Synchronization Behavior Research Articles

The slow clock is the master

AbstractWe investigate the synchronization and stability of mutually coupled oscillators through small impacts and explore both master–master and master–slave synchrony. The synchronization behaviour between two oscillators, one operating at a frequency $$ \omega $$ ω and the other at a frequency near a multiple of the first one, $$ n \omega $$ n ω where $$ n $$ n is an integer greater than 1, is investigated. It is observed that such systems tend to exhibit a consistent pattern of master–slave relationship. This phenomenon is geometrically elucidated by considering the interaction dynamics: while the multiple bursts of the faster oscillator tend to cancel each other out upon impacting the slower oscillator, the single burst of the slower oscillator on the faster has a secular effect. We propose that this synchronization pattern, arising from perturbative impacts, is prevalent across various physical systems. Further experimental validation of these findings could contribute to a deeper understanding of synchronization phenomena and their implications in natural and technological domains.

Hyperscanning: from inter-brain coupling to causality

In hyperscanning studies, participants perform a joint task while their brain activation is simultaneously recorded. Evidence of inter-brain coupling is examined, in these studies, as a predictor of behavioral change. While the field of hyperscanning has made significant strides in unraveling the associations between inter-brain coupling and changes in social interactions, drawing causal conclusions between brain and behavior remains challenging. This difficulty arises from factors like the inherently different timescales of behavioral responses and measured cerebral activity, as well as the predominant focus of existing methods on associations rather than causality. Specifically, a question remains as to whether inter-brain coupling between specific brain regions leads to changes in behavioral synchrony, or vice-versa. We propose two novel approaches to addressing this question. The first method involves using dyadic neurofeedback, wherein instances of inter-brain coupling are directly reinforced. Such a system could examine if continuous changes of inter-brain coupling are the result of deliberate mutual attempts to synchronize. The second method employs statistical approaches, including Granger causality and Structural Equation Modeling (SEM). Granger causality assesses the predictive influence of one time series on another, enabling the identification of directional neural interactions that drive behavior. SEM allows for detailed modeling of both direct and indirect effects of inter-brain coupling on behavior. We provide an example of data analysis with the SEM approach, discuss the advantages and limitations of each approach and posit that applying these approaches could provide significant insights into how inter-brain coupling supports crucial processes that occur in social interactions.

The coupling dynamic characteristics and vibration suppression of a double-beam structure with two linear oscillators installed separately

This paper investigates the coupling dynamic characteristics of a double-beam structure with two linear oscillators that generate harmonic concentrated excitation and the vertical elastic support boundary, including the Sommerfeld effect and the synchronization behavior. The governing equations of motion with boundary conditions are developed using Hamilton's principle. The Sommerfeld effect near the resonance region is characterized by transient power balance analysis, and the critical power of the motor is given to allow the system to pass through the resonance region. The theoretical condition for the synchronous behavior of two linear oscillators is derived using the average method, and its stability is also determined. The synchronization characteristics are analyzed and compared with the numerical steady-state response of typical physical parameters. Results show good agreement. Further, on the condition of the linear oscillators exhibiting synchronous behavior, sensitive working regions and parameters are sought to suppress the dynamic loads transmitted from the system to the foundation. The parameter optimization results show that the stable phase difference plays a crucial role in vibration suppression within the appropriate range of sensitive parameters. This study effectively extends the theoretical criteria for synchronous behavior on complex structures and is expected to provide ideas for vibration suppression strategies of multi-driving sources acting on multi-groups of elastic structures.

Firing dynamics and coupling synchronization of memristive EMR-based Chaivlo neuron utilizing equivalent energy approach.

Firing dynamics and its energy property of neuron are crucial for exploring the mechanism of intricate information processing within the nervous system. However, the energy analysis of discrete neuron is significantly lacking in comparison to the vast literature and mature theory available on continuous neuron, thereby necessitating a focused effort in this underexplored realm. In this paper, we introduce a Chaivlo neuron map by employing a flux-controlled memristor to simulate electromagnetic radiation (EMR), and a detailed analysis of its firing dynamics is conducted based on an equivalent Hamiltonian energy approach. Our observations reveal that a range of energy-based firing behaviors, such as spike firing, coexistence firing, mixed-mode firing, and chaotic bursting firing, can be induced by EMR and injected current. To delve deeper into the synchronous firing dynamics, we establish a Chaivlo network by electrically coupling two memristive EMR-based Chaivlo neurons. Subsequently, we experimentally evaluate the synchronization behavior of this network by quantifying both the synchronization factor and the average difference of equivalent Hamiltonian energy. Our findings conclusively demonstrate that both EMR and coupling strength positively contribute to the network's synchronization ability.

