Synchronization Behavior Research Articles

Consensus in networks of uncertain euler-lagrange agents using adaptive gravity compensation

The leaderless and the leader-follower consensus are the most basic synchronization behaviors for multi-agent systems. For networks of Euler-Lagrange (EL) agents different controllers have been proposed to achieve consensus, requiring in all cases, either the cancellation or the estimation of the gravity forces. While, in the first case, it is shown that a simple Proportional plus damping (P+d) scheme with exact gravity cancellation can achieve consensus, in the latter case, it is necessary to estimate, not just the gravity forces, but the parameters of the whole dynamics. This requires the computation of a complicated regressor matrix, that grows in complexity as the degrees-of-freedom of the EL-agents increase. To simplify the controller implementation we propose in this paper a simple P+d scheme with only adaptive gravity compensation. In particular, two adaptive controllers that solve both consensus problems by only estimating the gravitational term of the agents and hence without requiring the complete regressor matrix are reported. The first controller is a simple P+d scheme that does not require to exchange velocity information between the agents but requires centralized information. The second controller is a Proportional-Derivative plus damping (PD+d) scheme that is fully decentralized but requires exchanges of speed information between the agents. Simulation results demonstrate the performance of the proposed controllers.

Physiological and Behavioral Synchrony Predict Group Cohesion and Performance

Interpersonal synchrony contributes to social functioning in dyads, but it remains unknown how synchrony shapes group experiences and performance. To this end, we designed a novel group drumming task in which participants matched their drumming to either predictable or unpredictable tempos. Fifty-one three-person groups were randomly assigned to one of two conditions: synchronized or asynchronized drumming. Outcome measures included electrocardiograms and self-reports of group cohesion and synchrony. The drumming task elicited an increase in physiological synchrony between group members (specifically their hearts’ interbeat intervals). We also found that physiological synchronization and behavioral synchronization predicted individuals’ experience of group cohesion. Physiological synchrony also predicted performance in a subsequent group task that involved freely drumming together. The findings suggest that the behavioral and physiological consequences of synchronization contribute to the formation of group bonds and coordination. They also confirm that insights from translational social neuroscience can inform our knowledge of the development of cohesive and efficacious groups.

Do familiar group mates facilitate integration into the milking group after calving in dairy cows?

As dairy cows’ needs and demands change over the different phases of their reproductive cycle, regrouping is common practice in dairy farming to facilitate management and handling. However, social instability associated with regrouping is known to have negative effects on the cows, including disturbances in their lying behaviour. In this study, we examined the effect of familiar group mates on lying time and lying synchrony in a dynamic group of approximately 50 early lactating dairy cows during 23 regrouping events. We focussed on 13 primiparous and 33 multiparous post partum cows during 24 h after their introduction to the group as compared to a matched control sample of resident cows. We hypothesised that freshly introduced cows would lie shorter and behave less synchronously with the group as compared to resident cows. Further, we hypothesised that lying duration and lying synchrony will increase with the number of familiar animals present and that these effects may depend on whether the familiarity was acquired early in life or only recently.As predicted, primiparous fresh cows lied less and behaved less synchronous at the dyadic level than their matched residents. However, no such effect was present in multiparous cows. The presence of recently familiar animals had no influence on either primiparous or multiparous cows’ behaviour. In contrast, early familiar animals affected the cows’ behaviour in several aspects, yet differently in primiparas and multiparas. In fresh primiparas, an increasing number of early familiar animals present had a negative effect on lying duration. Among both fresh and resident primiparas, early familiar dyads were more synchronized than other pairs of animals. In multiparous cows, a higher number of early familiar cows present led to more synchronous behaviour with the group.We conclude that primiparous and multiparous cows are differently affected when introduced to a lactating group after calving. Duration and synchronization of lying behaviour indicated that primiparas are strongly challenged by their entrance to the group while multiparas cope well with it. In both primiparas and multiparas, lying behaviour was affected, albeit differently, by the presence of early familiar individuals, but not by recently familiar animals. The relations between familiarity, group dynamics, behavioural synchrony and lying behaviour are complex and need deeper investigation.

Emergent conservation outcomes of shared risk perception in human-wildlife systems.

