Effect of noise on the tuning properties of excitable systems

We analyze the effect of additive dynamical noise on simple phase-locking patterns in the Fitzhugh–Nagumo (FHN) two-dimensional system in the excitable regime. In the absence of noise, the response amplitude for this system displays a classical resonance as a function of driving frequency. This translates into V-shaped tuning curves, which represent the amplitude threshold for one firing per cycle as a function of forcing frequency. We show that noise opens up these tuning curves at mid-to-low frequencies. We explain this numerical result analytically using a heuristic form for the firing rate that incorporates the frequency dependence of the subthreshold voltage response. We also present stochastic phase-locking curves in the noise intensity-forcing period subspace of parameter space. The relevance of our findings for the tuning of electroreceptors of weakly electric fish and their encoding of amplitude modulations of high frequency carriers are briefly discussed. Our study shows that, in certain contexts, it is essential to take into account the frequency sensitivity of neural responses and their modification by sources of noise.     

Comparison of dynamical and spectator models of a (pseudo)conformal universe

We consider two versions of the scenario for generating scalar cosmological perturbations based on the conformal symmetry: a spectator version with a scalar field conformally coupled to gravity and with a negligible energy density; a dynamical version with a scalar field minimally coupled to gravity and dominating the cosmological evolution. Using the Newtonian gauge, we show, first, that no UV strong-coupling scale is generated below M _Pl , because of mixing with metric perturbations in the dynamical scenario, and, second, that both the dynamical and the spectator models yield identical results in the leading nonlinear order. These results, which include potentially observable effects like statistical anisotropy and non-Gaussianity, hold for the entire class of conformal models. As an example, in the dynamical scenario with the comoving gauge, we reproduce our result on the statistical anisotropy, previously obtained in the framework of the spectator approach.     

Modelling life tables with advanced ages: An extreme value theory approach

We propose a new model – we call it a smoothed threshold life table (STLT) model – to generate life tables incorporating information on advanced ages. Our method allows a smooth mortality transition from non-extreme to extreme ages, and provides objectively determined highest attained ages with which to close the life table.We proceed by modifying the threshold life table (TLT) model developed by Li et al. (2008). In the TLT model, extreme value theory (EVT) is used to make optimal use of the relatively small number of observations at high ages, while the traditional Gompertz distribution is assumed for earlier ages. Our novel contribution is to constrain the hazard function of the two-part lifetime distribution to be continuous at the changeover point between the Gompertz and EVT models. This simple but far-reaching modification not only guarantees a smooth transition from non-extreme to extreme ages, but also provides a better and more robust fit than the TLT model when applied to a high quality Netherlands dataset. We show that the STLT model also compares favourably with other existing methods, including the Gompertz–Makeham model, logistic models, Heligman–Pollard model and Coale–Kisker method, and that a further generalisation, a time-dependent dynamic smooth threshold life table (DSTLT) model, generally has superior in-sample fitting as well as better out-of-sample forecasting performance, compared, for example, with the Cairns et al. (2006) model.     

Clusters die hard: Time-correlated excitation in the Hamiltonian mean field model

The Hamiltonian mean field (HMF) model has a low-energy phase where N particles are trapped inside a cluster. Here, we investigate some properties of the trapping/untrapping mechanism of a single particle into/outside the cluster. Since the single particle dynamics of the HMF model resembles the one of a simple pendulum, each particle can be identified as a high-energy particle (HEP) or a low-energy particle (LEP), depending on whether its energy is above or below the separatrix energy. We then define the trapping ratio as the ratio of the number of LEP to the total number of particles and the “fully-clustered” and “excited” dynamical states as having either no HEP or at least one HEP. We analytically compute the phase-space average of the trapping ratio by using the Boltzmann–Gibbs stable stationary solution of the Vlasov equation associated with the N → ∞ limit of the HMF model. The same quantity, obtained numerically as a time average, is shown to be in very good agreement with the analytical calculation. Another important feature of the dynamical behavior of the system is that the dynamical state changes transitionally: the “fully-clustered” and “excited” states appear in turn. We find that the distribution of the lifetime of the “fully-clustered” state obeys a power law. This means that clusters die hard, and that the excitation of a particle from the cluster is not a Poisson process and might be controlled by some type of collective motion with long memory. Such behavior should not be specific of the HMF model and appear also in systems where itinerancy among different “quasi-stationary” states has been observed. It is also possible that it could mimick the behavior of transient motion in molecular clusters or some observed deterministic features of chemical reactions.     

