Synchronization Behavior Research Articles

Stability in star networks of identical Stuart–Landau oscillators with asymmetric coupling

In this paper, we systematically investigate the stability issues of different kinds of collective behaviors, including the equilibrium point, complete synchronization, quenched hub incoherence, anti-phase remote synchronization and regular remote synchronization, which arise in identical Stuart–Landau oscillators asymmetrically coupled in a star network. We have analytically obtained their rigorous stability conditions and stable basins, which are well verified by numerical results. Additionally, we surprisingly find that, for measuring the remote synchronization, the two traditional order parameters rdirect and rindirect are not well-defined metrics. All these results may help us to further improve our understanding of nonlinear systems’ complete, partial and cluster synchronization behaviors in real or man-made complex networks.

First-order route to antiphase clustering in adaptive simplicial complexes.

This Letter investigates the transition to synchronization of oscillator ensembles encoded by simplicial complexes in which pairwise and higher-order coupling weights alter with time through a rate-based adaptive mechanism inspired by the Hebbian learning rule. These simultaneously evolving disparate adaptive coupling weights lead to a phenomenon in that the in-phase synchronization is completely obliterated; instead, the antiphase synchronization is originated. In addition, the onsets of antiphase synchronization and desynchronization are manageable through both dyadic and triadic learning rates. The theoretical validation of these numerical assessments is delineated thoroughly by employing Ott-Antonsen dimensionality reduction. The framework and results of the Letter would help understand the underlying synchronization behavior of a range of real-world systems, such as the brain functions and social systems where interactions evolve with time.

Social impact of mara pair disruption on the formation of new bonds and reproduction in a multiple mate choice context

Maras, Dolichotis patagonum , combine social monogamy and plural breeding, an unusual mating system for mammals. We tested how maras adapt to the forced separation of pair-bonded partners and how the potential new mates perform over the breeding season and during the process of forming new pairs. Fourteen established pairs from a captive population were randomly assigned to a control (C-group; N = 7) or an experimental (E-group; N = 7) condition. The experiment consisted of replacing seven paired males with seven socially unfamiliar males (new potential mates). Individual behaviour and social interactions were recorded over a 6-month period (spring–summer; i.e. 14 sessions) from 0800 to 1800 hours, totalling 11 hourly sampling points per session. We measured pair behaviours and degree of general behavioural synchrony over sessions 1–7 (early) and over sessions 8–14 (late). We also measured how social disruption affected the social networking of individuals forming new pair bonds as compared to individuals with established mates. We furthermore assessed the level of activity of females exposed to mate switching and the production of offspring over the breeding season. In the E-group, maras showed a reduction in pair behaviours and synchronization of activities. There were also multiple interactions among females with several males, revealing initial mate choice activity during the early time period. The period of mate choice was characterized by instability in social networking and changes in the strength of a pair's fidelity. Although the E-group included five newly established pairs, offspring production was similar to that of the C-group. Our findings show that after presumably stressful experimental social disruption, most maras re-paired in captivity, although with some delay in offspring production, suggesting that this species has the plasticity to cope with male partner loss under semicontrolled environmental conditions. However, the strength of monogamous bonds was affected by this social disruption. • Pair-bonding disruption affected the behaviour of maras, D. patagonum. • Female and male interactions during mate choice caused social instability. • Most female maras were able to re-pair after the loss of their male partner. • Offspring were unaffected by social disruption during the breeding season. • Monogamy level of male–female pairs was affected by social disruption.

Effects of pairing on color change and central gene expression in lined seahorses.

