arXiv subjects

Hiroshi Kori

Publications and source records attributed to Hiroshi Kori.

At least 37 records · Page 2Linked to original sources

arXiv2024

Bifurcation analysis of a two-neuron central pattern generator model for both oscillatory and convergent neuronal activities

The neural oscillator model proposed by Matsuoka is a piecewise affine system, which exhibits distinctive periodic solutions. Although such typical oscillation patterns have been widely studied, little is understood about the dynamics of convergence to certain fixed points and bifurcations between the periodic orbits and fixed points in this model. We performed fixed point analysis on a two-neuron version of the Matsuoka oscillator model, the result of which explains the mechanism of oscillation and the discontinuity-induced bifurcations such as subcritical/supercritical Hopf-like, homoclinic-like, and grazing bifurcations. Furthermore, it provided theoretical predictions concerning a logarithmic oscillation-period scaling law and noise-induced oscillations, which are both observed around those bifurcations. These results are expected to underpin further investigations into both oscillatory and transient neuronal activities with respect to central pattern generators.

nlin.AO↗

arXiv2024

Two distinct transitions in a population of coupled oscillators with turnover: desynchronization and stochastic oscillation quenching

Synchronization, which is caused by mutual coupling, and turnover, which is the replacement of old components with new ones, are observed in various open systems consisting of many components. Although these phenomena can co-occur, the interplay of coupling and turnover has been overlooked. Here, we analyze coupled phase oscillators with turnover and reveal that two distinct transitions occur, depending on both coupling and turnover: desynchronization and what we name stochastic oscillation quenching. Importantly, the latter requires both the turnover and coupling to be sufficiently intense.

nlin.AO↗

arXiv2024

Diffusive coupling facilitates and impedes noise-induced escape in interacting bistable elements

Diverse complex systems often undergo sudden changes in their states, such as epileptic seizures, climate changes, and social uprisings. Such behavior has been modeled by noise-induced escape of bistable elements, which is the escape from an attracting state driven by a fluctuation in the system's state. We consider a system of interacting bistable elements and investigate the effect of diffusive coupling among elements on the process of noise-induced escape. We focus on the influence of the coupling strength over the escape time, which is the time it takes for noise-induced escape to occur. We performed numerical simulations and observed that weak coupling reduced the mean escape time, whereas strong coupling impeded escape. We argue that, although diffusive coupling both facilitates and impedes escape, the facilitating effect is dominant when coupling is weak. For weak coupling cases, we develop an approximate theory that can predict the mean and variance of escape times. In contrast, strong coupling reduces the effective noise intensity to impede escape. Our results suggest that diffusive coupling among multistable elements contributes to regulating the rate of transitions among attracting states.

nlin.AO↗

arXiv2023

Waveform Proportionality and Taylor's Law Induced by Synchronization of Periodic and Chaotic Oscillators

Taylor's law (TL), the scaling relationship between the mean and variance, has been observed in various fields. However, the underlying reasons why TL is so widely observed, why the exponents of TL are often close to 2, and the relationship between temporal and spatial TLs are not fully understood. Here, using coupled oscillator models, we analytically and numerically demonstrate that synchronization can induce TL. In particular, we show that strong synchronization leads to waveform proportionality, resulting in temporal and spatial TLs with exponent 2. Our study can help infer the existence of synchronization solely from the relationship between the mean and variance.

nlin.AO↗

arXiv2023

Synchronization approach to achieving maximum power and thermal efficiency for weakly-coupled low-temperature-differential Stirling engines

Low-temperature-differential (LTD) Stirling engines are heat engines that can operate autonomously with a slight temperature difference between low-temperature heat reservoirs and are thus expected to contribute to a sustainable society. A minimal dynamical-system model with only two variables has been proposed to explain the principle of autonomous rotational motion caused by temperature differences, and the maximum efficiency of the engine was formulated [Y. Izumida, Europhys. Lett. 121, 50004 (2018); Phys. Rev. E 102, 012142 (2020)]. This paper aims to clarify the coupling effects on the dynamics, power, and thermal efficiency of a pair of weakly coupled LTD Stirling engines and formulate the maximum thermal efficiency of the coupled system in the quasilinear response regime. We show that the dependence relation between the effective frequency difference and the coupling strength is characterized by a hysteresis, which comes from different kinds of bifurcations in the process of increasing and decreasing the value of the coupling strength. Then, by generalizing thermodynamic fluxes and forces and their quasilinear relations for engines under weak coupling, we show that the coupling improves the power exerted against the load torques and the thermal efficiency. We further show that their maximum values are achieved when the engines are synchronized. Since the thermal efficiency depends on the frequency difference, the dependence of thermal efficiency on the coupling strength is also characterized by a hysteresis. Finally, the load torque that achieves the maximum thermal efficiency of the coupled system is formulated.