Human perception of risks related to economic damages caused by nearby wildlife can be transmitted through social networks. Understanding how sharing risk information within a human community alters the spatial dynamics of human-wildlife interactions has important implications for the design and implementation of effective conservation actions. We developed an agent-based model that simulates farmer livelihood decisions and activities in an agricultural landscape shared with a population of a generic wildlife species (wildlife-human interactions in shared landscapes [WHISL]). In the model, based on risk perception and economic information, farmers decide how much labor to allocate to farming and whether and where to exclude wildlife from their farms (e.g., through fencing, trenches, or vegetation thinning). In scenarios where the risk perception of farmers was strongly influenced by other farmers, exclusion of wildlife was widespread, resulting in decreased quality of wildlife habitat and frequency of wildlife damages across the landscape. When economic losses from encounters with wildlife were high, perception of risk increased and led to highly synchronous behaviors by farmers in space and time. Interactions between wildlife and farmers sometimes led to a spillover effect of wildlife damage displaced from socially and spatially connected communities to less connected neighboring farms. The WHISL model is a useful conservation-planning tool because it provides a test bed for theories and predictions about human-wildlife dynamics across a range of different agricultural landscapes.

The integration of social and neural synchrony: a case for ecologically valid research using MEG neuroimaging.

The recent decade has seen a shift from artificial and environmentally deprived experiments in neuroscience to real-life studies on multiple brains in interaction, coordination and synchrony. In these new interpersonal synchrony experiments, there has been a growing trend to employ naturalistic social interactions to evaluate mechanisms underlying synchronous neuronal communication. Here, we emphasize the importance of integrating the assessment of neural synchrony with measurement of nonverbal behavioral synchrony as expressed in various social contexts: relaxed social interactions, planning a joint pleasurable activity, conflict discussion, invocation of trauma, or support giving and assess the integration of neural and behavioral synchrony across developmental stages and psychopathological conditions. We also showcase the advantages of magnetoencephalography neuroimaging as a promising tool for studying interactive neural synchrony and consider the challenge of ecological validity at the expense of experimental rigor. We review recent evidence of rhythmic information flow between brains in interaction and conclude with addressing state-of-the-art developments that may contribute to advance research on brain-to-brain coordination to the next level.

AE event rate characteristics of flawed granite: from damage stress to ultimate failure

SUMMARYUniaxial compression tests with combined acousto-optical monitoring techniques are conducted on flawed granite specimens, with the aim of investigating the fracture-related acoustic emission (AE) event rate characteristics at the unstable cracking phase in flawed rocks. The interevent time (IET) function F(τ) is adopted to interpret the AE time-series from damage stress (σcd) to ultimate failure, and photographic data are used to evaluate unstable cracking behaviours in flawed granite. The results show that a high AE event rate is always registered but intermittently interrupted by macrofracturing at the unstable cracking phase. The reversed U-shaped curve relation between the AE event rate and the loading time is documented in unstable flawed granite for the first time. The acoustic quiescence has a mechanismic linkage and quantitative correlation with stress drop, and this synchronous acousto-mechanical behaviour is a typical result of the initiation, growth and coalescence of macrocracks initiated from the flaw tips. Moreover, the reactivation and intensification of fracture process zones (FPZs) by increasing loads are the dominant mechanism triggering unstable crack growth in flawed granite.

Common stochastic inputs induce neuronal transient synchronization with partial reset

Neuronal synchronization plays important roles in information encoding and transmission in the brain. Mathematical models of neurons have been widely used to simulate synchronization behavior and analyze its mechanisms. Common stochastic inputs are considered to be effective in facilitating synchronization. However, the mechanisms of how partial reset affects neuronal synchronization are still not well understood. In this paper, the synchronization of Stein’s model neurons with partial reset is studied. The differences in synchronization mechanisms between neurons with full reset and those with partial reset are analyzed, and the findings lead to the novel concept of transient synchronization. Furthermore, it is proven analytically that due to common stochastic inputs, Stein’s model neurons with different initial membrane potentials and partial reset achieve transient synchronization with probability 1. Additionally, a systematic numerical analysis is performed to explore the similarities and differences between full reset and partial reset regarding model parameters, synchronization time, and desynchronization behavior. Thus, partial reset is a powerful and flexible tool that facilitates neuronal synchronization while reserving the possibility of desynchronization. Our analysis also provides an alternative approach to analyze neurons of the integrate-and-fire family and a theoretical complement implying possible information encoding mechanisms in the brain.

Self-organizing cicada choruses respond to the local sound and light environment.

