Synchronization Behavior Research Articles

Perceiving Social Cohesion: Movement Synchrony and Task Demands Both Matter.

Previous research has shown that interpersonal synchrony is associated with a number of prosocial effects. We investigated the respective roles of behavioural synchrony and perceived task demands on perceptions of cohesion by performing two experiments in which participants viewed pairs of point-light figures engaging in four coordinated behaviours. Behaviours were seen twice, once in perfect in-phase synchrony and once with synchrony manipulated (phase shift: 180° in Experiment 1 and 45°, 90°, 270°, and 315° in Experiment 2). Dyads were rated on perceived exertion and perceived social cohesion. Results indicate that in-phase synchrony is associated with higher levels of perceived cohesion and that perceived exertion is a good predictor of cohesion ratings. Two interactions suggest that the effect is not purely perceptual and that participants observing coordinated movement also make inferences about the intentions of those observed. Results are discussed and future directions suggested.

Investigating the relationship between behavioral synchrony and dimensions of interpersonal attraction: Why task attraction rises above the others.

Investigating the relationship between behavioral synchrony and dimensions of interpersonal attraction: Why task attraction rises above the others.

Phase synchronization and intermittent behavior in healthy and Alzheimer-affected human-brain-based neural network

We study the dynamical proprieties of phase synchronization and intermittent behavior of neural systems using a network of networks structure based on an experimentally obtained human connectome for healthy and Alzheimer-affected brains. We consider a network composed of 78 neural subareas (subnetworks) coupled with a mean-field potential scheme. Each subnetwork is characterized by a small-world topology, composed of 250 bursting neurons simulated through a Rulkov model. Using the Kuramoto order parameter we demonstrate that healthy and Alzheimer-affected brains display distinct phase synchronization and intermittence properties as a function of internal and external coupling strengths. In general, for the healthy case, each subnetwork develops a substantial level of internal synchronization before a global stable phase-synchronization state has been established. For the unhealthy case, despite the similar internal subnetwork synchronization levels, we identify higher levels of global phase synchronization occurring even for relatively small internal and external coupling. Using recurrence quantification analysis, namely the determinism of the mean-field potential, we identify regions where the healthy and unhealthy networks depict nonstationary behavior, but the results denounce the presence of a larger region or intermittent dynamics for the case of Alzheimer-affected networks. A possible theoretical explanation based on two locally stable but globally unstable states is discussed.

Phase-locking particle image velocimetry measurement of unsteady flow behaviors: Online dynamic mode decomposition using field-programmable gate array

A novel online dynamic mode decomposition (DMD) approach using a field-programmable gate array (FPGA), which takes full advantage of the DMD to extract multiple unsteady events and the FPGA system for signal sampling and fast computation, was developed for phase-locking particle image velocimetry (PIV) measurements of unsteady flow behaviors. The turbulent separated and reattaching flow around a finite blunt plate with a length-to-height-ratio L/D = 6.0 was examined to demonstrate this novel approach. The wall-pressure field and the velocity field were measured using arrayed microphones and the conventional planar PIV setup, respectively. Offline DMD analysis of the wall-pressure fluctuation field was first used to identify the dominant modes corresponding to the energetically unsteady events. For each mode, the eigenmode and its mode coefficient reflected the spatial footprint pattern and temporal strength of the unsteady event, respectively. Next, trained machine learning of the mode coefficient was used to establish a phase prediction strategy. Finally, in the online analysis, the relevant eigenmode was cast into the FPGA device to serve as the reference mode for reconstruction with the sampled wall-pressure data, determining the phase signal to fire the PIV setup. High-resolution spatiotemporal evolutions of the dominant flow structures (i.e., the flapping separation bubble, the impinging leading-edge vortex, and the trailing-edge vortex street) were separately assembled. Further measurements demonstrated a clear panoramic view of the synchronous behavior of the enlarging separation bubble and the impinging leading-edge vortex. The proposed online FPGA-DMD approach can serve as a sophisticated strategy for phase-locking PIV measurements of unsteady flow behaviors.