Social monogamy is a reproductive strategy characterized by pair living and defense of a common territory. Pair bonding, sometimes displayed by monogamous species, is an affective construct that includes preference for a specific partner, distress upon separation, and the ability of the partner to buffer against stress. Many seahorse species show a monogamous social structure in the wild, but their pair bond has not been well studied. We examined the gene expression of lined seahorses (Hippocampus erectus) during and after the process of pairing in the laboratory as well as color change (luminance), a potential form of social communication and behavioral synchrony between pair mates. When a seahorse of either sex was interacting with its pair mate, their changes in luminance ("brightness") were correlated and larger than when interacting with an opposite-sex stranger. At the conclusion of testing, subjects were euthanized, RNA was extracted from whole brains and analyzed via RNA sequencing. Changes in gene expression in paired males versus those that were unpaired included processes governing metabolic activity, hormones and cilia. Perhaps most interesting is the overlap in gene expression change induced by pairing in both male seahorses and male prairie voles, including components of hormone systems regulating reproduction. Because of our limited sample size, we consider our results and interpretations to be preliminary, and prompts for further exploration. Future studies will expand upon these findings and investigate the neuroendocrine and genetic basis of these behaviors.

Simultaneous study of behavioral synchronization of two individuals during a cooperative task

IntroductionInterpersonally coordinated behaviors are crucial for social interactions.The “Theory of Mind,” or mentalization capacity, of an individual is essential for the establishment of behavioral synchronization. The Reading the Mind in the Eyes Test (RMET) is used to assess mentalization, social cognition and empathy. Previous RMET studies, investigated people in isolation, not in social situations. It is unclear how the RMET predicts functioning during real-life social interactions.ObjectivesTo investigate the relationship between the performance measured on the RMET test and the synchronous behavior of two individuals interacting with each other during tasks requiring social collaboration.MethodsSample included healthy controls (HC,n=48) and patients with ADHD (n=26) or schizophrenia (SCH,n=36) from an ongoing EEG-hyperscanning study, employing a social coordination condition.We applied a Go/NoGo reaction time(RT) task performed by pairs of participants. Synchronous behavior was characterized by the correlation of participants’ RTs.We used the percent (%) correct responses from the RMET to characterize social cognition.ResultsIn HC, with better social cognitive performance, the correlation of behavioral responses was significantly (p<0.05) higher. In ADHD, better performance on the RMET was also accompanied by better behavioral synchronization, but the association did not reach significance due to the smaller sample size. In SCH, no relationship was detected.ConclusionsIn HC and ADHD, the mentalization ability as measured by RMET is associated with the behavioral synchronization between individuals in social interaction.The lack of association in the schizophrenia group may be due to psychopathological symptoms, which should be elucidated in future research. Funding: Supported by the Hungarian Brain Research program#2017-1.2.1-NKP-2017-0002DisclosureNo significant relationships.

Learning-Based Sliding-Mode Control for Underactuated Deployment of Tethered Space Robot With Limited Input

This article proposes a learning-based adaptive sliding-mode control for the underactuted deployment of tethered space robot with limited input. The reduced-order system on the sliding surface is optimized by the critic neural network-based nearly optimal approximation algorithm, and both the linear and nonlinear situations are taken into account. To remove the assumption that the state-dependent disturbance is vanishing, the behavior of state synchronization on the sliding surface is revealed for the first time, and the nearly optimal solution of limited input for generating stable trajectory can be approximated by the actor neural network-based adaptive dynamic programming. The hyperbolic tangent of desired input is synthesized into the optimal value function, and it can be obtained by the actor-critic neural network-based reinforcement learning algorithm solving the corresponding Hamilton–Jacobi–Bellman equation. The numerical simulation takes the numerical example of the deployment of tethered space robot to verify the effectiveness of the proposed method.

