Task Synchronization Research Articles

Dynamical mechanisms of how an RNN keeps a beat, uncovered with a low-dimensional reduced model

Despite music’s omnipresence, the specific neural mechanisms responsible for perceiving and anticipating temporal patterns in music are unknown. To study potential mechanisms for keeping time in rhythmic contexts, we train a biologically constrained RNN, with excitatory (E) and inhibitory (I) units, on seven different stimulus tempos (2–8 Hz) on a synchronization and continuation task, a standard experimental paradigm. Our trained RNN generates a network oscillator that uses an input current (context parameter) to control oscillation frequency and replicates key features of neural dynamics observed in neural recordings of monkeys performing the same task. We develop a reduced three-variable rate model of the RNN and analyze its dynamic properties. By treating our understanding of the mathematical structure for oscillations in the reduced model as predictive, we confirm that the dynamical mechanisms are found also in the RNN. Our neurally plausible reduced model reveals an E-I circuit with two distinct inhibitory sub-populations, of which one is tightly synchronized with the excitatory units.

Application of Reservoir Computers for Chaos Synchronization and Cracking Chaos-Based Cryptography in Fermionic 2D Thirring and 4D Gursey Models with Spinor Fields

Reservoir computers have recently become one of the most widely exploited model-free approaches to chaos synchronization due to their fast convergence speed and simple yet effective learning rules. In this study, reservoir computing has been utilized to emulate the dynamics of chaotic Thirring and Gursey systems. In the supervised learning of the reservoir, one-step ahead states of the dynamical systems have been employed as the teaching signals. After the training phase, the reservoir was first run autonomously and then weakly driven by chaotic systems. It has been shown that the trained reservoir computers can exhibit the same characteristics as the attractors of the learned chaotic systems, which enable their use in synchronization tasks of chaotic systems with possible application in cracking chaos-based cryptography. To investigate the effect of noise on the performance of reservoir computers, noise signals with different colors and amplitudes have been included in the transmitted signals. The obtained results indicate that the proposed scheme can provide lower error metrics for both models.

System friendliness of distributed resources in sustainable energy systems

The increasing share of volatile renewable energy generation in current and future energy systems which does not follow the demand, makes it necessary to shift the synchronization tasks to the system and demand level. The intended demand side consumption management is usually incentivized via financial mechanisms. However, the optimum design of related incentives is still unclear. It is usually discussed under the term “system friendliness” which in turn still lacks a broadly accepted definition. In this article we introduce a new technical definition of “system friendliness” and develop comprehensive and holistic related indicators. For that, we introduce the burden concept for energy systems which represents the amount of technical infrastructure required for stable operation. We use the concept of a hypothetical system energy storage to derive indicators that are capable of quantifying the system friendliness of a given point-of-interest. The developed indicators are independent of regulations or market environments which enables comparability of results between studies and different systems. In a case study we demonstrate our newly developed methodology and exemplary examine decentral district energy storages. Our findings demonstrate that today’s regulatory environments that usually support residential self-consumption maximization are counterproductive. Instead, we show that dynamic end-user prices coupled with dynamic feed in tariffs are able to incentivize an almost 100% system friendly behavior of distributed prosumers.

Asymptotic Synchronization for Caputo Fractional-Order Time-Delayed Cellar Neural Networks with Multiple Fuzzy Operators and Partial Uncertainties via Mixed Impulsive Feedback Control

To construct Caputo fractional-order time-delayed cellar neural networks (FOTDCNNs) that characterize real environments, this article introduces partial uncertainties, fuzzy operators, and nonlinear activation functions into the network models. Specifically, both the fuzzy AND operator and the fuzzy OR operator are contemplated in the master–slave systems. In response to the properties of the considered cellar neural networks (NNs), this article designs a new class of mixed control protocols that utilize both the error feedback information of systems and the sampling information of impulse moments to achieve network synchronization tasks. This approach overcomes the interference of time delays and uncertainties on network stability. By integrating the fractional-order comparison principle, fractional-order stability theory, and hybrid control schemes, readily verifiable asymptotic synchronization conditions for the studied fuzzy cellar NNs are established, and the range of system parameters is determined. Unlike previous results, the impulse gain spectrum considered in this study is no longer confined to a local interval (−2,0) and can be extended to almost the entire real number domain. This spectrum extension relaxes the synchronization conditions, ensuring a broader applicability of the proposed control schemes.