Forced synchronization and asynchronous quenching of periodic oscillations in a thermoacoustic system

We perform an experimental and theoretical study to investigate the interaction between an external harmonic excitation and a self-excited oscillatory mode ($f_{n0}$) of a prototypical thermoacoustic system, a horizontal Rijke tube. Such an interaction can lead to forced synchronization through the routes of phase locking or suppression. We characterize the transition in the synchronization behaviour of the forcing and the response signals of the acoustic pressure while the forcing parameters, i.e. amplitude ($A_{f}$) and frequency ($f_{f}$) of forcing are independently varied. Further, suppression is categorized into synchronous quenching and asynchronous quenching depending upon the value of frequency detuning ($|\,f_{n0}-f_{f}|$). When the applied forcing frequency is close to the natural frequency of the system, the suppression in the amplitude of the self-excited oscillation is known as synchronous quenching. However, this suppression is associated with resonant amplification of the forcing signal, leading to an overall increase in the response amplitude of oscillations. On the other hand, an almost 80 % reduction in the root mean square value of the response oscillation is observed when the system is forced for a sufficiently large value of the frequency detuning (only for$f_{f}<f_{n0}$). Such a reduction in amplitude occurs due to asynchronous quenching where resonant amplification of the forcing signal does not occur, as the frequency detuning is significantly high. Further, the results from a reduced-order model developed for a horizontal Rijke tube show a qualitative agreement with the dynamics observed in experiments. The relative phase between the acoustic pressure ($p^{\prime }$) and the heat release rate ($\dot{q}^{\prime }$) oscillations in the model explains the occurrence of maximum reduction in the pressure amplitude due to asynchronous quenching. Such a reduction occurs when the positive coupling between$p^{\prime }$and$\dot{q}^{\prime }$is disrupted and their interaction results in overall acoustic damping, although both of them oscillate at the forcing frequency. Our study on the phenomenon of asynchronous quenching thus presents new possibilities to suppress self-sustained oscillations in fluid systems in general.

Alpha band signatures of social synchrony

Previous research has reported changes in mu rhythm, the central rhythm of the alpha frequency band, in both intentional and spontaneous interpersonal coordination. The current study was designed to extend existing findings on social synchrony to the pendulum swinging task and simultaneously measured time unfolding behavioral synchrony and EEG estimation of mu activity during spontaneous, intentional in-phase and intentional anti-phase interpersonal coordination. As expected, the behavioral measures of synchrony demonstrated the expected pattern of weak synchronization for spontaneous coordination, moderate synchronization for intentional anti-phase coordination, and strong synchronization for in-phase coordination. With respect to the EEG measures, we found evidence for mu enhancement for spontaneous coordination in contrast to mu suppression for intentional coordination (both in phase and anti-phase), with higher levels of synchronization associated with higher levels of mu suppression in the right hemisphere. The implications of the research findings and methodology for understanding the underlying mechanisms contributing to social problems in psychological disorders, leader-follower relationships, and inter-brain dynamics are discussed.

Enhancing network cluster synchronization capability based on artificial immune algorithm

With the deeper study on complex networks, more and more attention has been paid to the research on the cluster synchronization phenomena based on complex networks. In the real world, synchronization phenomena or cluster synchronous behaviors occur frequently, some of which may result in larger negative impacts to the society, such as “cadmium rice event,” while others bring significant economic benefits to the society, such as the synchronization of the propaganda for “black Friday.” Therefore, research on cluster synchronism has great values for theoretical study and social applications. Currently, the study of cluster synchronicity is focused on the solution of the synchronization threshold and the analysis of the synchronization phenomenon, etc. However, the optimization to enhance the synchronous evolutionary effect is rarely presented in literatures. To overcome these limitations of current work, we explore the optimization of network structure with artificial immune algorithms under the condition of a constant network scale and finally realize the promotion of synchronous evolution effect in this paper. Moreover, the relevant research results are applied to real cases. On one hand, for the positive synchronous behaviors, the network structure with good synchronization capability is created to achieve better synchronization. On the other hand, the connection between nodes and edges in the network is cut off to avoid the occurrence of negative synchronous behaviors.