Transient Stability of Hybrid Power Systems Dominated by Different Types of Grid-Forming Devices

This paper investigates the transient stability of power systems co-dominated by different types of grid-forming (GFM) devices. Synchronous generators (SGs and VSGs) and droop-controlled inverters are typical GFM devices in modern power systems. SGs/VSGs are able to provide inertia while droop-controlled inverters are generally inertialess. The transient stability of power systems dominated by homogeneous GFM devices has been extensively studied. Regarding the hybrid system jointly dominated by heterogeneous GFM devices, the transient stability is rarely reported. This paper aims to fill this gap. It is found that the synchronization behavior of the hybrid system can be described by a second-order motion equation, resembling the swing equation of SGs. Moreover, two significant differences from conventional power systems are discovered. The first is that the droop control dramatically enhances the damping effect, greatly affecting the transient stability region. The second is that the frequency state variable exhibits a jump at the moment of fault disturbances, thus impacting the post-fault initial-state location and stability assessment. The underlying mechanism behind the two new characteristics is clarified and the impact on the transient stability performance is analyzed and verified. The findings provide new insights into transient stability of power systems hosting heterogeneous devices.

Synchronization, extreme multistability, and its control for a field coupled neurons with time delays

Neurons are connected through synapses, but it is not reasonable to equate the connection mode of synapses to an edge in the network due to synaptic plasticity whereas the magnetic field coupling can be considered to handle it. Therefore, in this paper, the interaction between HR neurons is realized by magnetic field coupling based on induction coil, and time delay is introduced to represent the lag in information transfer. First, the coexisting firing activities and synchronization behaviors in dual neuronal networks are numerically calculated, respectively, depending on the external stimulation current, coupling strength, time delays, and initial conditions. When the time delays are given, it is interesting to note that the infinite number of firing modes including chaotic firing, periodical firing, and quiescent state is induced by initial conditions. Due to the initial values, the types of synchronization consisting of complete synchronization, delayed synchronization, and asynchronization are then revealed under the framework of extreme multistability. In particular, the state of complete synchronization exhibits only quiescent state and period-1 firing when the time delay is not equal to 0. Furthermore, the linear augmentation method is conceived to control extreme multistability. It can be found that the attractors with different positions and topological structures can be controlled to the point attractors with the same shape but with different positions when the coupling strength of linear system and nonlinear system is increased. That is, the heterogeneous multistability can be successfully controlled to the homogeneous multistability, and the coupled neurons can also be achieved synchronization after control. These conclusions in this paper could be helpful in providing new insights for studying neurodynamics and applying neural circuits.

No Evidence for Contagious Yawning in Juvenile Ravens (Corvus corax): An Observational Study.

Simple SummaryResearch suggests that contagious yawning evolved to synchronize activity and vigilance within groups. To date, yawning has shown to be contagious in a wide range of mammalian species, including humans, great apes, some monkey species, domesticated dogs and pigs, wolves, lions, and rats. However, yawn contagion has only been previously documented in one bird species: budgerigars (Melosittacus undulatus). Here, we sought to examine whether yawning was contagious among juvenile common ravens (Corvus corax). By observing two small and undisturbed captive groups, we also assessed the contagious nature of other frequently observed and potentially contagious behaviors: stretching, scratching, and shaking. Overall, we found no evidence for behavioral contagion. Given the limitations to the observational methods, however, we suggest future experimental research be conducted to support these findings.The overt and reflexive matching of behaviors among conspecifics has been observed in a growing number of social vertebrates, including avian species. In general, behavioral contagion—such as the spread of yawning—may serve important functions in group synchronization and vigilance behavior. Here, we performed an exploratory study to investigate yawn contagion among 10 captive juvenile ravens (Corvus corax), across two groups. Using observational methods, we also examined the contagiousness of three other distinct behaviors: stretching, scratching, and shaking. A total of 44 20 min observations were made across both groups, including 28 in the morning and 16 in the afternoon. The time and occurrence of all the behaviors from each bird were coded, and the temporal pattern of each behavior across both groups was then analyzed to assess the degree of social contagion. Overall, we found no evidence for contagious yawning, stretching, scratching, or shaking. However, yawns were relatively infrequent per observation (0.052 ± 0.076 yawns/bird) and thus experimental methods should be used to support this finding.

Does interpersonal liking lead to interpersonal synchrony in musical contexts?

