n:m Phase-locking of weakly coupled oscillators

Two weakly coupled oscillators are studied and the existence of n:m phase-locked solutions is shown. With the use of a slow time scale, the problem is reduced to a two-dimensional system on an invariant attracting torus. This system is further reduced to a one-dimensional dynamical system. Fixed points of this system correspond to n:m phase-locked solutions. The method is applied to a forced oscillator, linearly coupled - systems, and a pair of integrate and fire neuron models.     

Dynamics of coupled stomatal oscillators

Stomata are microscopic openings in the leaves of green plants which permit gas exchange. Stomata exhibit oscillatory opening and closing behavior under certain environmental conditions in addition to a daily (diurnal) cycle. In order to explore the effects of coupling between neighboring stomata we present a mathematical model of the dynamics of a system of N coupled stomatal oscillators. An individual stomate is modeled to either remain closed, oscillate periodically, or remain open, depending on the local water potential. Coupling between neighboring stomata is accomplished in the model by taking into account the flow of water in the leaf as well as by oscillator phase coupling.Analysis of the model shows that under certain conditions it exhibits a stable spatially uniform synchronized behavior, referred to here as the in-phase mode. It is also shown that under non-uniform illumination the system may behave in a more complicated fashion.     

Time-synchronized clustering of gene expression trajectories

Current clustering methods are routinely applied to gene expressiontime course data to find genes with similar activation patternsand ultimately to understand the dynamics of biological processes.As the dynamic unfolding of a biological process often involvesthe activation of genes at different rates, successful clusteringin this context requires dealing with varying time and shapepatterns simultaneously. This motivates the combination of anovel pairwise warping with a suitable clustering method todiscover expression shape clusters. We develop a novel clusteringmethod that combines an initial pairwise curve alignment toadjust for time variation within likely clusters. The cluster-specifictime synchronization method shows excellent performance overstandard clustering methods in terms of cluster quality measuresin simulations and for yeast and human fibroblast data sets.In the yeast example, the discovered clusters have high concordancewith the known biological processes.     

A group-theoretic approach to rings of coupled biological oscillators

In this paper, a general approach for studying rings of coupled biological oscillators is presented. This approach, which is group-theoretic in nature, is based on the finding that symmetric ring networks of coupled non-linear oscillators possess generic patterns of phaselocked oscillations. The associated analysis is independent of the mathematical details of the oscillators' intrinsic dynamics and the nature of the coupling between them. The present approach thus provides a framework for distinguishing universal dynamic behaviour from that which depends upon further structure. In this study, the typical oscillation patterns for the general case of a symmetric ring of n coupled non-linear oscillators and the specific cases of three- and five-membered rings are considered. Transitions between different patterns of activity are modelled as symmetry-breaking bifurcations. The effects of one-way coupling in a ring network and the differences between discrete and continuous systems are discussed. The theoretical predictions for symmetric ring networks are compared with physiological observations and numerical simulations. This comparison is limited to two examples: neuronal networks and mammalian intestinal activity. The implications of the present approach for the development of physiologically meaningful oscillator models are discussed.     

Synchronization of coupled nonidentical genetic oscillators

The study of the collective dynamics of synchronization among genetic oscillators is essential for the understanding of the rhythmic phenomena of living organisms at both molecular and cellular levels. Genetic oscillators are biochemical networks, which can generally be modelled as nonlinear dynamic systems. We show in this paper that many genetic oscillators can be transformed into Lur'e form by exploiting the special structure of biological systems. By using a control theory approach, we provide a theoretical method for analysing the synchronization of coupled nonidentical genetic oscillators. Sufficient conditions for the synchronization as well as the estimation of the bound of the synchronization error are also obtained. To demonstrate the effectiveness of our theoretical results, a population of genetic oscillators based on the Goodwin model are adopted as numerical examples.     