Periodical cicadas exhibit an extraordinary capacity for self‐organizing spatially synchronous breeding behavior. The regular emergence of periodical cicada broods across the United States is a phenomenon of longstanding public and scientific interest, as the cicadas of each brood emerge in huge numbers and briefly dominate their ecosystem. During the emergence, the 17‐year periodical cicada species Magicicada cassini is found to form synchronized choruses, and we investigated their chorusing behavior from the standpoint of spatial synchrony.Cicada choruses were observed to form in trees, calling regularly every five seconds. In order to determine the limits of this self‐organizing behavior, we set out to quantify the spatial synchronization between cicada call choruses in different trees, and how and why this varies in space and time.We performed 20 simultaneous recordings in Clinton State Park, Kansas, in June 2015 (Brood IV), with a team of citizen‐science volunteers using consumer equipment (smartphones). We use a wavelet approach to show in detail how spatially synchronous, self‐organized chorusing varies across the forest.We show how conditions that increase the strength of audio interactions between cicadas also increase the spatial synchrony of their chorusing. Higher forest canopy light levels increase cicada activity, corresponding to faster and higher‐amplitude chorus cycling and to greater synchrony of cycles across space. We implemented a relaxation‐oscillator‐ensemble model of interacting cicadas, finding that a tendency to call more often, driven by light levels, results in all these effects.Results demonstrate how the capacity to self‐organize in ecology depends sensitively on environmental conditions. Spatially correlated modulation of cycling rate by an external driver can also promote self‐organization of phase synchrony.

Phase reduction for FitzHugh-Nagumo neuron with large timescale separation.

Phase reduction approach is a useful tool to reduce the dimension of limit-cycle oscillators. In this paper, it is applied to the FitzHugh-Nagumo neuron model with large timescale separation. To quantitate the response of the oscillator to the external perturbations, the asymptotic behaviors of the phase sensitivity functions for fast and slow variables are obtained. It is shown that in the relaxation limit, apart from the jump points which are the vertices of the cubic nullcline, the phase is insensitive to the perturbations on the fast variable. By using the phase sensitivity functions, two cases, namely, periodic pulse train perturbation and common noise perturbation, are investigated. Theoretical and numerical results suggest better performance for the synchronization behaviors of the perturbations on the slow variable for large timescale separation.

Neural Dynamics and Gamma Oscillation on a Hybrid Excitatory-Inhibitory Complex Network (Student Abstract)

This paper investigates the neural dynamics and gamma oscillation on a complex network with excitatory and inhibitory neurons (E-I network), as such network is ubiquitous in the brain. The system consists of a small-world network of neurons, which are emulated by Izhikevich model. Moreover, mixed Regular Spiking (RS) and Chattering (CH) neurons are considered to imitate excitatory neurons, and Fast Spiking (FS) neurons are used to mimic inhibitory neurons. Besides, the relationship between synchronization and gamma rhythm is explored by adjusting the critical parameters of our model. Experiments visually demonstrate that the gamma oscillations are generated by synchronous behaviors of our neural network. We also discover that the Chattering(CH) excitatory neurons can make the system easier to synchronize.

Dominant rule of community effect in synchronized beating behavior of cardiomyocyte networks.

Exploiting the combination of latest microfabrication technologies and single cell measurement technologies, we can measure the interactions of single cells, and cell networks from "algebraic" and "geometric" perspectives under the full control of their environments and interactions. However, the experimental constructive single cell-based approach still remains the limitations regarding the quality and condition control of those cells. To overcome these limitations, mathematical modeling is one of the most powerful complementary approaches. In this review, we first explain our on-chip experimental methods for constructive approach, and we introduce the results of the "community effect" of beating cardiomyocyte networks as an example of this approach. On-chip analysis revealed that (1) synchronized interbeat intervals (IBIs) of cell networks were followed to the more stable beating cells even their IBIs were slower than the other cells, which is against the conventional faster firing regulation or "overdrive suppression," and (2) fluctuation of IBIs of cardiomyocyte networks decreased according to the increase of the number of connected cells regardless of their geometry. The mathematical simulation of this synchronous behavior of cardiomyocyte networks also fitted well with the experimental results after incorporating the fluctuation-dissipation theorem into the oscillating stochastic phase model, in which the concept of spatially arranged cardiomyocyte networks was involved. The constructive experiments and mathematical modeling indicated the dominant rule of synchronization behavior of beating cardiomyocyte networks is a kind of stability-oriented synchronization phenomenon as the "community effect" or a fluctuation-dissipation phenomenon. Finally, as a practical application of this approach, the predictive cardiotoxicity is introduced.

In and out of synchrony-Behavioral and physiological dynamics of dyadic interpersonal coordination.

