Stochastic responses of tumor-immune system with periodic treatment

We investigate the stochastic responses of a tumor–immune system competition model with environmental noise and periodic treatment. Firstly, a mathematical model describing the interaction between tumor cells and immune system under external fluctuations and periodic treatment is established based on the stochastic differential equation. Then, sufficient conditions for extinction and persistence of the tumor cells are derived by constructing Lyapunov functions and Ito's formula. Finally, numerical simulations are introduced to illustrate and verify the results. The results of this work provide the theoretical basis for designing more effective and precise therapeutic strategies to eliminate cancer cells, especially for combining the immunotherapy and the traditional tools.     

Stochastic fluctuation induced the competition between extinction and recurrence in a model of tumor growth

We investigate the phenomenon that stochastic fluctuation induced the competition between tumor extinction and recurrence in the model of tumor growth derived from the catalytic Michaelis–Menten reaction. We analyze the probability transitions between the extinction state and the state of the stable tumor by the Mean First Extinction Time (MFET) and Mean First Return Time (MFRT). It is found that the positional fluctuations hinder the transition, but the environmental fluctuations, to a certain level, facilitate the tumor extinction. The observed behavior could be used as prior information for the treatment of cancer.     

阈下激励与噪声联合作用下肝细胞系统的内钙时空随机共振问题

研究阈下周期信号激励对耦合肝细胞系统内钙离子浓度（［Ca²⁺］)的时空随机共振性质的影响.当阈下激励的频率等于确定性系统在Hopf分岔点附近的频率时,它就会极大地提高随机耦合系统内发生［Ca²⁺］喷发的细胞的比例,通过对喷发比的自相关函数计算得知阈下激励增强了系统在高斯白噪声作用下［Ca²⁺］的时间共振性.通过数值模拟得知,对于不同耦合强度,都存在最优噪声强度使得随机系统内［Ca²⁺］时间共振达到最佳,并且随着细胞间耦 关键词： 钙振动 噪声 阈下激励 随机共振     

Control of stochastic resonance in bistable system by using periodic signal

<正>According to the characteristic structure of double wells in bistable systems,this paper analyses stochastic fluctuations in the single potential well and probability transitions between the two potential wells and proposes a method of controlling stochastic resonance by using a periodic signal.Results of theoretical analysis and numerical simulation show that the phenomenon of stochastic resonance happens when the time scales of the periodic signal and the noise-induced probability transitions between the two potential wells achieve stochastic synchronization.By adding a bistable system with a controllable periodic signal,fluctuations in the single potential well can be effectively controlled,thus affecting the probability transitions between the two potential wells.In this way,an effective control can be achieved which allows one to either enhance or realize stochastic resonance.     

Monitoring noise-resonant effects in cancer growth influenced by external fluctuations and periodic treatment

We investigate a mathematical model describing the growth of tumor in the presence of immune response of a host organism. The dynamics of tumor and immune cells populations is based on the generic Michaelis-Menten kinetics depicting interaction and competition between the tumor and the immune system. The appropriate phenomenological equation modeling cell-mediated immune surveillance against cancer is of the predator-prey form and exhibits bistability within a given choice of the immune response-related parameters. Under the influence of weak external fluctuations, the model may be analyzed in terms of a stochastic differential equation bearing the form of an overdamped Langevin-like dynamics in the external quasi-potential represented by a double well. We analyze properties of the system within the range of parameters for which the potential wells are of the same depth and when the additional perturbation, modeling a periodic treatment, is insufficient to overcome the barrier height and to cause cancer extinction. In this case the presence of a small amount of noise can positively enhance the treatment, driving the system to a state of tumor extinction. On the other hand, however, the same noise can give rise to return effects up to a stochastic resonance behavior. This observation provides a quantitative analysis of mechanisms responsible for optimization of periodic tumor therapy in the presence of spontaneous external noise. Studying the behavior of the extinction time as a function of the treatment frequency, we have also found the typical resonant activation effect: For a certain frequency of the treatment, there exists a minimum extinction time.     