Spontaneous synchronization of coupled circadian oscillators

In mammals, the circadian pacemaker, which controls daily rhythms, is located in the suprachiasmatic nucleus (SCN). Circadian oscillations are generated in individual SCN neurons by a molecular regulatory network. Cells oscillate with periods ranging from 20 to 28 h, but at the tissue level, SCN neurons display significant synchrony, suggesting a robust intercellular coupling in which neurotransmitters are assumed to play a crucial role. We present a dynamical model for the coupling of a population of circadian oscillators in the SCN. The cellular oscillator, a three-variable model, describes the core negative feedback loop of the circadian clock. The coupling mechanism is incorporated through the global level of neurotransmitter concentration. Global coupling is efficient to synchronize a population of 10,000 cells. Synchronized cells can be entrained by a 24-h light-dark cycle. Simulations of the interaction between two populations representing two regions of the SCN show that the driven population can be phase-leading. Experimentally testable predictions are: 1), phases of individual cells are governed by their intrinsic periods; and 2), efficient synchronization is achieved when the average neurotransmitter concentration would dampen individual oscillators. However, due to the global neurotransmitter oscillation, cells are effectively synchronized.     

The behavior of rings of coupled oscillators

Coupled oscillators in a ring are studied using perturbation and numerical methods. Stability of waves with nearest neighbor weak coupling is shown for a class of simple oscillators. Linkens' [23] model for colorectal activity is analyzed and several stable modes are found. Stability of waves with general (non nearest neighbor coupling) is determined and comparisons to the nearest neighbor case are made. Approximate solutions to a ring with inhomogeneities are compared with numerical simulations.Supported by a NSF Grant No. MCS8300885 and the Alfred Sloan Foundation     

The dynamics of coupled populations subject to control

The dynamics of coupled populations have mostly been studied in the context of metapopulation viability with application to, for example, species at risk. However, when considering pests and pathogens, eradication, not persistence, is often the end goal. Humans may intervene to control nuisance populations, resulting in reciprocal interactions between the human and natural systems that can lead to unexpected dynamics. The incidence of these human-natural couplings has been increasing, hastening the need to better understand the emergent properties of such systems in order to predict and manage outbreaks of pests and pathogens. For example, the success of the growing aquaculture industry depends on our ability to manage pathogens and maintain a healthy environment for farmed and wild fish. We developed a model for the dynamics of connected populations subject to control, motivated by sea louse parasites that can disperse among salmon farms. The model includes exponential population growth with a forced decline when populations reach a threshold, representing control interventions. Coupling two populations with equal growth rates resulted in phase locking or synchrony in their dynamics. Populations with different growth rates had different periods of oscillation, leading to quasiperiodic dynamics when coupled. Adding small amounts of stochasticity destabilized quasiperiodic cycles to chaos, while stochasticity was damped for periodic or stable dynamics. Our analysis suggests that strict treatment thresholds, although well intended, can complicate parasite dynamics and hinder control efforts. Synchronizing populations via coordinated management among farms leads to more effective control that is required less frequently. Our model is simple and generally applicable to other systems where dispersal affects the management of pests and pathogens.     

Synchronization of non-linear biochemical oscillators coupled by diffusion

The behaviour of similar coupled non-linear oscillators of the type \(\dot x\) =f(x, y, µ \(\dot y\) =g(x, y, µ is to be investigated. The oscillators are assumed to be coupled by diffusion gradients. If some conditions on the magnitude of the diffusion coefficients are satisfied, it is proved that: 1) if the oscillators have the same period (identical value of the parameter μ) and different phases before coupling, after coupling they tend to synchronize the phases; 2) if the periods of the oscillators are not too different (in terms of the values of the parameter μ) before coupling, after coupling they tend to oscillate with the same period. It is suggested the possible role of diffusion as a synchronizing mechanism in some biological phenomena.     

Lung and buccal ventilation in the frog: uncoupling coupled oscillators

The frog, with two distinct ventilatory acts, provides a useful model to investigate the prospective interaction of two oscillators in generating the respiratory rhythm. Building on evidence supporting the existence of separate oscillators generating buccal and lung ventilation, we have attempted to uncouple the two rhythms in the isolated brain stem preparation. Opioid preferentially inhibits the lung rhythm, suggesting an uncoupling of the lung from the buccal oscillator. Reduction of the superfusate chloride concentration alters both the buccal and the lung rhythms. Joint application of opioid and reduced-chloride superfusate leads to an increase in the variability of the buccal burst-to-lung burst intervals. This increase in variability suggests that chloride-mediated mechanisms are involved in coupling the buccal oscillator to the lung oscillator. Given the results from these interventions, we propose a simple schematic model of the frog respiratory rhythm generator, outlining the coupling of the lung and buccal oscillators.     