On the scaling properties of the period-increment scenario in dynamical systems

Two one-dimensional dynamical systems discrete in time are presented, where the variation of one parameter causes a sequence of global bifurcations; at each bifurcation the period increases by a constant value (period-increment scenario, usually denoted as a period-adding scenario). We determine all the bifurcation points and the scaling constants of the period-increment scenario analytically. A re-injection mechanism, leading to the period-increment scenario, is discussed. It will be shown, that in systems with more than one parameter the scaling constants can depend on the values of the parameters.     

Characterization of chaotic attractors at bifurcations in Murali–Lakshmanan–Chua's circuit and one-way coupled map lattice system

In the present paper we study certain characteristic features associated with bifurcations of chaos in a finite dimensional dynamical system – Murali–Lakshmanan–Chua (MLC) circuit equation and an infinite dimensional dynamical system – one-way coupled map lattice (OCML) system. We characterize chaotic attractors at various bifurcations in terms of σ_n(q) – the variance of fluctuations of coarse-grained local expansion rates of nearby orbits. For all chaotic attractors the σ_n(q) versus q plot exhibits a peak at q=q_α. Additional peaks, however, are found only just before and just after the bifurcations of chaos. We show power-law variation of maximal Lyapunov exponent near intermittency and sudden widening bifurcations. Linear variation is observed for band-merging bifurcation. We characterize weak and strong chaos using probability distribution of k-step difference of a state variable.     

Control and recovery from rare congestion events in a large multi-server system

We develop deterministic fluid approximations to describe the recovery from rare congestion events in a large multi-server system in which customer holding times have a general distribution. There are two cases, depending on whether or not we exploit the age distribution (the distribution of elapsed holding times of customers in service). If we do not exploit the age distribution, then the rare congestion event is a large number of customers present. If we do exploit the age distribution, then the rare event is an unusual age distribution, possibly accompanied by a large number of customers present. As an approximation, we represent the large multi-server system as an M/G/∞ model. We prove that, under regularity conditions, the fluid approximations are asymptotically correct as the arrival rate increases. The fluid approximations show the impact upon the recovery time of the holding-time distribution beyond its mean. The recovery time may or not be affected by the holding-time distribution having a long tail, depending on the precise definition of recovery. The fluid approximations can be used to analyze various overload control schemes, such as reducing the arrival rate or interrupting services in progress. We also establish large deviations principles to show that the two kinds of rare events have the same exponentially small order. We give numerical examples showing the effect of the holding-time distribution and the age distribution, focusing especially on the consequences of long-tail distributions. This revised version was published online in June 2006 with corrections to the Cover Date.     

Hair-triggered instability of radial steady states, spread and extinction in semilinear heat equations

We first study the initial value problem for a general semilinear heat equation. We prove that every bounded nonconstant radial steady state is unstable if the spatial dimension is low (n?10) or if the steady state is flat enough at infinity: the solution of the heat equation either becomes unbounded as t approaches the lifespan, or eventually stays above or below another bounded radial steady state, depending on if the initial value is above or below the first steady state; moreover, the second steady state must be a constant if n?10.Using this instability result, we then prove that every nonconstant radial steady state of the generalized Fisher equation is a hair-trigger for two kinds of dynamical behavior: extinction and spreading. We also prove more criteria on initial values for these types of behavior. Similar results for a reaction-diffusion system modeling an isothermal autocatalytic chemical reaction are also obtained.     

Dynamical behavior of a virus dynamics model with CTL immune response

In this paper, the dynamical behavior of a virus dynamics model with CTL immune response is studied. Sufficient conditions for the asymptotical stability of a disease-free equilibrium, an immune-free equilibrium and an endemic equilibrium are obtained. We prove that there exists a threshold value of the infection rate b beyond which the endemic equilibrium bifurcates from the immune-free one. Still for increasing b values, the endemic equilibrium bifurcates towards a periodic solution. We further analyze the orbital stability of the periodic orbits arising from bifurcation by applying Poore’s condition. Numerical simulation with some hypothetical sets of data has been done to support the analytical findings.     