Stochastic resonance on paced genetic regulatory small-world networks: effects of asymmetric potentials

We study the phenomenon of stochastic resonance on small-world networks consisting of bistable genetic regulatory units, whereby the external subthreshold periodic forcing is introduced as a pacemaker trying to impose its rhythm on the whole network through the single unit to which it is introduced. Without the addition of additive spatiotemporal noise, however, the whole network remains forever trapped in one of the two stable steady states of the local dynamics. We show that the correlation between the frequency of subthreshold pacemaker activity and the response of the network is resonantly dependent on the intensity of additive noise. The reported pacemaker driven stochastic resonance depends significantly on the asymmetry of the two potential wells characterizing the bistable dynamics, which can be tuned via a single system parameter. In particular, we show that the ratio between the clustering coefficient and the characteristic path length is a suitable quantity defining the ability of a small-world network to facilitate the outreach of the pacemaker-emitted subthreshold rhythm, but only if the asymmetry between the potentials is practically negligible. In case of substantially asymmetric potentials the impact of the small-world topology is less profound and cannot warrant an enhancement of stochastic resonance by units that are located far from the pacemaker.     

Stochastic resonance on a modular neuronal network of small-world subnetworks with a subthreshold pacemaker

We study the phenomenon of stochastic resonance on a modular neuronal network consisting of several small-world subnetworks with a subthreshold periodic pacemaker. Numerical results show that the correlation between the pacemaker frequency and the dynamical response of the network is resonantly dependent on the intensity of additive spatiotemporal noise. This effect of pacemaker-driven stochastic resonance of the system depends extensively on the local and the global network structure, such as the intra- and inter-coupling strengths, rewiring probability of individual small-world subnetwork, the number of links between different subnetworks, and the number of subnetworks. All these parameters play a key role in determining the ability of the network to enhance the noise-induced outreach of the localized subthreshold pacemaker, and only they bounded to a rather sharp interval of values warrant the emergence of the pronounced stochastic resonance phenomenon. Considering the rather important role of pacemakers in real-life, the presented results could have important implications for many biological processes that rely on an effective pacemaker for their proper functioning.     

Fluctuations and dissipations in stochastic energetic resonance

By analyzing the fluctuations and dissipations of a Brownian particle colliding with the molecules in a fluid, the work exchanged between the Brownian particle constrained in a bistable potential well and an external periodic force is investigated. Characters of the stochastic energetic resonance are found and studied at different intensities of fluctuations and dissipations. The microscopic mechanism of energy exchange between the Brownian particle and the external force is revealed. The method used in this study provides a novel way of controlling the stochastic energetic resonance.     

双稳系统演化的时间尺度与随机共振的加强

噪声作用下的双稳系统存在着单一势阱内的随机波动和两势阱之间的概率跃迁,这两种不同层级的运动具有不同的时间尺度,且低层级的势阱内的波动影响着高层级的势阱间的跃迁．当外作用周期信号的时间尺度与噪声诱导的势阱间概率跃迁达到随机同步时,则能产生随机共振;给系统再加第二驱动周期信号,使其时间尺度与低层级的势阱内的波动相匹配,则存在着频率吸收现象,并能增强双稳系统的随机共振效应． 关键词： 随机共振 双稳系统 层级 时间尺度     

Stochastic resonance in a locally excited system of bistable oscillators

Stochastic resonance is studied in a one-dimensional array of overdamped bistable oscillators in the presence of a local subthreshold periodic perturbation. The system can be treated as an ensemble of pseudospins tending to align parallel which are driven dynamically by an external periodic magnetic field. The oscillators are subjected to a dynamic white noise as well as to a static topological disorder. The latter is quantified by the fraction of randomly added long-range connections among ensemble elements. In the low connectivity regime the system displays an optimal global stochastic resonance response if a small-world network is formed. In the mean-field regime we explain strong changes in the dynamic disorder strength provoking a maximal stochastic resonance response via the variation of fraction of long-range connections by taking into account the ferromagnetic-paramagnetic phase transition of the pseudospins. The system size analysis shows only quantitative power-law type changes on increasing number of pseudospins.     

Hopping and phase shifts in noisy periodically driven bistable systems

We consider a periodically driven bistable system in the presence of fluctuations. In a number of recent papers it has been shown that the amplitude of the response of the noisy system to periodic modulations exhibits stochastic resonance, i.e. a resonance-like behavior as a function of the noise intensity. In this paper, we consider the phase shift between the response and the periodic driving. For weak periodic driving, the phase shift also shows a resonance like behaviour as a function of the noise strength, but this effect is shown to be of different origin than the one responsible for stochastic resonance. Furthermore, the phase shift is demonstrated to exhibit a resonance-like behavior as a function of the driving frequency.     

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.     

Noise-induced entrainment and stochastic resonance in human brain waves

We present the first observation of stochastic resonance (SR) in the human brain's visual processing area. The novel experimental protocol is to stimulate the right eye with a subthreshold periodic optical signal and the left eye with a noisy one. The stimuli bypass sensory organs and are mixed in the visual cortex. With many noise sources present in the brain, higher brain functions, e.g., perception and cognition, may exploit SR.     