Detecting effective connectivity in networks of coupled neuronal oscillators

The application of data-driven time series analysis techniques such as Granger causality, partial directed coherence and phase dynamics modeling to estimate effective connectivity in brain networks has recently gained significant prominence in the neuroscience community. While these techniques have been useful in determining causal interactions among different regions of brain networks, a thorough analysis of the comparative accuracy and robustness of these methods in identifying patterns of effective connectivity among brain networks is still lacking. In this paper, we systematically address this issue within the context of simple networks of coupled spiking neurons. Specifically, we develop a method to assess the ability of various effective connectivity measures to accurately determine the true effective connectivity of a given neuronal network. Our method is based on decision tree classifiers which are trained using several time series features that can be observed solely from experimentally recorded data. We show that the classifiers constructed in this work provide a general framework for determining whether a particular effective connectivity measure is likely to produce incorrect results when applied to a dataset.     

Models of coupled population oscillators using 1-D maps

 Coupled population oscillators are investigated with the use of coupled logistic maps. Two forms of coupling are employed, reproductive and density. Three biologically distinct situations are investigated: populations independently oscillating in a two point cycle, populations independently chaotic, and populations independently approach a stable point. Both entrained and phase reversed patterns are observed along with complicated forms of chaos as the coupling parameters are varied.     

Intercellular synchronization of diffusively coupled Ca2+ oscillators

We examine the synchrony in the dynamics of localized [Ca^2 +]_i oscillations among a group of cells exhibiting such complex Ca^2 + oscillations, connected in the form of long chain, via diffusing coupling where cytosolic Ca^2 + and inositol 1,4,5-triphosphate are coupling molecules. Based on our numerical results, we could able to identify three regimes, namely desynchronized, transition and synchronized regimes in the (T − k_e) (time period-coupling constant) and (A − k_e) (amplitude-coupling constant) spaces which are supported by phase plots (Δϕ verses time) and recurrence plots, respectively. We further show the increase of synchronization among the cells as the number of coupling molecules increases in the (T − k_e) and (A − k_e) spaces.     

The heart as a system of coupled nonlinear oscillators

In various approximations the heart is considered as a system of coupled nonlinear oscillators which are characterized by their phase transition curve (PTC) only. The system exhibits many phenomena which are known from ECG recordings such as multi-level-Wenckebach periodicity, dissociation, induction or removal of a tachycardia by an extrasystole, pseudo-block and the gap phenomenon. All these can be discussed within the model on a quantitative level.     

Synchronization ability of coupled cell-cycle oscillators in changing environments

Background

The biochemical oscillator that controls periodic events during the Xenopus embryonic cell cycle is centered on the activity of CDKs, and the cell cycle is driven by a protein circuit that is centered on the cyclin-dependent protein kinase CDK1 and the anaphase-promoting complex (APC). Many studies have been conducted to confirm that the interactions in the cell cycle can produce oscillations and predict behaviors such as synchronization, but much less is known about how the various elaborations and collective behavior of the basic oscillators can affect the robustness of the system. Therefore, in this study, we investigate and model a multi-cell system of the Xenopus embryonic cell cycle oscillators that are coupled through a common complex protein, and then analyze their synchronization ability under four different external stimuli, including a constant input signal, a square-wave periodic signal, a sinusoidal signal and a noise signal.

Results

Through bifurcation analysis and numerical simulations, we obtain synchronization intervals of the sensitive parameters in the individual oscillator and the coupling parameters in the coupled oscillators. Then, we analyze the effects of these parameters on the synchronization period and amplitude, and find interesting phenomena, e.g., there are two synchronization intervals with activation coefficient in the Hill function of the activated CDK1 that activates the Plk1, and different synchronization intervals have distinct influences on the synchronization period and amplitude. To quantify the speediness and robustness of the synchronization, we use two quantities, the synchronization time and the robustness index, to evaluate the synchronization ability. More interestingly, we find that the coupled system has an optimal signal strength that maximizes the synchronization index under different external stimuli. Simulation results also show that the ability and robustness of the synchronization for the square-wave periodic signal of cyclin synthesis is strongest in comparison to the other three different signals.