Experimental study on the synchronization mechanism and trigger characteristic density of vertical evacuation in crowds.

Due to simultaneous horizontal and vertical displacement during vertical evacuation, the consequences of stampede congestion accidents can be more severe. Generally, pedestrians trigger a synchronization mechanism at some point during the vertical evacuation process. This synchronization behavior helps prevent stampede congestion and improves evacuation efficiency. This paper designs a well-controlled single-file vertical evacuation experiment. After the experiment, the video footage is imported into the TRACKER system to extract the coordinates of pedestrian step movements, after which the experimental data undergo calculations and visual analysis. The research findings indicate the following: Firstly, when the crowd coordinates trigger the synchronization mechanism, this behavior remains stable as long as pedestrian speed and direction are unchanged; Secondly, the variation in footstep speed over time is not directly related to the footstep synchronization rate of the crowd; Lastly, this study calculated the characteristic density value most likely to trigger the synchronization mechanism during vertical evacuation. This research deepens our understanding of crowd dynamics, reveals the characteristics of pedestrian movement during vertical evacuation, and proposes evacuation guidance strategies based on these features.

Synchronization of Chaotic Systems with Huygens-Like Coupling

One of the earliest reports on synchronization of inert systems dates back to the time of the Dutch scientist Christiaan Huygens, who discovered that a pair of pendulum clocks coupled through a wooden bar oscillate in harmony. A remarkable feature in Huygens’ experiment is that different synchronous behaviors may be observed by just changing a parameter in the coupling. Motivated by this, in this paper, we propose a novel synchronization scheme for chaotic oscillators, in which the design of the coupling is inspired in Huygens’ experiment. It is demonstrated that the coupled oscillators may exhibit not only complete synchronization, but also mixed synchronization—some states synchronize in anti-phase whereas other states synchronize in-phase—depending on a single parameter of the coupling. Additionally, the stability of the synchronous solution is investigated by using the master stability function approach and the largest transverse Lyapunov exponent. The Lorenz system is considered as particular application example, and the performance of the proposed synchronization scheme is illustrated with computer simulations and validated by means of experiments using electronic circuits.

Influences of short-term and long-term plasticity of memristive synapse on firing activity of neuronal network

Abstract Synaptic plasticity can greatly affect the firing behavior of neural networks, and it specifically refers to changes in the strength, morphology, and function of synaptic connections. In this paper, a novel memristor model, which can be configured as a volatile and nonvolatile memristor by adjusting its internal parameter, is proposed to mimic the short-term and long-term synaptic plasticity. Then, a bi-neuron network model, with the proposed memristor serving as a coupling synapse and the external electromagnetic radiation being emulated by the flux-controlled memristors, is established to elucidate the effects of short-term and long-term synaptic plasticity on firing activity of the neuron network. The resultant 7D neuron network has no equilibrium point and its hidden dynamical behavior is revealed by phase diagram, time series, bifurcation diagram, Lyapunov exponent spectrum and two-dimensional dynamic map. Our results show the short-term and long-term plasticity can induce different bifurcation scenarios when the coupling strength increases. In addition, memristor synaptic plasticity has a great influence on the distribution of firing patterns in the parameter space. More interestingly, when exploring the synchronous firing behavior of two neurons, the two neurons can gradually achieve phase synchronization as the coupling strength increases along the opposite directions under two different memory attributes. Finally, a microcontroller-based hardware system is implemented to verify the numerical simulation results.

Prehatch Calls and Coordinated Birth in Turtles.

Hatching synchronisation is widespread in oviparous taxa. It has been demonstrated that many species use sounds to coordinate synchronous hatching, being widespread among archosaurs (birds and crocodilians). Recent studies have shown that some turtle species produce vocalisations from within the egg, but the role of this behaviour in synchronising hatch is untested. The small amount of information about sound production by turtle embryos, limited to a handful of closely related species, precludes any inferences based on differences in their ecology, reproductive behaviour and phylogenetic context. With the goal to investigate if coordinated synchronous behaviour is mediated by within-egg vocalisations in turtles, we recorded clutches from six different turtle species. The selected animals present different ecological and reproductive niches and belong to distinct phylogenetic lineages at the family level. We aimed to understand: (1) what is the phylogenetic distribution of within-egg vocal behaviour among turtles; (2) if asynchronous turtle species vocalise from within the egg; (3) if clutch size influences synchronous behaviour and (4) if within-egg turtle calls follow any phylogenetic signal. The new evidence provides light to the current knowledge about synchronous behaviour and within-egg calls, challenging previous hypothesis that within-egg sounds are accidentally produced as side-effects of other behaviours.