Design of an integrated network order system for main distribution network considering power dispatch efficiency

This study presents a comprehensive review of the primary distribution design of an advanced network control system, emphasizing its evolution from initial requirements to practical applications. The system solves complex problems of power management by combining real-time data analysis, intelligent decision making for resource allocation, rapid fault correction, remote monitoring and complex optimization methods, all aimed at ensuring stable and safe operation of the power grid. Its performance is geared towards fast response, efficient data processing and synchronous processing tasks, ensuring smooth operation even under heavy workloads. Security is enhanced through strict protocols, encryption methods, and controlled access systems. The system is divided into four layers-data collection, communication, decision-making and application management-using innovative tools such as Kalman filters and deep Q networks. The research showcases the integrated network command system’s prowess, achieving an average response time of 0.27 s, 98.5% dispatching accuracy, and 83.2% resource utilization, evidencing exceptional performance. It excels under various tests, including managing high loads with minimal accuracy loss, rapidly adapting to changes with a hydro model response time of 0.22 s, efficiently integrating renewables at 78.0% efficiency, and proving resilient in peak hours, affirming its capability to bolster grid efficiency, reliability, and integration of renewable energy resources. By outlining these specific achievements, this case study not only illustrates the complex design of the system, but also highlights its great potential for improving grid resilience and efficiency, attracting a wide audience interested in the future of energy management.

The Difference Between Expert Dancers' and Non-Dancers Tapping Timing With and Without an Auditory Stimulus at a Slow Tempo.

Our primary purpose in this study was to determine whether trained dancers differed from untrained non-dancers in their ability to accurately control motor timing during finger and heel tapping tasks, both with and without slow isochronous auditory stimuli. Dancers and non-dancers were instructed to synchronize their taps with isochronous auditory stimuli under three conditions: 30, 40, and 50BPM. After the synchronization phase, participants were asked to continue tapping without the auditory sequences. On the synchronization task, the tapping onset of both groups lagged behind the stimulus onset in all tempo conditions. In all conditions, dancers showed more accurate and stable beat synchronization and continuation than non-dancers. As the tempo condition slowed down (from 50 to 30BPM), synchronization accuracy decreased while synchronization and continuation variability increased. Unlike for novices, dancers showed no difference between the finger and heel tapping synchronization tasks. During the continuous tasks, their timing accuracy was higher for heel than for finger tapping. Collectively, these findings suggest that dance training, which involves synchronizing bodily movements based on rhythm, may lead to an accumulation of experience that enhances specific sensorimotor skills related to synchronizing movements with external stimuli or continuing rhythmic movements temporally.

Neuro-Optimal Event-Triggered Impulsive Control for Stochastic Systems via ADP.

This article presents a novel neural-network-based optimal event-triggered impulsive control method. First, a novel general-event-based impulsive transition matrix (GITM) is constructed to represent the probability distribution evolving characteristics regarding all system states across the impulsive actions, rather than the prefixed timing sequence. On the foundation of this GITM, the event-triggered impulsive adaptive dynamic programming (ETIADP) algorithm and its high-efficiency version (HEIADP) are developed to deal with the optimization problems for stochastic systems with event-triggered impulsive controls. It is shown that the obtained controller design scheme can reduce the computational and communication burden caused by updating the controller periodically. By analyzing the admissibility, monotonicity, and optimality properties of ETIADP and HEIADP, we further establish the approximation error bound of the neural networks to address the connection between the ideal and neural-network-based realizations of the present methods. It is proven that the iterative value functions of both the ETIADP and HEIADP algorithms fall in a small neighborhood of the optimum as the iteration index increases to infinity. By adopting a novel task synchronization mechanism, the proposed HEIADP algorithm fully utilizes the computing resources of multiprocessor systems (MPSs), while significantly reducing the memory requirement compared to traditional ADP approaches. Finally, we carry out a numerical study to show that the proposed methods can fulfill the desired goals.