Conclusions

These results suggest that the reaction process in which the activated cyclin-CDK1 activates the Plk1 has a very important influence on the synchronization ability of the coupled system, and the square-wave periodic signal of cyclin synthesis is more conducive to the synchronization and robustness of the coupled cell-cycle oscillators. Our study provides insight into the internal mechanisms of the cell cycle system and helps to generate hypotheses for further research.

     

European population substructure: clustering of northern and southern populations

Using a genome-wide single nucleotide polymorphism (SNP) panel, we observed population structure in a diverse group of Europeans and European Americans. Under a variety of conditions and tests, there is a consistent and reproducible distinction between “northern” and “southern” European population groups: most individual participants with southern European ancestry (Italian, Spanish, Portuguese, and Greek) have >85% membership in the “southern” population; and most northern, western, eastern, and central Europeans have >90% in the “northern” population group. Ashkenazi Jewish as well as Sephardic Jewish origin also showed >85% membership in the “southern” population, consistent with a later Mediterranean origin of these ethnic groups. Based on this work, we have developed a core set of informative SNP markers that can control for this partition in European population structure in a variety of clinical and genetic studies.     

Two coupled oscillators: simulations of the circadian pacemaker in mammalian activity rhythms

In the activity rhythms of captive small mammals a variety of features, most notably “splitting”, suggest that two coupled oscillators may constitute the pacemaker system which underlies the rhythms. A phenomenological model proposed by Pittendrigh is developed and expanded here using an explicit quantitative structure. It is found that such a system can simulate several qualitative features in the experimental data: the inter-dependence of free-running period (gt) and activity time (α) with changing light intensity described in Aschoff's rule, after-effects on τ and α of prior conditions, and the occasional existence of two stable phase relationships, with different τ values for a given light intensity, as observed in “splitting”. It is hoped that the model will suggest experiments aimed at the elucidation of the physiological basis of these phenomena.     

Quantifying the dynamics of coupled networks of switches and oscillators

Complex network dynamics have been analyzed with models of systems of coupled switches or systems of coupled oscillators. However, many complex systems are composed of components with diverse dynamics whose interactions drive the system's evolution. We, therefore, introduce a new modeling framework that describes the dynamics of networks composed of both oscillators and switches. Both oscillator synchronization and switch stability are preserved in these heterogeneous, coupled networks. Furthermore, this model recapitulates the qualitative dynamics for the yeast cell cycle consistent with the hypothesized dynamics resulting from decomposition of the regulatory network into dynamic motifs. Introducing feedback into the cell-cycle network induces qualitative dynamics analogous to limitless replicative potential that is a hallmark of cancer. As a result, the proposed model of switch and oscillator coupling provides the ability to incorporate mechanisms that underlie the synchronized stimulus response ubiquitous in biochemical systems.     

Phase locking induces scale-free topologies in networks of coupled oscillators

An initial unsynchronized ensemble of networking phase oscillators is further subjected to a growing process where a set of forcing oscillators, each one of them following the dynamics of a frequency pacemaker, are added to the pristine graph. Linking rules based on dynamical criteria are followed in the attachment process to force phase locking of the network with the external pacemaker. We show that the eventual locking occurs in correspondence to the arousal of a scale-free degree distribution in the original graph.     

Power-rate synchronization of coupled genetic oscillators with unbounded time-varying delay

In this paper, a new synchronization problem for the collective dynamics among genetic oscillators with unbounded time-varying delay is investigated. The dynamical system under consideration consists of an array of linearly coupled identical genetic oscillators with each oscillators having unbounded time-delays. A new concept called power-rate synchronization, which is different from both the asymptotical synchronization and the exponential synchronization, is put forward to facilitate handling the unbounded time-varying delays. By using a combination of the Lyapunov functional method, matrix inequality techniques and properties of Kronecker product, we derive several sufficient conditions that ensure the coupled genetic oscillators to be power-rate synchronized. The criteria obtained in this paper are in the form of matrix inequalities. Illustrative example is presented to show the effectiveness of the obtained results.