Frequency enhancement in coupled noisy excitable elements

Kramers Rate Theory of Pacemaker Dynamics in Noisy Excitable Media

Rhythmic activities, which are usually driven by pacemakers, are common in biological systems. In noisy excitable media, pacemakers are self-organized firing clusters, but the underlying dynamics remains to be elucidated. Here we develop a Kramers rate theory of coupled cells to describe the firing properties of pacemakers and their dependence on coupling strength and system size and dimension. The theory captures accurately the simulation results of tissue models with stochastic Hodgkin-Huxley equations except when transitions from pacemakers to spiral waves occur under weak coupling.

Unbalanced clustering and solitary states in coupled excitable systems

We discover the mechanisms of emergence and the link between two types of symmetry-broken states, the unbalanced periodic two-cluster states and solitary states, in coupled excitable systems with attractive and repulsive interactions. The prevalent solitary states in non-locally coupled arrays, whose self-organization is based on successive (order preserving) spiking of units, derive their dynamical features from the corresponding unbalanced cluster states in globally coupled networks. Apart from the states with successive spiking, we also find cluster and solitary states where the interplay of excitability and local multiscale dynamics gives rise to so-called leap-frog activity patterns with an alternating order of spiking between the units. We show that the noise affects the system dynamics by suppressing the multistability of cluster states and by inducing pattern homogenization, transforming solitary states into patterns of patched synchrony.

Dynamics of beating cardiac tissue under slow periodic drives

Effects of mechanical coupling on cardiac dynamics are studied by monitoring the beating dynamics of a cardiac tissue which is being pulled periodically at a pace slower than its intrinsic beating rate. The tissue is taken from the heart of a bullfrog that includes pacemaker cells. The cardiac tissue beats spontaneously with an almost constant interbeat interval (IBI) when there is no external forcing. On the other hand, the IBI is observed to vary significantly under an external periodic drive. Interestingly, when the period of the external drive is about two times the intrinsic IBI of the tissue without pulling, the IBI as a function of time exhibits a wave packet structure. Our experimental results can be understood theoretically by a phase-coupled model under external driving. In particular, the theoretical prediction of the wave-packet period as a function of the normalized driving period agrees excellently with the observations. Furthermore, the cardiac mechanical coupling constant can be extracted from the experimental data from our model and is found to be insensitive to the external driving period. Implications of our results on cardiac physiology are also discussed.

Mitochondrial networks in cardiac myocytes reveal dynamic coupling behavior

Oscillatory behavior of mitochondrial inner membrane potential (ΔΨm) is commonly observed in cells subjected to oxidative or metabolic stress. In cardiac myocytes, the activation of inner membrane pores by reactive oxygen species (ROS) is a major factor mediating intermitochondrial coupling, and ROS-induced ROS release has been shown to underlie propagated waves of ΔΨm depolarization as well as synchronized limit cycle oscillations of ΔΨm in the network. The functional impact of ΔΨm instability on cardiac electrophysiology, Ca(2+) handling, and even cell survival, is strongly affected by the extent of such intermitochondrial coupling. Here, we employ a recently developed wavelet-based analytical approach to examine how different substrates affect mitochondrial coupling in cardiac cells, and we also determine the oscillatory coupling properties of mitochondria in ventricular cells in intact perfused hearts. The results show that the frequency of ΔΨm oscillations varies inversely with the size of the oscillating mitochondrial cluster, and depends on the strength of local intermitochondrial coupling. Time-varying coupling constants could be quantitatively determined by applying a stochastic phase model based on extension of the well-known Kuramoto model for networks of coupled oscillators. Cluster size-frequency relationships varied with different substrates, as did mitochondrial coupling constants, which were significantly larger for glucose (7.78 × 10(-2) ± 0.98 × 10(-2) s(-1)) and pyruvate (7.49 × 10(-2) ± 1.65 × 10(-2) s(-1)) than lactate (4.83 × 10(-2) ± 1.25 × 10(-2) s(-1)) or β-hydroxybutyrate (4.11 × 10(-2) ± 0.62 × 10(-2) s(-1)). The findings indicate that mitochondrial spatiotemporal coupling and oscillatory behavior is influenced by substrate selection, perhaps through differing effects on ROS/redox balance. In particular, glucose-perfusion generates strong intermitochondrial coupling and temporal oscillatory stability. Pathological changes in specific catabolic pathways, which are known to occur during the progression of cardiovascular disease, could therefore contribute to altered sensitivity of the mitochondrial network to oxidative stress and emergent ΔΨm instability, ultimately scaling to produce organ level dysfunction.

Activation process in excitable systems with multiple noise sources: One and two interacting units

We consider the coaction of two distinct noise sources on the activation process of a single excitable unit and two interacting excitable units, which are mathematically described by the Fitzhugh-Nagumo equations. We determine the most probable activation paths around which the corresponding stochastic trajectories are clustered. The key point lies in introducing appropriate boundary conditions that are relevant for a class II excitable unit, which can be immediately generalized also to scenarios involving two coupled units. We analyze the effects of the two noise sources on the statistical features of the activation process, in particular demonstrating how these are modified due to the linear or nonlinear form of interactions. Universal properties of the activation process are qualitatively discussed in the light of a stochastic bifurcation that underlies the transition from a stochastically stable fixed point to continuous oscillations.