Koordinasi Pada Bagian Protokol dan Komunikasi Pimpinan Dalam Meningkatkan Pelayanan di Lingkungan Sekretariat Daerah Kabupaten Supiori

This research aims to describe and analyze Coordination in the Protocol and Leadership Communication Section in Improving Services within the Regional Secretariat of Supiori Regency. The research is descriptive qualitative in nature. Data analysis techniques through observation, in-depth interviews, documentation, literature study including work procedure mechanisms, directing, synchronization and division of tasks. The results of the research found that the work procedure mechanism carried out in the service was not optimal because the communication carried out had not been accommodated well, but the direction carried out looked good but not optimal. This was because the coordination function between leaders and subordinates in communication was not good and the implementation of activities had not gone well. , the synchronization aspect was found to be not optimal because there was still work being done that was not in accordance with the directions, the division of tasks looked good but was not optimal because there were still vacancies in certain positions. So from the results of this research it was found that coordination in the Protocol and Leadership Communication Section in Improving Services in the Regional Secretariat of Supiori Regency is not yet optimal because there are still many factors that influence the delivery of services including poor communication, inadequate facilities and infrastructure and there is no collaboration yet. both between leaders and subordinates.

Boosting Prefrontal Brain Responsiveness by Interoceptive Attentiveness during Synchronized Breathing, Motor, and Cognitive Task

Background: this study explored the prefrontal cortex (PFC) hemodynamic variations produced by the association of an Interoceptive Attentiveness (IA) condition with a simple breath, motor, and cognitive synchronization task. Methods: 18 healthy individuals performed different synchronization activities (breath, motor, and cognitive) under both IA and control conditions, while levels of oxygenated (O2Hb) and deoxygenated hemoglobin were measured using functional Near-Infrared Spectroscopy (fNIRS). Results: findings revealed higher O2Hb levels in the prefrontal brain region during the experimental condition (IA) in contrast to the control condition. Notably, this difference was particularly evident during the cognitive task as opposed to the other tasks (breath and motor). In contrast, no significant differences were found for the PFC lateralization effect. Conclusions: This evidence holds potential for rehabilitation professionals suggesting that the combination of deliberate attention to the breath and a cognitive synchronization task (such as a vocal exercise executed simultaneously) could boost PFC responsiveness.

Performance Assessment for the Validation of Wireless Communication Engines in an Innovative Wearable Monitoring Platform.

In today's health-monitoring applications, there is a growing demand for wireless and wearable acquisition platforms capable of simultaneously gathering multiple bio-signals from multiple body areas. These systems require well-structured software architectures, both to keep different wireless sensing nodes synchronized each other and to flush collected data towards an external gateway. This paper presents a quantitative analysis aimed at validating both the wireless synchronization task (implemented with a custom protocol) and the data transmission task (implemented with the BLE protocol) in a prototype wearable monitoring platform. We evaluated seven frequencies for exchanging synchronization packets (10 Hz, 20 Hz, 30 Hz, 40 Hz, 50 Hz, 60 Hz, 70 Hz) as well as two different BLE configurations (with and without the implementation of a dynamic adaptation of the BLE Connection Interval parameter). Additionally, we tested BLE data transmission performance in five different use case scenarios. As a result, we achieved the optimal performance in the synchronization task (1.18 ticks as median synchronization delay with a Min-Max range of 1.60 ticks and an Interquartile range (IQR) of 0.42 ticks) when exploiting a synchronization frequency of 40 Hz and the dynamic adaptation of the Connection Interval. Moreover, BLE data transmission proved to be significantly more efficient with shorter distances between the communicating nodes, growing worse by 30.5% beyond 8 m. In summary, this study suggests the best-performing network configurations to enhance the synchronization task of the prototype platform under analysis, as well as quantitative details on the best placement of data collectors.