The causal relationship of interpersonal liking affecting interpersonal synchrony is inconsistently documented. This study tests whether (a) interpersonal liking increases both behavioural and perceived synchrony and (b) people will synchronise with an agreeable partner over a competing musical stimulus. We had college students (N = 25) shake an egg-shaker with an agreeable or disagreeable confederate without music, with music, and with specific instruction to synchronise. Participants reported liking the agreeable confederate more than the disagreeable confederate and rated their relationship more positively; however, both behavioural and perceived synchrony were unaffected by the agreeableness of the confederate. Thus, we failed to replicate previous findings in an auditory only context. Furthermore, participants who believed they were more synchronised with the confederate liked the confederate more and felt more like a team, but the degree of behavioural synchrony was unrelated to these social perceptions. Perception of synchrony appears to be more important for social bonding than behavioural synchrony.

Early experience with the second generation of leadless pacemakers and correlation with ecg parameters

Abstract Funding Acknowledgements Type of funding sources: None. Background Leadless pacing has evolved as a safe and effective treatment option in selected patients. With the updated generation that allows sensing of atrial contraction, atrioventricular synchronized pacing is now possible in a VDD mode. Previous retrospective analyses have demonstrated that echocardiographic parameters may be helpful in selecting patients with a higher chance of good atrioventricular synchronous pacing behaviour. Purpose Analysis of the early experience with the second generation of leadless pacemaker and the role of ECG parameters to predict a good atrial contraction signal (so-called A4 amplitude) in patients who underwent leadless pacemaker implantation in four tertiary centres. Methods and Results In this retrospective analysis, a total of 136 patients were included. Mean age was 78.0 (64.7 - 84.2 years) years with 48.9 % being male. Coronary artery disease was the leading underlying heart disease with 27.1 % affected patients. 61.7 % of the population suffered from sinus rhythm with complete or intermittent atrioventricular block. The majority of devices were implanted at the mid-septal (61.2 %) or high-septal (25.6 %) right ventricle, respectively. Electrical parameters were optimal at implant (Table 1) and remained stable over time (Table 1). In addition, A4 signal amplitude remained stable too during follow-up compared to the value early after implantation (Table 1). From this entire cohort, patients with an ECG available at implant and those in which the device was working predominantly in the VDD mode were selected for further analyses (62 patients). PR interval measured from the ECG prior to implantation did not correlate with the A4 signal amplitude (Figure 1A; P = NS). Next, P wave amplitudes were measured in all 12 ECG leads. There was a correlation between P wave amplitude from lead V2 with the A4 amplitude (Figure 1B; P = 0.034, R2 = 0.09), whereas the other right-sided ECG leads (V1/aVR), either alone or in combination, did not correlate with the A4 signal amplitude (P = NS). Conclusions In our cohort of patients with the second generation of leadless pacemakers, offering VDD pacing, good electrical parameters can be achieved as it has been observed with the first generation. Also the A4 signal amplitude as a marker for atrial contraction remains stable over time. In regard to ECG parameters measured prior to device implantation, only the P wave amplitude in lead V2 correlated with a amplitude of the A4 signal.

Topology identification and dynamical pattern recognition for Hindmarsh–Rose neuron model via deterministic learning

Studies have shown that Parkinson’s, epilepsy and other brain deficits are closely related to the ability of neurons to synchronize with their neighbors. Therefore, the neurobiological mechanism and synchronization behavior of neurons has attracted much attention in recent years. In this contribution, it is numerically investigated the complex nonlinear behaviour of the Hindmarsh–Rose neuron system through the time responses, system bifurcation diagram and Lyapunov exponent under different system parameters. The system presents different and complex dynamic behaviors with the variation of parameter. Then, the identification of the nonlinear dynamics and topologies of the Hindmarsh–Rose neural networks under unknown dynamical environment is discussed. By using the deterministic learning algorithm, the unknown dynamics and topologies of the Hindmarsh–Rose system are locally accurately identified. Additionally, the identified system dynamics can be stored and represented in the form of constant neural networks due to the convergence of system parameters. Finally, based on the time-invariant representation of system dynamics, a fast dynamical pattern recognition method via system synchronization is constructed. The achievements of this work will provide more incentives and possibilities for biological experiments and medical treatment as well as other related clinical researches, such as the quantifying and explaining of neurobiological mechanism, early diagnosis, classification and control (treatment) of neurologic diseases, such as Parkinson’s and epilepsy. Simulations are included to verify the effectiveness of the proposed method.

