover. The methods to compute the fractions of open base pairs versus temperature are discussed: by averaging the base pair displacements over the path ensemble, we find that such fractions signal the multisteps of the transition in good agreement with the indications provided by the specific heat plots.     

Optimal control of neuronal activity

We investigate the optimal control of neuronal spiking activity for neurons receiving a class of random synaptic inputs, characterized by a positive parameter alpha. Optimal control signals and optimal variances are found exactly for the diffusion process approximating an integrate and fire model. When synaptic inputs are "sub-Poisson" (alpha<0.5), we find that the optimal synaptic input is a delta function (corresponding to bang-bang control) and the optimal signal is not unique. Poisson synaptic input is the critical case: The control signal is unique, but the control signal is still a delta function. For "supra-Poisson" (alpha>0.5) inputs, the optimal control is smooth and unique. The optimal variance obtained in the current paper sets the lowest possible bound in controlling the stochasticity of neuronal activity. We also discuss how to implement the optimal control signal for certain model neurons.     

Amplification of terahertz/infrared field at the nodes of Ranvier for myelinated nerve

The myelination of axons was the last major evolution in the vertebrate nervous system. Myelin promotes the speed of action potential by two orders, and modulates the conduction of neurons, important for learning new skills. However, the intrinsic mechanism for high-speed information propagation in myelin in the nervous systems is still unclear. We propose that myelinated nerve fibres serve as dielectric waveguides for the high-frequency electromagnetic information in a certain mid-infrared to terahertz spectral range. Based on the structure characteristics of myelinated nerve composed of periodic nodes of Ranvier and myelin sheath, the energy for the signal propagation is supplied and amplified when crossing the nodes of Ranvier via a periodic relay. In this work, we exploit the quasi-quantum model of amplification for neural terahertz/infrared information at the nodes of Ranvier, and prove the existence of biomolecular ensemble for three-energy-level amplification, revealing the essential mechanism of high-speed electromagnetic information transmitting in myelinated nerves.     

A comparison of stochastic and effective medium approaches to the backscattered signal from a porous layer in a solid matrix

This paper reports a study of the backscattering behavior of a solid layer containing randomly spaced spherical cavities in the long wavelength limit. The motivation for the work arises from a need to model the responses of porous composite materials in ultrasonic NDE procedures. A comparison is made between models based on a summation over discrete scatterers, which show interesting emergent properties, and an integral formulation based on an ensemble average, and with a simple slab effective medium approximation. The similarities and differences between these three models are demonstrated. A simple quantitative criterion is established which sets the maximum frequency at which ensemble average or equivalent homogeneous medium models can represent echo signal generation in a porous layer for given interpore spacing, or equivalently, given pore size and concentration.     

基于时频分析的离心泵空化状态表征研究

空化检测对于保障离心泵运行的安全性和可靠性具有重要意义,已有研究侧重于信号采集和特征提取,对于空化诱发的振动噪声形成机理研究不够深入.为了实现离心泵空化状态的准确表征和有效识别,本文建立了基于信号调制理论的流体机械振动噪声信号模型,将流体激振信号和调制信号视为空化表征的有效信息成分,在此基础上提出了一种基于频带能量和峭...     

Pacer cell response to periodic Zeitgebers

Almost all organisms show some kind of time periodicity in their behavior. In mammals, the neurons of the suprachiasmatic nucleus form a biological clock regulating the activity-inactivity cycle of the animal. The main question is how this clock is able to entrain to the natural 24 h light-dark cycle by which it is stimulated. Such a system is usually modeled as a collection of mutually coupled two-state (active-inactive) phase oscillators with an external stimulus (Zeitgeber). In this article however, we investigate the entrainment of a single pacer cell to the ensemble of other pacer cells. Moreover the stimulus of the ensemble is taken to be periodic. The pacer cell interacts with its environment by phase delay at the end of its activity interval and phase advance at the end of its inactivity interval. We develop a mathematical model for this system, naturally leading to a circle map depending on parameters like the intrinsic period and phase delay and advance. The existence of resonance tongues in a circle map shows that an individual pacer cell is able to synchronize with the ensemble. We furthermore show how the parameters in the model can be related to biological observable quantities. Finally we give several directions of further research.     