Low-Power Microwave Relaxation Oscillators Based on Phase-Change Oxides for Neuromorphic Computing

Neuro-inspired computing architectures are one of the leading candidates to solve complex, large-scale associative learning problems. The two key building blocks for neuromorphic computing are the synapse and the neuron, which form the distributed computing and memory units. Solid state implementations of these units remain an active area of research. Specifically, voltage or current controlled oscillators are considered a minimal representation of neurons for hardware implementations. Such oscillators should demonstrate synchronization and coupling dynamics for demonstrating collective learning behavior, besides the desirable individual characteristics such as scaling, power, and performance. To this end, we propose the use of nanoscale, epitaxial heterostructures of phase change oxides and oxides with metallic conductivity as a fundamental unit of an ultralow power, tunable electrical oscillator capable of operating in the microwave regime. Our simulations show that optimized heterostructure design with low thermal boundary resistance can result in operation frequency of up to 3 GHz and power consumption as low as 15 fJ/cycle with rich coupling dynamics between the oscillators.

On the Influence of Structural Connectivity on the Correlation Patterns and Network Synchronization

Since brain structural connectivity is the foundation of its functionality, in order to understand brain abilities, studying the relation between structural and functional connectivity is essential. Several approaches have been applied to measure the role of the structural connectivity in the emergent correlation/synchronization patterns. In this study, we investigates the cross-correlation and synchronization sensitivity to coupling strength between neural regions for different topological networks. We model the neural populations by a neural mass model that express an oscillatory dynamic. The results highlight that coupling between neural ensembles leads to various cross-correlation patterns and local synchrony even on an ordered network. Moreover, as the network departs from an ordered organization to a small-world architecture, correlation patterns, and synchronization dynamics change. Interestingly, at a certain range of the synaptic strength, by fixing the structural conditions, different organized patterns are seen at the different input signals. This variety switches to a bifurcation region by increasing the synaptic strength. We show that topological variations is a major factor of synchronization behavior and lead to alterations in correlated local clusters. We found the coupling strength (between cortical areas) to be especially important at conversions of correlation and synchronization states. Since correlation patterns generate functional connections and transitions of functional connectivity have been related to cognitive operations, these diverse correlation patterns may be considered as different dynamical states corresponding to various cognitive tasks.

Music, rowing, and the aesthetics of rhythm

ABSTRACTHaving “good rhythm” is essential in both music and competitive rowing, but what exactly constitutes “good rhythm,” and how do we achieve it? Although rhythm is often discussed in purely auditory terms, I argue that rhythm is fundamentally a multisensory, kinesthetic phenomenon. By drawing parallels between music and rowing, I illustrate how biological motion principles underlie the parameters of rhythm in both disciplines, and how the cognition and appreciation of rhythm is deeply embodied. I suggest that the two main ways in which rhythms generate pleasure in both music and rowing are by enabling behavioral synchrony between individuals, and by engaging the body in the cognitive process of rhythm perception and prediction. In essence, “good rhythm”—a rhythm that is enjoyed and appreciated—is rhythm that moves.

Developmental social pragmatic interventions for preschoolers with autism spectrum disorder: A systematic review

Background and aims Developmental social pragmatic interventions are one treatment option for supporting the social communication and language skills of preschool children with autism spectrum disorder. Our first aim was to differentiate interventions using a developmental social pragmatic model from other developmental or naturalistic behavioral approaches. We applied explicit criteria outlining core features of developmental social pragmatic interventions to identify programs that use these core features. We then systematically reviewed studies examining the impact of developmental social pragmatic interventions in supporting (a) foundational social communication and language skills of preschool children with autism spectrum disorder and (b) caregiver interaction style. Additionally, we reviewed results exploring mediators and potential factors influencing children’s response to developmental social pragmatic interventions. Methods A multistep comprehensive search strategy was used to identify developmental social pragmatic treatments and studies examining their effectiveness for preschool children with autism spectrum disorder. The characteristics of each study and their outcomes were then reviewed, and a modified Critical Appraisal Skills Programme tool was used to evaluate rigor. Main contribution/Results Six interventions that met criteria to be classified as developmental social pragmatic are examined within this review. Ten studies of varying methodological rigor met criteria for inclusion and collectively reported on the outcomes of 716 preschool-aged children with autism spectrum disorder. All of the studies examined foundational communication outcomes and all but one reported positive outcomes for at least one of the measures. Seven studies examined language outcomes. While results were positive for language use within natural contexts, they were mixed for overall, receptive, and expressive language. Parents’ interaction styles significantly changed postintervention, namely in terms of increased responsiveness, synchronous behavior, use of affect, and decreased directiveness. Only two studies conducted formal mediation analysis and found that parent responsiveness and synchronous behavior were related to children’s positive response to treatment. Conclusions This review suggests that developmental social pragmatic treatments positively impact children’s foundational communication capacities (i.e. attention, social referencing, joint attention, initiation, reciprocity). Positive findings were not consistently found for supporting children’s language. Further, methodologically rigorous studies are needed to draw definitive conclusions. Additional research exploring components of developmental social pragmatic treatments that might mediate response to treatment is needed. Implications This review provides synthesized information for clinicians, families, and researchers on the effectiveness of developmental social pragmatic interventions for improving children’s foundational communication. It also suggests directions for future research and provides ideas for enhancing methodological rigor and promoting more homogeneity among treatment implementation and outcome assessments.