nlin.AO↗

arXiv2023

Synchronization and oscillation quenching in interacting metronomes on a movable platform: simple model and bifurcation analysis

Various oscillatory phenomena occur in the world. Because some oscillations are related to abnormal states (e.g., particular diseases), establishing state-transition methods from an oscillatory to a resting state is important. In this study, we construct a simple metronome model and analyze the oscillation-quenching phenomenon of metronomes on a platform as an example of such state transitions. Although numerous studies were conducted on the metronome dynamics, most of them focused on the synchronization, and few studies treated the oscillation quenching because of the difficulty in analysis. To facilitate the analysis, we model a metronome as a linear spring pendulum with an impulsive force (escapement mechanism) described by a fifth-order polynomial. By performing an averaging approximation, we obtain a phase diagram for the in-phase synchronization, anti-phase synchronization, and oscillation quenching. We also numerically integrate the equation of motion and confirm the agreement between the analytical and numerical results. Despite the simplicity, our model successfully reproduces essential phenomena in interacting mechanical clocks, such as the bistability of in-phase and anti-phase synchrony and oscillation quenching occurring for a large mass ratio between the oscillator and the platform. We believe that our simple model will contribute to future analyses of other dynamics observed in metronomes.

nlin.AO↗

arXiv2023

Mean-field theory for double-well systems on degree-heterogeneous networks

Many complex dynamical systems in the real world, including ecological, climate, financial, and power-grid systems, often show critical transitions, or tipping points, in which the system's dynamics suddenly transit into a qualitatively different state. In mathematical models, tipping points happen as a control parameter gradually changes and crosses a certain threshold. Tipping elements in such systems may interact with each other as a network, and understanding the behavior of interacting tipping elements is a challenge because of the high dimensionality originating from the network. Here we develop a degree-based mean-field theory for a prototypical double-well system coupled on a network with the aim of understanding coupled tipping dynamics with a low-dimensional description. The method approximates both the onset of the tipping point and the position of equilibria with a reasonable accuracy. Based on the developed theory and numerical simulations, we also provide evidence for multistage tipping point transitions in networks of double-well systems.

physics.soc-ph↗

arXiv2023

Transportation efficiency of hydrodynamically coupled spherical oscillators in low Reynolds number fluids

Most bacteria are driven by the cilia or flagella, consisting of a long filament and a rotary molecular motor through a short flexible hook. The beating pattern of these filaments shows synchronization properties from hydrodynamic interactions, especially in low Reynolds number fluids. Here, we introduce a model based on simple spherical oscillators which execute oscillatory movements in one dimension by an active force, as a simplified imitation of the movements of cilia or flagella. It is demonstrated that the flow, measured by the net transportation of a test particle, is generated by a chain of oscillators and enhanced by the hydrodynamic interactions between beads, with supports from both perturbative and numerical results. Transportation efficiency also highly correlates with hydrodynamic interactions. Increments of bead numbers are generally expected to produce stronger flow and efficiency, at least for small numbers of beads.

physics.flu-dyn↗

arXiv2023

Synchronization and stability analysis of an exponentially diverging solution in a mathematical model of asymmetrically interacting agents

This study deals with an existing mathematical model of asymmetrically interacting agents. We analyze the following two previously unfocused features of the model: (i) synchronization of growth rates and (ii) initial value dependence of damped oscillation. By applying the techniques of variable transformation and time-scale separation, we perform the stability analysis of a diverging solution. We find that (i) all growth rates synchronize to the same value that is as small as the smallest growth rate and (ii) oscillatory dynamics appear if the initial value of the slowest-growing agent is sufficiently small. Furthermore, our analytical method proposes a way to apply stability analysis to an exponentially diverging solution, which we believe is also a contribution of this study. Although the employed model is originally proposed as a model of infectious disease, we do not discuss its biological relevance but merely focus on the technical aspects.

nlin.AO↗

arXiv2022

An extended Hilbert transform method for reconstructing the phase from an oscillatory signal