Two-dimensional viscous study of coupled nonlinear fluid resonances in two narrow gaps

The wave-induced hydrodynamics of coupled nonlinear piston-mode fluid resonances within two narrow gaps between three barges are numerically investigated using a two-dimensional viscous wave flume. This study aims to explore the time-dependent nonlinear interactions between fluid oscillations in the two gaps. The coupled synchronous dynamic behaviors of fluid oscillations during the transient evolution stage are first examined in terms of amplitude and frequency modulation. It is shown that phase dynamics, including phase slipping, trapping, and locking, play significant roles in establishing the coupled synchronous dynamic evolutions of fluid oscillations in the two gaps. The quasi-steady state of the amplitude- and phase-frequency responses of fluid oscillations within the gaps, along with the reflection and transmission waves in front of and behind the three-barge system, are further analyzed. This analysis clarifies the significance of viscous damping energy dissipation and radiation damping energy transfer involved in gap resonance problems. This clarification also explains the performance of fully nonlinear potential flow solvers in predicting fluid resonances in the two narrow gaps. Finally, the nonlinear dynamic features of fluid oscillations are examined. The effects of incident wave nonlinearity, i.e., wave steepness, on resonant frequencies, response amplitudes, energy dissipation, and reflection and transmission coefficients are investigated. Harmonic analysis via Fourier transformation reveals the contributions of first-, second-, and third-order harmonics to the overall response amplitudes. The physical insights gained from this study provide a deeper understanding of the coupled nonlinear dynamics of piston-mode fluid resonances in multiple narrow gaps.

Recent achievements in nonlinear dynamics, synchronization, and networks.

This Focus Issue covers recent developments in the broad areas of nonlinear dynamics, synchronization, and emergent behavior in dynamical networks. It targets current progress on issues such as time series analysis and data-driven modeling from real data such as climate, brain, and social dynamics. Predicting and detecting early warning signals of extreme climate conditions, epileptic seizures, or other catastrophic conditions are the primary tasks from real or experimental data. Exploring machine-based learning from real data for the purpose of modeling and prediction is an emerging area. Application of the evolutionary game theory in biological systems (eco-evolutionary game theory) is a developing direction for future research for the purpose of understanding the interactions between species. Recent progress of research on bifurcations, time series analysis, control, and time-delay systems is also discussed.

Secure impulsive synchronization for derivatively coupled networks against DoS attacks: A memory-compensated strategy

This work is concerned with the synchronization issue of complex networks suffering from Denial-of-Service (DoS) attacks. The derivative coupling has been proposed to model the nodes which are capable of perceiving state changing. An overarching handling procedure is initially introduced to convert derivatively coupled dynamic networks into a general form. To offset the information missing resulting from DoS attacks, an intricately crafted memory-based self-triggered impulsive controller (MBSTIC) is devised. The introduced scheme involves the meticulous collection of nodes’ historical state information. By jointly considering Lyapunov stability theorem and mathematical deduction approach, sufficient conditions for ensuring synchronous behavior for controlled networks are derived. A numerical example is given to demonstrate that the proposed method exhibits considerable performance when facing DoS attacks.

Special Survival Strategy of First-Instar Scorpions Revealed by Synchronous Molting Behavior from Social Facilitation of Maternal Care and Reciprocal Aggregation.

Ecdysis is a well-known developmental feature among arthropods. Because the aggregate and synchronous molting of first-instar scorpions is markedly different from the common independent molting behavior of older scorpions and most arthropods, knowledge on the biological benefits of the unusual behavior of first-instar scorpions remain limited. Before the molting of newborn scorpions, their mothers exhibited a remarkable ability to efficiently locate the fallen offspring and help them climb onto their back, which was supported by strong maternal behavior because they climbed more swiftly than the 7-day postpartum scorpions. Most newborn scorpions molted and survived on the mother's back, with a survival rate of approximately 100%, and most newborn scorpions survived via aggregate molting behavior on sand in the absence of mothers (89.83% ± 1.91%). The important role of the mother scorpion was further highlighted in mothers with one to five first-instar scorpions. While all first-instar scorpions individually or reciprocally molted and survived on the mother's back, only 52.00% ± 7.14% to 79.20% ± 4.24% of newborn scorpions isolated from the mother could individually or reciprocally molt and survive on the sand, and the aggregated states of first-instar scorpions strengthened as their numbers on sand increased before molting. These results highlight collaborative molting as an evolutionary driving force for newborn scorpions. Taken together, both maternal care and collaborative aggregate molting behavior enhanced the survival of first-instar scorpions before and after molting, and these benefits for first-instar scorpions play essential and evolutionary roles in scorpion survival.