Brain Rhythm Sequencing Using EEG Signals: A Case Study on Seizure Detection

A technique based on five brain rhythms (δ, θ, α, β, and y) presented in the sequence for analyzing Electroencephalography (EEG) signals has been proposed. First, the production of the sequence has been accomplished by selecting the prominent brain rhythm having the maximum instantaneous power at specific timestamp consecutively throughout the EEG. To this purpose, the reassigned smoothed pseudo Wigner-Ville distribution (RSPWVD) has been employed. Then, in order to verify the proposed technique and evaluate its performance, a case study of seizure detection has been implemented. As experimental validation, 93 patients from the Karunya database have been investigated. Moreover, to characterize the brain rhythm sequence for seizure detection, two additional indices derived from the power discharge and synchronous behavior have been applied. Results show that the particular rhythm pattern during the seizure is usually one type (either δ, θ, or α) and it is subject-dependent. Hence, by focusing on the changes of such particular rhythm through the two indices, the time-related occurrences of seizures can be determined in detail. Meanwhile, the representative channels for seizure detection can be found by studying the similarity of sequences, which are helpful to reduce the number of applied channels. Finally, the proposed technique provides an accuracy of 98.9%, which demonstrates it is competent to detect the appearances of abnormal seizures from the EEG signals reliably. Consequently, the brain rhythm sequencing could open a new way to interpret and characterize the EEG in various applications such as for epileptic patients.

Electrohydrodynamic 3D printing of layer-specifically oriented, multiscale conductive scaffolds for cardiac tissue engineering.

Mimicking the hierarchical microarchitecture of native myocardium in vitro plays an important role in cardiac tissue engineering. Here we present a novel strategy to produce multiscale conductive scaffolds with layer-specific fiber orientations for cardiac regeneration by combining solution-based and melt-based electrohydrodynamic (EHD) printing techniques. Polycaprolactone (PCL) microfibers were printed by melt-based EHD printing and the fiber orientation was flexibly controlled in a layer-by-layer manner according to user-specific design. The as-printed microfibrous scaffolds can provide the seeded cells necessary contact cues to guide layer-specific cellular alignments. Sub-microscale conductive fibers were simultaneously incorporated inside the well-organized PCL scaffolds by solution-based EHD printing, which significantly improved the conductivity as well as the cellular adhesion and proliferation capacity. The multiscale conductive scaffolds can further direct the multiple-layer alignments of primary cardiomyocytes and facilitate cardiomyocyte-specific gene expressions, which exhibited enhanced synchronous beating behavior compared with pure microfibrous scaffolds. It is envisioned that the proposed hybrid EHD printing technique might provide a promising strategy to fabricate multifunctional micro/nanofibrous scaffolds with biomimetic architectures, electrical conductivity and even biosensing properties for the regeneration of electroactive tissues.