Rhythmic activity is ubiquitous in biological systems from the cellular to organism level. Reconstructing the instantaneous phase is the first step in analyzing the essential mechanism leading to a synchronization state from the observed signals. A popular method of phase reconstruction is based on the Hilbert transform, which can only reconstruct the interpretable phase from a limited class of signals, e.g., narrow band signals. To address this issue, we propose an extended Hilbert transform method that accurately reconstructs the phase from various oscillatory signals. The proposed method is developed by analyzing the reconstruction error of the Hilbert transform method with the aid of Bedrosian's theorem. We validate the proposed method using synthetic data and show its systematically improved performance compared with the conventional Hilbert transform method with respect to accurately reconstructing the phase. Finally, we demonstrate that the proposed method is potentially useful for detecting the phase shift in an observed signal. The proposed method is expected to facilitate the study of synchronization phenomena from experimental data.

nlin.AO↗

arXiv2022

Partial synchronization and community switching in phase-oscillator networks and its analysis based on a bidirectional, weighted chain of three oscillators

Complex networks often possess communities defined based on network connectivity. When dynamics undergo in a network, one can also consider dynamical communities; i.e., a group of nodes displaying a similar dynamical process. We have investigated both analytically and numerically the development of dynamical community structure, where the community is referred to as a group of nodes synchronized in frequency, in networks of phase oscillators. We first demonstrate that using a few example networks, the community structure changes when network connectivity or interaction strength is varied. In particular, we found that community switching, i.e., a portion of oscillators change the group to which they synchronize, occurs for a range of parameters. We then propose a three-oscillator model: a bidirectional, weighted chain of three Kuramoto phase oscillators, as a theoretical framework for understanding the community formation and its variation. Our analysis demonstrates that the model shows a variety of partially synchronized patterns: oscillators with similar natural frequencies tend to synchronize for weak coupling, while tightly connected oscillators tend to synchronize for strong coupling. We obtain approximate expressions for the critical coupling strengths by employing a perturbative approach in a weak coupling regime and a geometric approach in a strong coupling regimes. Moreover, we elucidate the bifurcation types of transitions between different patterns. Our theory might be useful for understanding the development of partially synchronized patterns in a wider class of complex networks than community structured networks.

nlin.AO↗

arXiv2022

Phase and frequency linear response theory for hyperbolic chaotic oscillators

We formulate a linear phase and frequency response theory for hyperbolic flows, which generalizes phase response theory for autonomous limit cycle oscillators to hyperbolic chaotic dynamics. The theory is based on a shadowing conjecture, stating the existence of a perturbed trajectory shadowing every unperturbed trajectory on the system attractor for any small enough perturbation of arbitrary duration and a corresponding unique time isomorphism, which we identify as phase, such that phase shifts between the unperturbed trajectory and its perturbed shadow are well defined. The phase sensitivity function is the solution of an adjoint linear equation and can be used to estimate the average change of phase velocity to small time dependent or independent perturbations. These changes of frequency are experimentally accessible giving a convenient way to define and measure phase response curves for chaotic oscillators. The shadowing trajectory and the phase can be constructed explicitly in the tangent space of an unperturbed trajectory using co-variant Lyapunov vectors. It can also be used to identify the limits of the regime of linear response.

nlin.CD↗

arXiv2022

Accuracy of a one-dimensional reduction of dynamical systems on networks

Resilience is an ability of a system with which the system can adjust its activity to maintain its functionality when it is perturbed. To study resilience of dynamics on networks, Gao et al. proposed a theoretical framework to reduce dynamical systems on networks, which are high dimensional in general, to one-dimensional dynamical systems. The accuracy of this one-dimensional reduction relies on several assumption in addition to the assumption that the network has a negligible degree correlation. In the present study, we analyze the accuracy of the one-dimensional reduction assuming networks without degree correlation. We do so mainly through examining the validity of the individual assumptions underlying the method. Across five dynamical system models, we find that the accuracy of the one-dimensional reduction hinges on the spread of the equilibrium value of the state variable across the nodes in most cases. Specifically, the one-dimensional reduction tends to be accurate when the dispersion of the node's state is small. We also find that the correlation between the node's state and the node's degree, which is common for various dynamical systems on networks, is unrelated to the accuracy of the one-dimensional reduction.

physics.soc-ph↗

arXiv2021

Inference Methods for Interaction and Noise Intensities Using Only Spike-time Data on Coupled Oscillators