Inter-brain entrainment (IBE) during interoception. A multimodal EEG-fNIRS coherence-based hyperscanning approach

This work examined the impact of interoceptive manipulation and the presence of a shared goal on inter-brain entrainment (IBE) during a motor synchronization task. A multimodal functional Near Infrared Spectroscopy − Electroencephalogram (fNIRS-EEG) system-based hyperscanning approach was applied to 13 dyads performing the motor synchrony task during an interoceptive (focus on the breath) and control condition. Additionally, two version of the motor task—one with and one without a clearly defined common goal—were presented to participants to emphasize the task’s collaborative purpose. The multimodal approach was exploited to record the electrophysiological (EEG) cortical oscillation and hemodynamic (oxy-Hb and deoxy-Hb) levels. Results revealed significant correlations between EEG delta, theta, and alpha band and hemodynamic oxy-Hb in the left compared to right hemisphere for the interoceptive confronted with the control condition. This significant EEG/fNIRS IBE correlation was also found for delta and theta band whereas the task was presented with an explicit shared goal confronted with the no-social version. In addition to separate functional connectivity EEG and fNIRS analysis, this study proposed a novel analysis pipeline including statistical tests for examining the coherence between functional connectivity EEG-fNIRS signals within couples. Besides proposing methodological advancements on EEG-fNIRS signals hyperscanning analysis, this research demonstrated that, in dyads undertaking a motor synchronization task, both the interoceptive attention to respiration and an explicit joint intention activate left anterior regions.

Synchronous planning of initial and target positions of redundant space manipulator based on deterministic configuration tree

Planning the operating position of redundant space manipulators (RSMs) can effectively improve the performance of manipulators while improving the quality of on-orbit servicing (OOS) is of great significance. For RSM, OOS with synchronous planning of initial and target positions (ITPs) has many combinations of positions or configurations, making it difficult to apply existing methods directly. To address this problem, this study proposes a method for synchronous planning ITPs of RSMs based on a deterministic configuration tree (DCT). First, the planning area is divided into grids, with the global performance analyzed utilizing self-motion manifolds. Then, a DCT is constructed based on the analysis results of global performance. Finally, a position planning strategy of pre-planning, rewiring, and regrowth is proposed to achieve synchronized planning of the ITP of the RSM on the DCT. This method is conducted alternately in operational space and joint space. The gridding and regrowth process in operational space avoids the considerable calculation required by gridding in high-dimensional joint space and improves the efficiency of position planning. In joint space pre-planning and rewiring, the ITP is optimized with the constraint of motion planning results while position planning is realized. The simulation experiment results of the 3-degree-of-freedom (DOF) planar RSM, 4-DOF RSM, and 7-DOF RSM indicate that the proposed method reduces time consumption by 34.81%, 18.15%, and 16.26% compared to conventional methods. Furthermore, energy consumption is reduced by 30.68%, 16.93%, and 15.64%, respectively. A typical ITPs synchronous planning task is also simulated, and the results also show that this planning method can effectively optimize the ITPs and reduce energy consumption.

Audiovisual integration of rhythm in musicians and dancers.

Music training is associated with better beat processing in the auditory modality. However, it is unknown how rhythmic training that emphasizes visual rhythms, such as dance training, might affect beat processing, nor whether training effects in general are modality specific. Here we examined how music and dance training interacted with modality during audiovisual integration and synchronization to auditory and visual isochronous sequences. In two experiments, musicians, dancers, and controls completed an audiovisual integration task and an audiovisual target-distractor synchronization task using dynamic visual stimuli (a bouncing figure). The groups performed similarly on the audiovisual integration tasks (Experiments 1 and 2). However, in the finger-tapping synchronization task (Experiment 1), musicians were more influenced by auditory distractors when synchronizing to visual sequences, while dancers were more influenced by visual distractors when synchronizing to auditory sequences. When participants synchronized with whole-body movements instead of finger-tapping (Experiment 2), all groups were more influenced by the visual distractor than the auditory distractor. Taken together, this study highlights how training is associated with audiovisual processing, and how different types of visual rhythmic stimuli and different movements alter beat perception and production outcome measures. Implications for the modality appropriateness hypothesis are discussed.

Negative emotions disrupt intentional synchronization during group sensorimotor interaction.