The displacement correlation tensor: microstructure, ensemble anisotropy and curving fibers

Experiments with multiple diffusion wave vectors are known to carry more information than what is available from standard diffusion experiments. Here we consider a special case of this class of pulse sequences, the double wave vector diffusion experiment, and use the cumulant expansion of the signal to introduce the displacement correlation tensor. We discuss its physical interpretation and properties, noting in particular that its short time behavior allows determination of the surface to volume ratio of the pore space. We present a general expression for the displacement correlation tensor, and provide explicit expressions for a few model geometries. We then show that the scatter matrix characterizing the orientation distribution of an ensemble of cylinders is simply related to the displacement correlation tensor. This result is generalized to ensembles of pores with arbitrary shapes allowing a precise formulation of the influence of microstructural and ensemble anisotropy on the double wave vector diffusion signal in the Gaussian phase approximation. Finally, as a new application of the double wave vector diffusion signal, we analyze its behavior in a curving fiber, and suggest that the displacement correlation tensor may be used to estimate sub-voxel fiber curvature and deflection angle. The theoretical results are corroborated by computer simulations.     

Spike-burst synchronization in an ensemble of electrically coupled discrete model neurons

In this paper, we study the dynamics of a system of two model neurons interacting via the electrical synapse. Each neuron is described by a two-dimensional discontinuous map. A chaotic relaxational-type attractor, which corresponds to the spiking-bursting chaotic oscillations of neurons is shown to exist in a four-dimensional phase space. It is found that the dynamical mechanism of formation of chaotic bursts is based on a new phenomenon of generation of transient chaotic oscillations. It is demonstrated that transition from the chaotic-burst generation to the state of relative rest occurs with a certain time delay. A new characteristic which estimates the degree of synchronization of the spiking-bursting oscillations is introduced. The dependence of the synchronization degree on the strength of coupling of the ensemble elements is studied.     

Bursting synchronization in non-locally coupled maps

Neuron activity presents two timescales, a fast one related to action-potential spiking, and a slow timescale in which bursting takes place. Bursting activity in neuron ensembles can be synchronized, meaning the adjustment of the bursting phases due to coupling. We investigated bursting synchronization in a non-locally coupled lattice using a two-dimensional map to describe neuron activity. The coupling involves all sites in a lattice, the corresponding strength decreasing with the lattice distance in a power-law fashion. We observed bursting synchronization for wide intervals of the coupling parameters. We also investigated the bursting synchronization of the ensemble with an external time-periodic signal applied to one or more selected neurons.     

乙醇含量拉曼光谱检测中噪声与背景同时消除方法研究

乙醇含量拉曼光谱检测中,拉曼光谱信号中的各种噪声及光谱荧光造成的基线漂移和样品池背景等,影响了校正模型的预测精度。利用总体平均经验模态分解,将光谱信号分解成若干无模态混叠的内在模式分量,根据排列熵的信号随机性检测判据判断出代表背景信息和噪声信息的内在模式分量,将其置零即可同时消除拉曼光谱中的噪声与背景。将总体平均经验模态分解与排列熵相结合的预处理方法应用于乙醇含量的拉曼光谱检测中,并与小波变换和平均平滑滤波做了对比。实验结果表明：应用总体平均经验模态分解与排列熵相结合的方法能够有效的同时消除乙醇含量拉曼光谱检测中的噪声和背景信息,提高校正模型的预测精度,且使用简便,无需参数设置,对乙醇含量拉曼光谱检测具有实用价值。     

Enhanced response to a signal from an ensemble of interacting bistable elements

A one-dimensional ensemble comprising a large number of interacting bistable elements was studied analytically. Formulas for a noiseless and a noise-driven response to a signal were derived for the steady-state case. Contrasting them with each other testifies to the enhancement of the response if noise is present in the ensemble. The response of the ensemble is found to exceed that of a single element by a quantity that exponentially rises with the coupling constant. It was inferred that the interaction of bistable elements makes stochastic resonance more pronounced.