We propose theoretical methods to infer coupling strength and noise intensity simultaneously through an observation of spike timing in two well-synchronized noisy oscillators. A phase oscillator model is applied to derive formulae relating each of the parameters to some statistics from spike-time data. Using these formulae, each parameter is inferred from a specific set of statistics. We demonstrate the methods with the FitzHugh-Nagumo model as well as the phase model. Our methods do not require any external perturbation and thus are ready for application to various experimental systems.

physics.bio-ph↗

arXiv2021

Feedback-induced desynchronization and oscillation quenching in a population of globally coupled oscillators

Motivated from a wide range of applications, various methods to control synchronization in coupled oscillators have been proposed. Previous studies have demonstrated that global feedback typically induces three macroscopic behaviors: synchronization, desynchronization, and oscillation quenching. However, analyzing all of these transitions within a single theoretical framework is difficult, and thus the feedback effect is only partially understood in each framework. Herein, we analyze a model of globally coupled phase oscillators exposed to global feedback, which shows all of the typical macroscopic dynamical states. Analytical tractability of the model enables us to obtain detailed phase diagrams where transitions and bistabilities between different macroscopic states are identified. Additionally, we propose strategies to steer the oscillators into targeted states with minimal feedback strength. Our study provides a useful overview of the effect of global feedback and is expected to serve as a benchmark when more sophisticated feedback needs to be designed.

nlin.AO↗

arXiv2020

The effects of coating culture dishes with collagen on fibroblast cell shape and swirling pattern formation

Motile human-skin fibroblasts form macroscopic swirling patterns when grown to confluence on a culture dish. In this paper, we investigate the effect of coating the culture-dish surface with collagen on the resulting pattern, using human-skin fibroblast NB1RGB cells as the model system. The presence of the collagen coating is expected to enhance the adherence of the fibroblasts to the dish surface, and thereby also enhance the traction that the fibroblasts have as they move. We find that, contrary to our initial expectation, the coating does not significantly affect the motility of the fibroblasts. Their eventual number density at confluence is also unaffected. However, the coherence length of cell orientation in the swirling pattern is diminished. We also find that the fibroblasts cultured in a collagen-coated dish are rounder in shape and shorter in perimeter, compared to those cultured in an uncoated dish. We hypothesize that the rounder cell-shape which weakens the cell-cell nematic contact interaction is responsible for the change in coherence length. A simple mathematical model of the migrating fibroblasts is constructed, which demonstrates that constant motility with weaker nematic interaction strength does indeed lead to the shortening of the coherence length.

physics.bio-ph↗

arXiv2020

Noise stability of synchronization and optimal network structures

We provide a theoretical framework for quantifying the expected level of synchronization in a network of noisy oscillators. Through linearization around the synchronized state, we derive the following quantities as functions of the eigenvalues and eigenfunctions of the network Laplacian using a standard technique for dealing with multivariate Ornstein-Uhlenbeck processes: the magnitude of the fluctuations around a synchronized state and the disturbance coefficients $α_i$ that represent how strongly node $i$ disturbs the synchronization. With this approach, we can quantify the effect of individual nodes and links on synchronization. Our theory can thus be utilized to find the optimal network structure for accomplishing the best synchronization. Furthermore, when the noise levels of the oscillators are heterogeneous, we can also find optimal oscillator configurations, i.e., where to place oscillators in a given network depending on their noise levels. We apply our theory to several example networks to elucidate optimal network structures and oscillator configurations.

nlin.AO↗

arXiv2018

Partial synchronization of relaxation oscillators with repulsive coupling in autocatalytic integrate-and-fire model and electrochemical experiments

Experiments and supporting theoretical analysis is presented to describe the synchronization patterns that can be observed with a population of globally coupled electrochemical oscillators close to a homoclinic, saddle-loop bifurcation, where the coupling is repulsive in the electrode potential. While attractive coupling generates phase clusters and desynchronized states, repulsive coupling results in synchronized oscillations. The experiments are interpreted with a phenomenological model that captures the waveform of the oscillations (exponential increase) followed by a refractory period. The globally coupled autocatalytic integrate-and-fire model predicts the development of partially synchronized states that occur through attracting heteroclinic cycles between out-of-phase two-cluster states. Similar behavior can be expected in many other systems where the oscillations occur close to a saddle-loop bifurcation, e.g., with Morris-Lecar neurons.

nlin.AO↗