Behavior of a network of heterogeneous Liénard systems under strong output coupling

In this paper, to participate in the understanding of a biological system, we analyze the synchronous and oscillatory behavior of coupled Liénard systems. In particular, we will consider a network of heterogeneous Liénard systems under output diffusive coupling to take into account two fundamental characteristics of a biological system. The key idea in this work is to emphasize the role of a network, which introduces an emergent behavior that each individual element approximately follows, hence making elements approximately synchronize. The intuition comes from a series of developments recently made in the name of ‘blended dynamics,’ and thus, the common philosophy of ‘blended dynamics’ approach enables us to illustrate a biological phenomenon that collective behavior is preserved even when there are some malfunctioning elements.

Complex Synchronization of a Ring-Structured Network of FitzHugh-Nagumo Neurons With Single-and Dual-State Gap Junctions Under Ionic Gates and External Electrical Disturbance

Synchronization plays an essential role in processing information and decisions by neurons and their networks in the brain, and it is useful to study the synchronization of neuron networks, as a part of the process of understanding the functionality of both healthy and diseased brains. In the past, most studies had developed control schemes relating to synchronization problems which were limited to two or three neurons, which cannot depict the dynamic synchronization behavior of neuron networks. In this paper, we investigated the synchronization issues associated with a ring-structured network of FitzHugh-Nagumo (FHN) neurons, under external electrical stimulation, and with single- and dual-state gap junctions. In addition, the gap junctions (coupling)s and ionic gate disturbances were included in the dynamics of this FHN neuronal network, making our work both more realistic, and more challenging. Thus, each neuron in this network was influenced synaptically by its neighboring two neurons. A simple, robust, and adaptive control scheme, for both a single- and the dual-gap-junction network has been proposed, which will compensate for the nonlinear dynamics without direct cancelation to achieve synchronization. Sufficient conditions to guarantee synchronization of both membrane potentials and recovery variables were derived by using Lyapunov stability theory. Finally, the proposed scheme was validated, and its efficacy was comprehensively analyzed through numerical simulations.

Transient synchronisation and quantum coherence in a bio-inspired vibronic dimer.

Synchronisation is a collective phenomenon widely investigated in classical oscillators and, more recently, in quantum systems. However it remains unclear what features distinguish synchronous behaviour in these two scenarios. Recent works have shown that investigating synchronisation dynamics in open quantum systems can give insight into this issue. Here we study transient synchronisation in a bio-inspired vibronic dimer, where electronic excitation dynamics is mediated by coherent interactions with intramolecular vibrational modes. We show that the synchronisation dynamics of local mode displacements exhibit a rich behaviour which arises directly from the distinct time-evolutions of different vibronic quantum coherences. Furthermore, our study shows that coherent energy transport in this bio-inspired system is concomitant with the emergence of positive synchronisation between mode displacements. Our work provides further understanding of the relations between quantum coherence and synchronisation in open quantum systems and suggests an interesting role for coherence in biomolecules, that of promoting synchronisation of vibrational motions driven out of thermal equilibrium.

Synchronization Control in Reaction‐Diffusion Systems: Application to Lengyel‐Epstein System

Synchronization and control in high dimensional spatial‐temporal systems have received increasing interest in recent years. In this paper, the problem of complete synchronization for reaction‐diffusion systems is investigated. Linear and nonlinear synchronization control schemes have been proposed to exhibit synchronization between coupled reaction‐diffusion systems. Synchronization behaviors of coupled Lengyel‐Epstein systems are obtained to demonstrate the effectiveness and feasibility of the proposed control techniques.

Firefly-Inspired Time Synchronization Mechanism for Self-Organizing Energy-Efficient Wireless Sensor Networks: A Survey