Emotions play a fundamental role in human interactions and trigger responses in physiological, psychological, and behavioral modalities. Interpersonal coordination often entails attunement between individuals in various modalities. Previous research has elucidated the mechanisms of interpersonal synchronization and the emotions aroused by joint action: cardiac activity aligns in disputing marital couples, spectators share enjoyment in observing live dance performances, and joint finger-tapping evokes positive emotions. However, little is known about the impact of emotions on intentional interpersonal synchronization. To address this problem, we conducted an experiment in 2022 asking 60 participants to engage in a three-way finger-tapping synchronization task. We systematically induced emotional states (positive, neutral, and negative) with social comparison feedback using success-failure manipulations. An analysis of behavior synchronization using the Kuramoto order parameter revealed that negative emotion induction significantly diminished time spent in synchrony compared to positive induction. Moreover, the results exposed incremental struggles in attaining higher levels of synchronization (Q2-Q3) after the induction of negative emotions. These outcomes further substantiate the necessity of integrating the indices of agents' emotions into interpersonal synchronization and coordination models. We discuss the implications of this work for research on interpersonal emotion in joint action and applied outcomes in emotion-aware technologies and interventions. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Social Interoception and Autonomic System Reactivity during Synchronization Behavior.

Within the social interoception field, little is known about the impact of interoception on autonomic system reactivity during synchronization tasks. The impact of social framing manipulation and Interoceptive Attentiveness (IA; defined as concentrated attention on the breath for a specific time interval) on autonomic responses during interpersonal synchronization was investigated in this research. Under two experimental interoceptive conditions-the concentration and no focus on the breath condition-participants completed two synchronization tasks. A social framing was given to participants by informing them that they needed to complete the tasks in unison to improve their collaboration abilities. Autonomic responses (electrodermal activity and cardiovascular indices) were collected throughout task performance. Two orders of results were observed: high cognitive engagement was detected during the focus on the breath condition and for the social frame. This effect was specifically observed for the motor compared to the linguistic synchronization task. Meanwhile, a potential lack of emotional control was observed in the no focus on the breath condition when the synchronization tasks were not socially framed. Such results encourage the use of the hyperscanning paradigm to deepen the impact of IA in real-time and ecological interpersonal synchronization dynamics.

КЛАССИФИКАЦИЯ УРОВНЯ СЛОЖНОСТИ СЕНСОМОТОРНОЙ ЗАДАЧИ ДЛЯ СПОРТСМЕНОВ НА ОСНОВАНИИ ФИЗИОЛОГИЧЕСКИХ ПОКАЗАТЕЛЕЙ МЕТОДАМИ МАШИННОГО ОБУЧЕНИЯ

The study aimed to identify the most sensitive autonomic indicators reflecting the level of complexity of the sensorimotor task performed by athletes using various machine learning methods (classification algorithms). As tasks of two levels of difficulty, we used the audio-motor synchronization task: to tap in synchrony with a metronome rhythmic sound (a simple task) and to tap the same rhythm without auditory cues (rhythm memory task, a complex task). Heart rate, respiratory parameters, skin conduction, and EEG were recorded. The most accurate classification was demonstrated by the Classification and Regression Trees (C&RT) model – the error was 18.3%.

Transfer learning promotes acquisition of individual BCI skills.

Subject training is crucial for acquiring brain-computer interface (BCI) control. Typically, this requires collecting user-specific calibration data due to high inter-subject neural variability that limits the usability of generic decoders. However, calibration is cumbersome and may produce inadequate data for building decoders, especially with naïve subjects. Here, we show that a decoder trained on the data of a single expert is readily transferrable to inexperienced users via domain adaptation techniques allowing calibration-free BCI training. We introduce two real-time frameworks, (i) Generic Recentering (GR) through unsupervised adaptation and (ii) Personally Assisted Recentering (PAR) that extends GR by employing supervised recalibration of the decoder parameters. We evaluated our frameworks on 18 healthy naïve subjects over five online sessions, who operated a customary synchronous bar task with continuous feedback and a more challenging car racing game with asynchronous control and discrete feedback. We show that along with improved task-oriented BCI performance in both tasks, our frameworks promoted subjects' ability to acquire individual BCI skills, as the initial neurophysiological control features of an expert subject evolved and became subject specific. Furthermore, those features were task-specific and were learned in parallel as participants practiced the two tasks in every session. Contrary to previous findings implying that supervised methods lead to improved online BCI control, we observed that longitudinal training coupled with unsupervised domain matching (GR) achieved similar performance to supervised recalibration (PAR). Therefore, our presented frameworks facilitate calibration-free BCIs and have immediate implications for broader populations-such as patients with neurological pathologies-who might struggle to provide suitable initial calibration data.