Dynamical behavior for an eco-epidemiological model with discrete and distributed delay

In this paper, the dynamical behavior of an eco-epidemiological model with discrete and distributed delay is studied. Sufficient conditions for the local asymptotical stability of the nonnegative equilibria are obtained. We prove that there exists a threshold value of the feedback time delay τ beyond which the positive equilibrium bifurcates towards a periodic solution. Using the normal form theory and center manifold argument, the explicit formulae which determine the stability, the direction and the periodic of bifurcating period solutions are derived. Numerical simulations are carried out to explain the mathematical conclusions.     

Interval availability analysis of a two-echelon,multi-item system

In this paper we analyze the interval availability of a two-echelon, multi-item spare part inventory system. We consider a scenario inspired by a situation that we encountered at Thales Netherlands, a manufacturer of naval sensors and naval command and control systems. Modeling the complete system as a Markov chain we analyze the interval availability and we compute in closed and exact form the expectation and the variance of the availability during a finite time interval [0, T]. We use these characteristics to approximate the survival function using a Beta distribution, together with the probability that the interval availability is equal to one. Comparison of our approximation with simulation shows excellent accuracy, especially for points of the distribution function below the mean value. The latter points are practically most relevant.     

The Stratonovich Interpretation of Quantum Stochastic Approximations

The Stratonovich version of non-commutative stochastic calculus is introduced and shown to be equivalent to the Itô version developed by Hudson and Parthasarathy [1]. The conversion from Stratonovich to Itô version is shown to be implemented by a stochastic form of Wick's theorem: that is, involving the normal ordering of time-dependent noise fields. It is shown for a model of a quantum mechanical system coupled to a Bosonic field in a Gaussian state that under suitable scaling limits, in particular the weak coupling limit (for linear interactions) and low density limit (for scattering interactions), the limit form of the dynamical equation of motion is most naturally described as a quantum stochastic differential equation of Stratonovich form. We then convert the limit dynamical equations from Stratonovich to Itô form. Thermal Stratonovich noises are also presented.     

The perturbed compound Poisson risk model with constant interest and a threshold dividend strategy

In this paper, we consider the compound Poisson risk model perturbed by diffusion with constant interest and a threshold dividend strategy. Integro-differential equations with certain boundary conditions for the moment-generation function and the nth moment of the present value of all dividends until ruin are derived. We also derive integro-differential equations with boundary conditions for the Gerber-Shiu functions. The special case that the claim size distribution is exponential is considered in some detail.     

Severity modeling of extreme insurance claims for tariffication

Generalized linear models are common instruments for the pricing of non-life insurance contracts. They are used to estimate the expected frequency and severity of insurance claims. However, these models do not work adequately for extreme claim sizes. To accommodate for these extreme claim sizes, we develop the threshold severity model, that splits the claim size distribution in areas below and above a given threshold. More specifically, the extreme insurance claims above the threshold are modeled in the sense of the peaks-over-threshold methodology from extreme value theory using the generalized Pareto distribution for the excess distribution, and the claims below the threshold are captured by a generalized linear model based on the truncated gamma distribution. Subsequently, we develop the corresponding concrete log-likelihood functions above and below the threshold. Moreover, in the presence of simulated extreme claim sizes following a log-normal as well as Burr Type XII distribution, we demonstrate the superiority of the threshold severity model compared to the commonly used generalized linear model based on the gamma distribution.     

Noise,nonlinear dynamics and the timecourse of affective disorders

Affective disorders, such as depression or mania, tend to be recurrent and progressive. Typically, disease patterns evolve from isolated episodes to rhythmic and finally accelerated “chaotic” mood patterns during the longitudinal course. Concepts from dynamical systems have been considered to explain this progression. However, most natural systems are not only nonlinear but also affected by noise. For this reason it seems important to incorporate cooperative stochastic–dynamic effects into current conceptional models for the course and neurobiology of such disorders. We use a computational perspective and describe behaviors of a simple mathematical model which result from interactions between random and deterministic dynamics. In particular, we focus on a scenario for illness progression that relies on noise enhancement of feedback instabilities. We suggest that noise amplification of subclinical neurobiological vulnerabilities could represent a relevant disease mechanism.     