Maternal anxiety symptoms associated with increased behavioral synchrony in the early postnatal period.

The presence of perinatal mood and anxiety disorders has typically been associated with decreases in the quality of mother-infant interactions. However, maternal anxiety symptoms during the postpartum period have been less studied than other mental health disorders like depression. In the current study, we examined associations among symptoms of maternal anxiety, maternal perceived stress, and mother-infant behavioral synchrony in the early postnatal period. Eighty-one mother-infant dyads participated in this study when the infants were 3months old. Surveys were given to obtain demographic information and current maternal mental health symptoms, and dyads completed a 5-min free-play task to measure behavioral synchrony. Results indicated that maternal anxiety symptoms were positively associated with behavioral synchrony, but only for mothers reporting moderate levels of perceived stress. These findings highlight the differential impact of maternal postpartum mental health on behavioral synchrony and suggest that higher maternal anxiety symptoms during the postnatal period may play an adaptive role in fostering more dynamic mother-infant interactions.

Memristive Izhikevich Spiking Neuron Model and Its Application in Oscillatory Associative Memory.

The Izhikevich (IZH) spiking neuron model can display spiking and bursting behaviors of neurons. Based on the switching property and bio-plausibility of the memristor, the memristive Izhikevich (MIZH) spiking neuron model is built. Firstly, the MIZH spiking model is introduced and used to generate 23 spiking patterns. We compare the 23 spiking patterns produced by the IZH and MIZH spiking models. Secondly, the MIZH spiking model actively reproduces various neuronal behaviors, including the excitatory cortical neurons, the inhibitory cortical neurons, and other cortical neurons. Finally, the collective dynamic activities of the MIZH neuronal network are performed, and the MIZH oscillatory network is constructed. Experimental results illustrate that the constructed MIZH spiking neuron model performs high firing frequency and good frequency adaptation. The model can easily simulate various spiking and bursting patterns of distinct neurons in the brain. The MIZH neuronal network realizes the synchronous and asynchronous collective behaviors. The MIZH oscillatory network can memorize and retrieve the information patterns correctly and efficiently with high retrieval accuracy.

Transient Synchronization Stability Improvement Control Strategy for Grid-Connected VSC Under Symmetrical Grid Fault

Under grid fault, the grid-connected voltage source converters (VSCs) have the risk of transient synchronization instability during low voltage ride through. Based on the equivalent rotor swing equation of VSC, this letter proposes an improved transient synchronization stability control strategy, which improves the existence of equilibrium points and transient synchronization behaviors of the VSC system. Thus, the transient synchronization stability of grid-connected VSC can be significantly enhanced. The simulation and experimental results demonstrate the validity of the proposed strategy.

Dynamics of particle network in composite battery cathodes

Improving composite battery electrodes requires a delicate control of active materials and electrode formulation. The electrochemically active particles fulfill their role as energy exchange reservoirs through interacting with the surrounding conductive network. We formulate a network evolution model to interpret the regulation and equilibration between electrochemical activity and mechanical damage of these particles. Through statistical analysis of thousands of particles using x-ray phase contrast holotomography in a LiNi0.8Mn0.1Co0.1O2-based cathode, we found that the local network heterogeneity results in asynchronous activities in the early cycles, and subsequently the particle assemblies move toward a synchronous behavior. Our study pinpoints the chemomechanical behavior of individual particles and enables better designs of the conductive network to optimize the utility of all the particles during operation.