Tactile cues are more intrinsically linked to motor timing than visual cues in visual-tactile sensorimotor synchronization.

Many tasks require precise synchronization with external sensory stimuli, such as driving a car. This study investigates whether combined visual-tactile information provides additional benefits to movement synchrony over separate visual and tactile stimuli and explores the relationship with the temporal binding window for multisensory integration. In Experiment 1, participants completed a sensorimotor synchronization task to examine movement variability and a simultaneity judgment task to measure the temporal binding window. Results showed similar synchronization variability between visual-tactile and tactile-only stimuli, but significantly lower than visual only. In Experiment 2, participants completed a visual-tactile sensorimotor synchronization task with cross-modal stimuli presented inside (stimulus onset asynchrony 80 ms) and outside (stimulus-onset asynchrony 400 ms) the temporal binding window to examine temporal accuracy of movement execution. Participants synchronized their movement with the first stimulus in the cross-modal pair, either the visual or tactile stimulus. Results showed significantly greater temporal accuracy when only one stimulus was presented inside the window and the second stimulus was outside the window than when both stimuli were presented inside the window, with movement execution being more accurate when attending to the tactile stimulus. Overall, these findings indicate there may be a modality-specific benefit to sensorimotor synchronization performance, such that tactile cues are weighted more strongly than visual information as tactile information is more intrinsically linked to motor timing than visual information. Further, our findings indicate that the visual-tactile temporal binding window is related to the temporal accuracy of movement execution.

Multisensory integration deficits in Schizophrenia and Autism evidenced in behaviour but not event related potentials

The process of integrating information from different sensory channels, known as multisensory integration (MSI) was assessed in two disorders, Autism Spectrum Disorder (ASD) and Schizophrenia (SCZ). 32 healthy controls (HC), 35 SCZ patients, and 23 ASD patients performed an audiovisual (AV) synchronous target detection task while reaction time (RT) and scalp recorded electrophysiological (EEG) activity were measured. MSI in the AV condition resulted in faster and less variable RTs compared to the unimodal conditions. Using our novel bootstrap method, MSI gain was observed in 78 % of HC, 26 % of ASD, and 48 % of SCZ patients. At the neural level, MSI in the AV condition resulted in larger amplitude of sensory evoked responses and cognitive P3 response compared to the corresponding unimodal conditions. These neural effects of MSI were not related to the behavioural MSI gain identified at the individual level and could not explain the deficits in behavioural MSI of patient groups. In conclusion, a robust MSI gain deficit in RT was observed in both patient groups that was not reflected in early perceptual and cognitive electro-cortical responses, suggesting that behavioural MSI deficits in ASD and SCZ may arise at late processing stages such as response selection.

Auditory-motor synchronization and perception suggest partially distinct time scales in speech and music

Speech and music might involve specific cognitive rhythmic timing mechanisms related to differences in the dominant rhythmic structure. We investigate the influence of different motor effectors on rate-specific processing in both domains. A perception and a synchronization task involving syllable and piano tone sequences and motor effectors typically associated with speech (whispering) and music (finger-tapping) were tested at slow (~2 Hz) and fast rates (~4.5 Hz). Although synchronization performance was generally better at slow rates, the motor effectors exhibited specific rate preferences. Finger-tapping was advantaged compared to whispering at slow but not at faster rates, with synchronization being effector-dependent at slow, but highly correlated at faster rates. Perception of speech and music was better at different rates and predicted by a fast general and a slow finger-tapping synchronization component. Our data suggests partially independent rhythmic timing mechanisms for speech and music, possibly related to a differential recruitment of cortical motor circuitry.