The effect of synchronous firing on the clustering dynamics of social amoebae

A discrete model for computer simulations of the clustering dynamics of social amoebae is presented. This model incorporates the wavelike propagation of extracellular signaling of 3′–5′‐cyclic adenosine monophosphate (cAMP), the sporadic firing of cells at early stage of aggregation, the signal relaying as a response to stimulus, and the inertia and purposeful random walk of the cell movement. It is found that the sporadic firing below the threshold of cAMP concentration plays an important role because it allows time for the cells to form synchronous firing right before the stage of aggregation, and the synchronous firing is critical for the onset of clustering behavior of social amoebae. A Monte‐Carlo simulation was also run which showed the existence of potential equilibriums of mean and variance of aggregation time. The simulation result of this model could well reproduce many phenomena observed by actual experiments. © 2013 Wiley Periodicals, Inc. Complexity 20: 16–26, 2014     

Contour Enhancement,Short Term Memory,and Constancies in Reverberating Neural Networks

A model of the nonlinear dynamics of reverberating on-center off-surround networks of nerve cells, or of cell populations, is analysed. The on-center off-surround anatomy allows patterns to be processed across populations without saturating the populations' response to large inputs. The signals between populations are made sigmoid functions of population activity in order to quench network noise, and yet store sufficiently intense patterns in short term memory (STM). There exists a quenching threshold: a population's activity will be quenched along with network' noise if it falls below the threshold; the pattern of supra threshold population activities is contour enhanced and stored in STM. Varying arousal level can therefore influence which pattern features will be stored. The total suprathreshold activity of the network is carefully regulated. Applications to seizure and hallucinatory phenomena, to position codes for motor control, to pattern discrimination, to influences of novel events on storage of redundant relevant cues, and to the construction of a sensory-drive heterarchy are mentioned, along with possible anatomical substrates in neocortex, hypothalamus, and hippocampus.     

Pricing basket default swaps in a tractable shot noise model

We value CDS spreads and kth-to-default swap spreads in a tractable shot noise model. The default dependence is modelled by letting the individual jumps of the default intensity be driven by a common latent factor. The arrival of the jumps is driven by a Poisson process. By using conditional independence and properties of the shot noise processes we derive tractable closed form expressions for the default distribution and the ordered survival distributions. These quantities are then used to price kth-to-default swap spreads. We calibrate a homogeneous version of the model to the term structure on market data from the iTraxx Europe index series sampled during the period 2008-01-14 to 2010-02-11. We perform 435 calibrations in this turbulent period and almost all calibrations yield very good fits. Finally we study kth-to-default spreads in the calibrated model.     

Polynomial power-Pareto quantile function models

In this paper we propose a polynomial power-Pareto quantile function model and a Bayesian method for parameters estimation. We also carried out simulation studies and applied our methodology to real data sets empirically. The results show that a quantile function approach to statistical modelling is very flexible due to the properties of quantile functions, and that the combination of a power and a Pareto distribution enables us to model both the main body and the tails of a distribution, even though the mathematical form of the distribution does not exist. Our research also suggests a new approach to studying extreme values based on a whole data set rather than group maximum/minimum or exceedances above/below a proper threshold value.     

Minimum action method for the study of rare events

The least action principle from the Wentzell‐Freidlin theory of large deviations is exploited as a numerical tool for finding the optimal dynamical paths in spatially extended systems driven by a small noise. The action is discretized and a preconditioned BFGS method is used to optimize the discrete action. Applications are presented for thermally activated reversal in the Ginzburg‐Landau model in one and two dimensions, and for noise induced excursion events in the Brusselator taken as an example of non‐gradient system arising in chemistry. In the Ginzburg‐Landau model, the reversal proceeds via interesting nucleation events, followed by propagation of domain walls. The issue of nucleation versus propagation is discussed and the scaling for the number of nucleation events as a function of the reversal time and other material parameters is computed. Good agreement is found with the numerical results. In the Brusselator, whose deterministic dynamics has a single stable equilibrium state, the presence of noise is shown to induce large excursions by which the system cycles out of this equilibrium state. © 2004 Wiley Periodicals, Inc.