Control of Flow–Acoustic Resonance Using Sweeping Jets

This study proposes a sweeping jet as a novel solution to control catastrophic flow–acoustic resonance through a combined experimental and scale-adaptive simulation (SAS) strategy. The relationships between resonance intensity and the geometry of the dual sweeping-jet controllers (SJCs) and mass ratio of the jet flow to mainstream flow were established by the wall-pressure measurements. The system with dual SJCs at two upstream channel–branch intersections with spanwise jet sweeping achieved the best control performance at the low mass ratio of . Through complementary simulations, self-sustained unsteady flow dynamics within dual SJCs, strong flow–acoustic resonance within the channel–branch system and complete suppression of the aeroacoustic field by the most efficient dual SJCs were demonstrated. The simulation results were first validated in terms of the frequency and amplitude information of the experimentally measured wall-pressure fluctuations. Subsequently, a proper orthogonal decomposition analysis was conducted and a large-scale synchronous sweeping behavior was observed when the jet flow proceeded from the fluidic oscillators to the free space. Thereafter, SAS results revealed the dual SJCs could remarkably attenuate velocity fluctuations, shear-layer momentum thickness, and Reynolds and Lighthill stresses. These improvements were achieved by completely suppressing the large-scale shear-layer vortex shedding into a series of horseshoe vortices.

Adaptive quantitative control for robust [formula omitted] synchronization between multiplex neural networks under stochastic cyber attacks

In this paper, to resist stochastic cyber attacks and suppress the influence of the exogenous disturbance in synchronization of multiplex neural networks, an adaptive quantization control strategy is proposed. To overcome uncertainties and represent constraints in communication, an adaptive quantitative controller is designed, which is used to arrive outer synchronized behavior with an H∞ performance between the multiplex neural networks under stochastic cyber attacks and exogenous disturbance. The node of the multiplex networks is neural networks which is named neural sub-networks. It is assumed that the neural sub-networks in the multiplex networks with delay topology are coupled by nonlinear functions. Based on Lyapunov stability method, the conditions for the multiplex networks to achieve synchronization with an H∞ performance are presented. Finally, numerical example illustrates the effective of the theoretical framework.

Synchronization behaviors of a vibrating mechanical system with adjustable frequencies and motion trajectories

In present work, the double and triple-frequency synchronization behaviors of a vibrating mechanical system with two different driving frequencies, driven by three reversed rotating exciters, are investigated by theory, numeric, and experiment. Based on Lagrange’s equations, the dynamic model corresponding to vibrating machine is proposed and motion differential equations are constructed. The Bogoliubov standard formal equations for three exciters are established, by introducing the asymptotic method, in which the synchronization problem is converted into that of the existence and stability of zero-valued solution of the average differential equations. The synchronization criterion of satisfying the synchronous operation is deduced. According to the Routh–Hurwitz criterion, the stability criterion of the synchronous states is achieved analytically. Based on the obtained theory results, the stability characteristics of the system, are numerically discussed in detail, including the stability ability coefficients and stable phase differences. Finally, simulations and experiments under the condition of two different driving frequencies, are performed to further examine the validity of the theoretical and numerical qualitative results. The present work can provide a theoretical reference for designing some new types of the vibrating machines with adjustable frequencies and motion trajectories.

Stochastic synchronization in nonlinear network systems driven by intrinsic and coupling noise

In this paper, we consider a noisy network of nonlinear systems in the sense that each system is driven by two sources of state-dependent noise: (1) an intrinsic noise that can be generated by the environment or any internal fluctuations and (2) a noisy coupling which is generated by interactions with other systems. Our goal is to understand the effect of noise and coupling on synchronization behaviors of such networks. First, we assume that all the systems are driven by a common noise and show how a common noise can be detrimental or beneficial for network synchronization behavior. Then, we assume that the systems are driven by independent noise and study network approximate synchronization behavior. We numerically illustrate our results using the example of coupled Van der Pol oscillators.