Clustering versus non-clustering phase synchronizations

Clustering phase synchronization (CPS) is a common scenario to the global phase synchronization of coupled dynamical systems. In this work, a novel scenario, the non-clustering phase synchronization (NPS), is reported. It is found that coupled systems do not transit to the global synchronization until a certain sufficiently large coupling is attained, and there is no clustering prior to the global synchronization. To reveal the relationship between CPS and NPS, we further analyze the noise effect on coupled phase oscillators and find that the coupled oscillator system can change from CPS to NPS with the increase of noise intensity or system disorder. These findings are expected to shed light on the mechanism of various intriguing self-organized behaviors in coupled systems.

Extracting connectivity from dynamics of networks with uniform bidirectional coupling

In the study of networked systems, a method that can extract information about how the individual nodes are connected with one another would be valuable. In this paper, we present a method that can yield such information of network connectivity using measurements of the dynamics of the nodes as the only input data. Our method is built upon a noise-induced relation between the Laplacian matrix of the network and the dynamical covariance matrix of the nodes, and applies to networked dynamical systems in which the coupling between nodes is uniform and bidirectional. Using examples of different networks and dynamics, we demonstrate that the method can give accurate connectivity information for a wide range of noise amplitude and coupling strength. Moreover, we can calculate a parameter Δ using again only the input of time-series data, and assess the accuracy of the extracted connectivity information based on the value of Δ.

The emergence of subcellular pacemaker sites for calcium waves and oscillations

Calcium (Ca(2+)) waves generating oscillatory Ca(2+) signals are widely observed in biological cells. Experimental studies have shown that under certain conditions, initiation of Ca(2+) waves is random in space and time, while under other conditions, waves occur repetitively from preferred locations (pacemaker sites) from which they entrain the whole cell. In this study, we use computer simulations to investigate the self-organization of Ca(2+) sparks into pacemaker sites generating Ca(2+) oscillations. In both ventricular myocyte experiments and computer simulations of a heterogeneous Ca(2+) release unit (CRU) network model, we show that Ca(2+) waves occur randomly in space and time when the Ca(2+) level is low, but as the Ca(2+) level increases, waves occur repetitively from the same sites. Our analysis indicates that this transition to entrainment can be attributed to the fact that random Ca(2+) sparks self-organize into Ca(2+) oscillations differently at low and high Ca(2+) levels. At low Ca(2+), the whole cell Ca(2+) oscillation frequency of the coupled CRU system is much slower than that of an isolated single CRU. Compared to a single CRU, the distribution of interspike intervals (ISIs) of the coupled CRU network exhibits a greater variation, and its ISI distribution is asymmetric with respect to the peak, exhibiting a fat tail. At high Ca(2+), however, the coupled CRU network has a faster frequency and lesser ISI variation compared to an individual CRU. The ISI distribution of the coupled network no longer exhibits a fat tail and is well-approximated by a Gaussian distribution. This same Ca(2+) oscillation behaviour can also be achieved by varying the number of ryanodine receptors per CRU or the distance between CRUs. Using these results, we develop a theory for the entrainment of random oscillators which provides a unified explanation for the experimental observations underlying the emergence of pacemaker sites and Ca(2+) oscillations.

Simple models for quorum sensing: nonlinear dynamical analysis

Quorum sensing refers to the change in the cooperative behavior of a collection of elements in response to the change in their population size or density. This behavior can be observed in chemical and biological systems. These elements or cells are coupled via chemicals in the surrounding environment. Here we focus on the change of dynamical behavior, in particular from quiescent to oscillatory, as the cell population changes. For instance, the silent behavior of the elements can become oscillatory as the system concentration or population increases. In this work, two simple models are constructed that can produce the essential representative properties in quorum sensing. The first is an excitable or oscillatory phase model, which is probably the simplest model one can construct to describe quorum sensing. Using the mean-field approximation, the parameter regime for quorum sensing behavior can be identified, and analytical results for the detailed dynamical properties, including the phase diagrams, are obtained and verified numerically. The second model consists of FitzHugh-Nagumo elements coupled to the signaling chemicals in the environment. Nonlinear dynamical analysis of this mean-field model exhibits rich dynamical behaviors, such as infinite period bifurcation, supercritical Hopf, fold bifurcation, and subcritical Hopf bifurcations as the population parameter changes for different coupling strengths. Analytical result is obtained for the Hopf bifurcation phase boundary. Furthermore, two elements coupled via the environment and their synchronization behavior for these two models are also investigated. For both models, it is found that the onset of oscillations is accompanied by the synchronized dynamics of the two elements. Possible applications and extension of these models are also discussed.