Interpersonal synchrony, the temporal coordination of actions, emotions, thoughts and physiological processes, is a widely studied ubiquitous phenomenon. Research has already established that more synchrony is not always more beneficial, especially in the fields of emotional and physiological synchrony. Despite this fact, the dominant tone in the literature is that behavioral interpersonal synchrony is a pro-social phenomenon, and hence, in social contexts, more behavioral synchrony is generally considered better. In accordance with that tone, the naturally occurring dynamics of moving in and out of synchrony have rarely been studied or considered as an adaptive state. In the present article, we aim to present a new model of interpersonal synchrony, based on the existing literature assessing synchrony as well as the ideas of complex dynamical systems. At the core of our model is the idea that two tendencies exist simultaneously, one to synchronize with others and another to move out of synchrony and act independently. We suggest that an adaptive interpersonal system is a flexible one, able to continuously adjust itself to the social context. We suggest that the concept of meta-stability might be a marker of such a flexible interpersonal system. Moreover, the model considers both behavioral and physiological aspects in order to provide a more extensive account. We present research implications of the model, as well as a demonstration of the model's applicability to data, and provide code researchers can use to analyze their own data in these methods. Finally, we discuss future directions in detail.

Phase anti-synchronization dynamics between mechanical oscillator and atomic ensemble within a Fabry–Perot cavity

Phase synchronization refers to a kind of collective phenomenon that the phase difference between two or more systems is locked, and it has widely been investigated between systems with the identical physical properties, such as the synchronization between mechanical oscillators and the synchronization between atomic ensembles. Here, we investigate the synchronization behavior between the mechanical oscillator and the atomic ensemble, the systems with different physical properties, and observe a novel synchronization phenomenon, i.e., the phase sum, instead of phase difference, is locked. We refer to this distinct synchronization as the phase anti-synchronization, and show that the phase anti-synchronization can be achieved in both the classical and quantum level, which means this novel collective behavior can be tested in experiment. Also, some interesting connections between phase anti-synchronization and quantum correlation is found.

Synchrony, leadership, and association in male Indo‐pacific bottlenose dolphins (Tursiops aduncus)

AbstractMale Indo‐pacific bottlenose dolphins in Shark Bay, Western Australia, have converged with humans in the formation of nested male alliances and the use of synchrony in alliance behavior. Further, the strength of association among allied male dolphins varies and the stability of alliances correlates with the rate that males consort with estrus females (and is thus a possible indicator of dominance). To examine the possibility that synchrony reflects alliance association strength and dominance relationships, we analyzed videotapes from focal follows of two groups of males that reflect the range of alliance size and the strength of association between individuals in the population. We examined two variables: leadership during synchronous behaviors, based on which animal in a synchronously surfacing pair surfaced first, and the degree of synchrony, based on temporal differences in synchronous surfacing. We predicted that closer associates would exhibit a greater degree of synchrony and that one dolphin in a dyad would consistently lead. Contrary to our predictions, the degree of synchrony was inversely related to strength of association within alliances. This surprising result suggests that individuals with less secure bonds may strive more to achieve synchrony. We found no evidence of leadership during synchronous surfacing or between synchrony and other behavioral variables. Proximate mechanisms for synchronous behavior, such as entrainment and mutual motor imitation (“the mirror game” paradigm), may inhibit leadership in this context. Our results show that synchrony during surfacing is not a useful behavior to examine for dominance relationships in wild dolphins but it may be a useful tool to examine variation in alliance relationships.

Hidden hyperchaotic attractors in a new 4D fractional order system and its synchronization.

The research of finding hidden attractors in nonlinear dynamical systems has attracted much consideration because of its practical and theoretical importance. A new fractional order four-dimensional system, which can exhibit some hidden hyperchaotic attractors, is proposed in this paper. The predictor-corrector method of the Adams-Bashforth-Moulton algorithm and the parameter switching algorithm are used to numerically study this system. It is interesting that three different kinds of hidden hyperchaotic attractors with two positive Lyapunov exponents are found, and the fractional order system can have a line of equilibria, no equilibrium point, or only one stable equilibrium point. Moreover, a self-excited attractor is also recognized with the change of its parameters. Finally, the synchronization behavior is studied by using a linear feedback control method.

Amplification of explosive width in complex networks.

We present an adaptive coupling strategy to induce hysteresis/explosive synchronization in complex networks of phase oscillators (Sakaguchi-Kuramoto model). The coupling strategy ensures explosive synchronization with significant explosive width enhancement. Results show the robustness of the strategy, and the strategy can diminish (by inducing enhanced hysteresis loop) the contrarian impact of phase frustration in the network, irrespective of the network structure or frequency distributions. Additionally, we design a set of frequency for the oscillators, which eventually ensure complete in-phase synchronization behavior among these oscillators (with enhanced explosive width) in the case of adaptive-coupling scheme. Based on a mean-field analysis, we develop a semi-analytical formalism, which can accurately predict the backward transition of the synchronization order parameter.