Stochastic resonance in a nonlinear system with a 1/f spectrum

The system of two nonlinear stochastic equations simulating 1/f fluctuations during the interaction of nonequilibrium phase transitions in the presence of an external harmonic force is analyzed using numerical methods. It is shown that the stochastic resonance occurring in the system enhances the output periodic signal under the action of noise. A random process with a 1/f power spectrum corresponds to the Gibbs-Shannon information entropy peak. In stochastic resonance, the information entropy is minimal.     

Characteristics of critical amplitude of a sinusoidal stimulus in a model neuron

The characteristics of the critical amplitude of a sinusoidal stimulus in a model neuron, Morris－Lecar model, are investigated numerically. It is important in the study of stochastic resonance to determine whether a periodic stimulus is subthreshold or not. The critical amplitude as a function of the stimulus frequency is not a constant, but a curve, which is the boundary between subthreshold and suprathreshold stimulation. It has been considered that this curve is U-shaped in the previous investigations, and this has been accepted as a universal phenomenon. Nevertheless, we think that it is only true for a type of neuron: namely, resonators. Actually, there exists another type of neuron, integrators, which can undergo a saddle-node on invariant circle bifurcation from the rest state to the firing state. For the latter we find that the critical amplitude increases monotonically as the frequency of sinusoidal stimulus is increased. This is shown by way of the Morris－Lecar model. As a consequence, the critical amplitude curve is studied further, and the dynamical mechanisms underlying the change in critical amplitude curve are uncovered. The results of this paper can provide a reference to choose the subthreshold periodic stimulus.     

Experimental evidence of coexisting periodic stochastic resonance and coherence resonance phenomena

We report evidence of coexisting period stochastic resonance (PSR) and coherence resonance (CR) phenomena in an electrochemical cell. The anodic voltage (V) in the cell is chosen such that the anodic current (I) exhibits excitable fixed point behavior. Subsequently, the anodic voltage is modulated by an external perturbation that is a composite of a subthreshold periodic pulse signal and Gaussian white noise (GWN). As the amplitude of the GWN is increased, the regularity of the invoked dynamics is analyzed using normalized variance curve. The calculated resonance curve shows a double minima, implying the existence of two optimum noise levels where enhanced regularity of the induced spike sequence is detected. Numerical simulations corroborate experimental findings.     

Stochastic resonance in threshold devices

Summary We consider the transmission of a periodic signal by noisy threshold devices. A general expression for the input-output characteristic is developed and applied to two particular threshold devices. It is shown that the amplitude of the signal output shows in the subthreshold regime a maximum as a function of the noise strength—the fingerprint of stochastic resonance. Paper presented at the International Workshop ?Fluctuations in Physics and Biology: Stochastic Resonance, Signal Processing and Related Phenomena?, Elba 5–10 June 1994.     

过阻尼谐振子的随机共振

研究了由交叉相关高斯白噪声驱动的过阻尼谐振子的随机共振,其中加法噪声被周期信号所调制,运用平稳关联函数的傅里叶变换,导出了过阻尼谐振子随机模型信噪比的精确表达式.结果揭示:在过阻尼谐振子的随机模型中存在二类随机共振.一类随机共振表现为信噪比随乘法噪声强度Q变化的曲线存在共振峰,另一类随机共振表现为信噪比随振子频率ω变化的曲线存在共振峰.大幅度改变信号频率Ω值的大小,信噪比随乘法噪声强度Q变化的曲线有单峰,一峰一谷和单调变化三种不同的形式.     

Noise induced complexity: from subthreshold oscillations to spiking in coupled excitable systems

We study the stochastic dynamics of an ensemble of N globally coupled excitable elements. Each element is modeled by a FitzHugh-Nagumo oscillator and is disturbed by independent Gaussian noise. In simulations of the Langevin dynamics we characterize the collective behavior of the ensemble in terms of its mean field and show that with the increase of noise the mean field displays a transition from a steady equilibrium to global oscillations and then, for sufficiently large noise, back to another equilibrium. In the course of this transition diverse regimes of collective dynamics ranging from periodic subthreshold oscillations to large-amplitude oscillations and chaos are observed. In order to understand the details and mechanisms of these noise-induced dynamics we consider the thermodynamic limit N-->infinity of the ensemble, and derive the cumulant expansion describing temporal evolution of the mean field fluctuations. In Gaussian approximation this allows us to perform the bifurcation analysis; its results are in good qualitative agreement with dynamical scenarios observed in the stochastic simulations of large ensembles.