Contingency and Synchrony: Interactional Pathways Toward Attentional Control and Intentional Communication

In this article we examine how contingency and synchrony during infant–caregiver interactions help children learn to pay attention to objects and how this, in turn, affects their ability to direct caregivers’ attention and to track communicative intentions in others. First, we present evidence that, early in life, child–caregiver interactions are asymmetric. Caregivers dynamically and contingently adapt to their child more than the other way around, providing higher-order semantic and contextual cues during attention episodes, which facilitate the development of specialized and integrated attentional brain networks in the infant brain. Then, we describe how social contingency also facilitates the child's development of predictive models and, through that, goal-directed behavior. Finally, we discuss how contingency and synchrony of brain and behavior can drive children's ability to direct their caregivers’ attention voluntarily and how this, in turn, paves the way for intentional communication.

Deep brain stimulation and lag synchronization in a memristive two-neuron network

In the pursuit of potential treatments for neurological disorders and the alleviation of patient suffering, deep brain stimulation (DBS) has been utilized to intervene or investigate pathological neural activities. To explore the exact mechanism of how DBS works, a memristive two-neuron network considering DBS is newly proposed in this work. This network is implemented by coupling two-dimensional Morris–Lecar neuron models and using a memristor synaptic synapse to mimic synaptic plasticity. The complex bursting activities and dynamical effects are revealed numerically through dynamical analysis. By examining the synchronous behavior, the desynchronization mechanism of the memristor synapse is uncovered. The study demonstrates that synaptic connections lead to the appearance of time-lagged or asynchrony in completely synchronized firing activities. Additionally, the memristive two-neuron network is implemented in hardware based on FPGA, and experimental results confirm the abundant neuronal electrical activities and chaotic dynamical behaviors. This work offers insights into the potential mechanisms of DBS intervention in neural networks.

Synchronization Control of Complex Spatio-Temporal Networks Based on Fractional-Order Hyperbolic PDEs with Delayed Coupling and Space-Varying Coefficients

This paper studies synchronization behaviors of two sorts of non-linear fractional-order complex spatio-temporal networks modeled by hyperbolic space-varying PDEs (FCSNHSPDEs), respectively, with time-invariant delays and time-varying delays, including one delayed coupling. One distributed controller with space-varying control gains is firstly designed. For time-invariant delayed cases, sufficient conditions for synchronization of FCSNHSPDEs are presented via LMIs, which have no relation to time delays. For time-varying delayed cases, synchronization conditions of FCSNHSPDEs are presented via spatial algebraic LMIs (SALMIs), which are related to time delay varying speeds. Finally, two examples show the validity of the control approaches.

Abstract P103: Assessment of Angiotensin II-induced Calcium Signals in Primary Human Adrenocortical Cells

Background: Cytosolic and mitochondrial Ca 2+ concentrations are key signals for triggering the secretion of aldosterone in primary aldosteronism (PA), the most common form of secondary hypertension. Aim: To investigate [Ca 2+ ] i transients and oscillations in human CD56 + cells isolated from aldosterone producing adenoma (APA) and normal surrounding adrenocortical (AAC) cells. Methods: We assessed [Ca 2+ ] i in CD56 + APA and APA-adjacent cells (AAC) in basal conditions and after angiotensin II (Ang II) stimulation using Fura-2 dye, live confocal microscopy, and an ad hoc developed custom-made pipeline to analyze [Ca 2+ ] i signals in terms of frequency and peak parameters as amplitude, full width at half maximum (FWHM) and area under the curve (AUC). As the two-pore domain K + TASK- 2 channels are under expressed in APA, we used quinidine (20 μM), 20’ prior to [Ca 2+ ] i imaging acquisition to examine the effect of the pharmacological inhibition of this channel. Results: Resting [Ca 2+ ] i basal levels were higher in AAC (n=11) (0.75, IQR;0.90-0.56) than in APA (n=11) (0.36 IQR;0.69-0.33), (p < 0.02). We detected spontaneous Ca 2+ activity, during resting conditions, in both cell types without significant difference in peak parameters. Upon 1 nM Ang II simulation, AAC showed elevated FWHM, amplitude, and AUC peak parameters of first Ca 2+ transients. However, APA cells exhibited elevated peak parameters of subsequent Ca 2+ oscillations. Ca 2 oscillations frequency and degree of oscillating cells were significantly higher in APA cells than in AAC. After 24 hours in culture, both AAC and APA cells developed rosette-like cell structure resembling the “glomeruli” of the intact zona glomerulosa clusters. Functional Statistics and clustering analysis showed synchronous behavior of cells belonging to the same cluster without significant differences between AAC and APA. In AAC, Task-2 Inhibition with quinidine tended to increase spontaneous activity and altered peak’s parameters but did not influence frequency of oscillation. Conclusion: Quantitative assessment of [Ca 2+ ] i signals unveiled significant differences in [Ca 2+ ] i dynamics between human AAC and APA cells. These results suggest the concurrent modulation of frequency and amplitude of [Ca 2+ ] I subsequent oscillations as a potential driver of increased rate of aldosterone production.