Complex dynamics of coupled map lattices under random asynchronous updating

The effects of a new type of asynchronous updating on the dynamical behavior of coupled chaotic maps with nearest neighbor as well as global coupling are studied in this paper. In contrast to synchronous updating, the occurrence of the synchronized fixed point window is observed in the parameter space for nearest neighbor interactions as a consequence of asynchronous updating. Moreover, the effects of variation of the degree of asynchronocity have been investigated and it is observed that the size of the synchronized fixed point window strongly depends on the degree of asynchronocity. The value of coupling constant at the point of onset of synchronization is found analytically and the result is in good agreement with the numerics. Lattice size also has a significant impact on the synchronization behavior for some coupling function. On the other hand in a globally coupled network, synchronization is identified for a certain range of the degree of asynchronocity but surprisingly the width of synchronized fixed point window is independent of the value of the asynchronocity parameter. This study may be useful to explain the spatiotemporal order structure observed in spatially extended complex biological and social systems with the help of stochastic asynchronous updating.

Synchronization of the secondary isolation system with a dual-motor excitation

A dynamical model is proposed in this paper to study the synchronization and stability of the secondary isolation system with a dual-motor excitation. After deducing the dynamic equations of the system by Lagrange’s equation, the Laplace transform is used to deduce the displacement responses of the system when the system operate in steady state. The synchronous balance equation and stability condition of the system is derived with average method, and the relationship between the coefficient of synchronous ability and the geometric parameters of the system is discussed. It can be found that synchronization ability of the system is gradually increased with the increase between two motors mounting distance; meanwhile the larger difference of the mass between the two unbalanced rotors, the more difficult to implement synchronous operation of the system. Moreover, the stable phase difference of the vibrating system being as the key determinant to reach synchronization is discussed numerically. The research result shows that the synchronous behavior of the system is influenced by rotation direction of the rotors, mounting position of two motors, and mass ratios between unbalanced rotors and vibrating body. The correctness of theoretical analyses is verified by simulation results with Runge-Kutta method.

Theta band behavioral fluctuations synchronized interpersonally during cooperation.

Human behavior fluctuates. A growing body of evidence has demonstrated that behavioral performance in perception fluctuates rhythmically, with dynamics closely resembling spectral features of neural oscillations. However, it is unclear whether the behavioral fluctuations in a complex cooperation context can also express similar rhythmic features, and, more importantly, whether these behavioral rhythms are synchronized among co-actors in a neurophysiologically relevant manner. To answer these questions, we applied a time-resolved approach, previously used for probing individual-level behavioral oscillations in perception, in a complex social interaction context, and further probed dyad-level behavioral synchrony. Twenty pairs of male participants completed, in dyad, joint-action tasks with cooperation or competition demand. We extracted behavioral rhythms from ongoing cooperative performance and measured behavioral synchrony by computing the phase coherence of these behavioral rhythms between dyad members. Despite the absence of significant behavioral oscillations in individuals' amplitude spectrum, we observed enhanced theta-band phase coherence between co-actors' behavioral rhythms during cooperation compared to competition conditions. These results indicate that cooperative behaviors of co-actors fluctuated synchronously within the theta band, providing a behavioral counterpart of theta-band interbrain synchrony in cooperation reported in previous hyperscanning studies. Furthermore, the observed behavioral synchrony could be used as a sensitive predictor of cooperation pattern, as evidenced by its significant correlation with leader-follower relationship during cooperation.

The classical and quantum synchronization between two scattering modes in Bose–Einstein condensates

The classical and quantum synchronization between two nonlinear mechanical modes of Bose–Einstein condensates is investigated by different types of measures in order to reveal macroscopic and microscopic properties of synchronized behaviors in a closed quantum system. The classical measure synchronization (CMS) is studied by Pearson correlation coefficient, the orbital overlapping and covering areas in the phase space based on mean-value dynamical equations. The dynamical transitions of CMS are analyzed with phase diagrams in the parametric plane of population imbalance and phase difference between two modes in a wide range of mode coupling rate. Based on Husimi Q functions, the synchronized behaviors of quantum measure synchronization (QMS) are displayed by density overlapping and correlated probability dynamics in phase space, and further investigated by two quantum measures: Mari measure and mutual information. These results demonstrate that the “revival and collapse” of quantum fluctuations beyond mean-value dynamics discriminates QMS from CMS. The overwhelming dynamics of error fluctuations not only excludes complete CMS and perfect phase overlap in QMS, but also leads to upper bound to Mari measure and unceasing oscillations of mutual information. We reveal that the correlation between Mari measure and mutual information for QMS is derived from the similar dynamics of error fluctuations with respect to their opposite mean-value behaviors.