One major issue faced by Wireless Sensor Network (WSN), which is based on pulsecoupled oscillators (PCOs) is the energy consumption and loss of data due to the deafness, high packet collision and high power in the application. Therefore, to overcome this problem this research proposes a technique for the efficient minimization of energy usage among WSNs, particularly during transmission scheduling (sender state) for time synchronization in WSNs. Specifically, the current work focuses on three decentralized methods of energy efficiency with scalability and robustness. Among the mechanisms used is the traveling wave pulse coupled oscillator (TWPCO), which is a self-organizing technique for energy efficient WSNs by adopting a traveling wave phenomenon based on phase locking of the PCO model regarding sensor nodes as observed in the flashing synchronization behaviors of fireflies and secretion of radio signals as firing to counteract deafness. The second mechanism is a self-organizing energy efficiency pulse coupled oscillator (EEPCO) mechanism for WSNs, which combines both the biologically inspired and non-biologically inspired network systems to counteract packet collision. The third proposed mechanism is the random traveling wave pulse coupled oscillator (RTWPCO), which reduces high-power to the smallest level by using phase-locking travelling wave in biologically inspired of the PCO model and random method based on anti-phase in non-biologically inspired of the PCO model. The performances of the proposed algorithms were studied using a simulation analysis. The results showed significant improvement in terms of reaching the steady state after a certain number of cycles, obtaining superior data gathering ratio, and reducing the energy consumption ratio of sensor nodes. Specifically, the TWPCO mechanism showed superior performance compared to other mechanisms with a deduction on the total energy consumption by 25 %, while improving the performance by 13 % in terms of data gathering. On the other hand, the EEPCO mechanism improved data collection by up to 100% when the number of sensor nodes is below 40. In such a scenario, the energy efficiency also improved by up to 15%. Finally, the proposed RTWPCO mechanism achieved up to 53% and 60% reduction in the energy usage mainly due to the increase in the number of sensor nodes as well as the increase in the data packet size of the transmitted data. In addition, the mechanism improved the data gathering ratio by up to 75% and 73% respectively. These mechanisms help to avoid deafness that occurs in the transmit state in WSNs, to counteract packet collision during transmission in WSNs and minimize the high-power utilization in the network and as well increase the data collection throughout the transmission states in WSNs.

Synchronization Cost of Coupled Oscillators With a Spatial Embedding

Synchronous behavior brings advantages for complex systems. Yet, this advantage comes with a cost: Emergence and sustainability of synchronization requires a continuous exchange among the interacting units. Thus, networks with optimal synchronization dynamics is a subject of active research. In this study, we define a cost function for synchronization which takes into account both the network structure which is embedded in space and the dynamic coupling within the system. Beginning from a fully connected network and using an edge pruning strategy based on simulated annealing, we searched for optimal configurations for synchronization with minimum cost. We observed that the same levels of synchronization with a fully connected network can be reached by different networks with sparse connections. We conclude that the chain structure, clustering behavior and degree-frequency relations are the main determinants of optimally synchronizable network structures.

Proper Orthogonal Decomposition and Extended- Proper Orthogonal Decomposition Analysis of Pressure Fluctuations and Vortex Structures Inside a Steam Turbine Control Valve

In steam turbine control valves, pressure fluctuations coupled with vortex structures in highly unsteady three-dimensional flows are essential contributors to the aerodynamic forces on the valve components, and are major sources of flow-induced vibrations and acoustic emissions. Advanced turbulence models can capture the detailed flow information of the control valve; however, it is challenging to identify the primary flow structures, due to the massive flow database. In this study, state-of-the-art data-driven analyses, namely, proper orthogonal decomposition (POD) and extended-POD, were used to extract the energetic pressure fluctuations and dominant vortex structures of the control valve. To this end, the typical annular attachment flow inside a steam turbine control valve was investigated by carrying out a detached eddy simulation (DES). Thereafter, the energetic pressure fluctuation modes were determined by conducting POD analysis on the pressure field of the valve. The vortex structures contributing to the energetic pressure fluctuation modes were determined by conducting extended-POD analysis on the pressure–velocity coupling field. Finally, the dominant vortex structures were revealed conducting a direct POD analysis of the velocity field. The results revealed that the flow instabilities inside the control valve were mainly induced by oscillations of the annular wall-attached jet and the derivative flow separations and reattachments. Moreover, the POD analysis of the pressure field revealed that most of the pressure fluctuation intensity comprised the axial, antisymmetric, and asymmetric pressure modes. By conducting extended-POD analysis, the incorporation of the vortex structures with the energetic pressure modes was observed to coincide with the synchronous, alternating, and single-sided oscillation behaviors of the annular attachment flow. However, based on the POD analysis of the unsteady velocity fields, the vortex structures, buried in the dominant modes at St = 0.017, were found to result from the alternating oscillation behaviors of the annular attachment flow.