Resonance-induced synchronization in coupled phase oscillators with bimodal frequency distribution and periodic coupling.

Synchronization behaviors in globally coupled phase oscillators with symmetric bimodal frequency distribution and periodic coupling are studied. It is found that by a proper setting of the frequency of the periodic coupling, the synchronization propensity of the oscillators can be markedly improved. Specifically, we show that when the frequency of the periodic coupling matches the distance of the central frequencies in the distribution, the critical coupling characterizing the onset of synchronization can be substantially decreased. The mechanism behind the phenomenon of periodic-coupling-enhanced synchronization is analyzed by the methods of Ott-Antonsen ansatz and synchronization transition tree, and it is revealed that the synchronization enhancement is attributed to the resonance between the synchronization clusters and the periodic coupling.

Counter-rotating synchronization theory and experiment of tri-rotor actuated with dual-frequency considering adaptive global sliding mode control strategy

In petroleum drilling engineering, self-synchronous vibration screen with single-frequency actuation is difficult to implement the scheduled synchronous behavior caused by its invariance and instability of dynamic characteristics, which usually leads to reduction of the production efficiency. Hence, to solve the problem mentioned above, a dual-frequency counter-rotating synchronization control method among three exciters is presented by combining adjacent cross-coupling control (ACCC) structure with global sliding mode control (GSMC) theory. Firstly, motion differential equation of the vibration system in each direction is derived according to mathematical model of the tri-rotor vibration machine. Secondly, considering exponential reaching law and adaptive control algorithm, the adjacent cross-coupling controller and the vector controller of each induction motor are investigated to achieve the stable zero phase difference synchronization between double-frequency rotors. Subsequently, Runge-Kutta method is introduced to establish the electromechanical coupling control model and prove validity of the control theory. Meanwhile, it is also discussed that the rotors cannot obtain an ideal self-synchronization state since velocity of high-frequency motor is not strictly equal to twice that of low-frequency motor. Finally, based on the experimental test scheme, an experimental prototype related to controlled multi-rotor synchronization vibration system is designed independently, which further verifies the validity of theory and computer simulation. Research shows that the desirable synchronous state of the vibration system can be accurately controlled via the designed control strategy, and the control system can implement diversity of the dynamical characteristics, due to the existence of strong robustness.

Chaos, synchronization, and emergent behaviors in memristive hopfield networks: bi-neuron and regular topology analysis

Chaos, synchronization, and emergent behaviors in memristive hopfield networks: bi-neuron and regular topology analysis

Higher or lower? Interpersonal behavioral and neural synchronization of movement imitation in autistic children.

How well autistic children can imitate movements and how their brain activity synchronizes with the person they are imitating have been understudied. The current study adopted functional near-infrared spectroscopy (fNIRS) hyperscanning and employed a task involving real interactions involving meaningful and meaningless movement imitation to explore the fundamental nature of imitation as a dynamic and interactive process. Experiment 1 explored meaningful and meaningless gesture imitation. The results revealed that autistic children exhibited lower imitation accuracy and behavioral synchrony than non-autistic children when imitating both meaningful and meaningless gestures. Specifically, compared to non-autistic children, autistic children displayed significantly higher interpersonal neural synchronization (INS) in the right inferior parietal lobule (r-IPL) (channel 12) when imitating meaningful gestures but lower INS when imitating meaningless gestures. Experiment 2 further investigated the imitation of four types of meaningless movements (orofacial movements, transitive movements, limb movements, and gestures). The results revealed that across all four movement types, autistic children exhibited significantly lower imitation accuracy, behavioral synchrony, and INS in the r-IPL (channel 12) than non-autistic children. This study is the first to identify INS as a biomarker of movement imitation difficulties in autistic individuals. Furthermore, an intra- and interindividual imitation mechanism model was proposed to explain the underlying causes of movement imitation difficulties in autistic individuals.