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Electroencephalographic Neurofeedback Training (EEG NFT) aims to improve sport performance by teaching athletes to control their mental states, leading to better cognitive, emotional, and physical outcomes. The psychomotor efficiency hypothesis suggests that optimizing brain function could enhance athletic ability, indicating the potential of EEG NFT. However, evidence for EEG-NFT’s ability to alter critical brain activity patterns, such as sensorimotor rhythm and frontal midline theta—key for concentration and relaxation—is not fully established. Current research lacks standardized methods and comprehensive studies. This shortfall is due to inconsistent EEG target selection and insufficient focus on coherence in training. This review aims to provide empirical support for EEG target selection, conduct detailed control analyses, and examine the specificity of electrodes and frequencies to relation to the psychomotor efficiency hypothesis. Following the PRISMA method, 2,869 empirical studies were identified from PubMed, Science Direct, Web of Science, Embase, CNKI, and PsycINFO. Thirteen studies met the inclusion criteria: (i) proficient skill levels; (ii) use of EEG; (iii) neurofeedback training (NFT); (iv) motor performance metrics (reaction time, precision, dexterity, balance); (v) control group for NFT comparison; (vi) peer-reviewed English-language publication; and (vii) randomized controlled trial (RCT) design. Studies indicate that NFT can enhance sports performance, including improvements in shooting accuracy, golf putting, and overall motor skills, as supported by the psychomotor efficiency hypothesis. EEG NFT demonstrates potential in enhancing sports performance by optimizing performers’ mental states and psychomotor efficiency. However, the current body of research is hampered by inconsistent methodologies and a lack of standardized EEG target selection. To strengthen the empirical evidence supporting EEG NFT, future studies need to focus on standardizing target selection, employing rigorous control analyses, and investigating underexplored EEG markers. These steps are vital to bolster the evidence for EEG NFT and enhance its effectiveness in boosting sport performance.

IntroductionImplementing a self-refereeing system presents a unique challenge in sports education, particularly in academic and training settings where officiated sports prevail. However, Ultimate Frisbee stands out by entrusting players with both athlete and referee roles, introducing distinctive ethical complexities. This manuscript is intended to evaluate ethical behavior and self-control within the Spirit of the Game (SOTG) scoring system in Elite Ultimate. To address these, Ultimate employs the (SOTG) scoring system, integral since the sport's inception in the late 1980s. SOTG aims to enhance and evaluate athletes’ ethical conduct. This study evaluates SOTG's effectiveness in elite-level Ultimate, analyzing variations across divisions and age groups in three high-level tournaments.MethodsUsing a cross-sectional design, data were collected from five international Ultimate tournaments in 2022. Teams spanned diverse age groups (under 17 to over 50) and divisions (women's, mixed, open). Post-match, teams assessed opponents’ SOTG in five domains: Rules knowledge, fouls, fairness, attitude/self-control, and communication. Ratings used a 5-point Likert scale (“poor” to “excellent”). An overall SOTG score was calculated by aggregating domain scores.ResultsOur study consistently revealed high SOTG scores, reflecting strong sportsmanship. “Positive attitude and self-control” consistently ranked highest, while “Knowledge and use of the rules” scored lowest. Divisional differences in SOTG were statistically insignificant. Notably, WMUCC2022 (participants aged 30+) had significantly higher SOTG scores, possibly indicating age-related self-control improvement or evolving sport culture. Lower rules knowledge scores may stem from linguistic translation challenges.ConclusionSelf-refereeing promotes ethical behavior across divisions and age groups. SOTG underscores sportsmanship's importance and aligns with International Olympic Committee (IOC) and with Sustainable Development Goals (SDGs), particularly SDG 3, 4, 5 and 16 fostering a fairer, healthier, and more peaceful world.

IntroductionAchieving optimal visuomotor performance in precision sports relies on maintaining an optimal psychological state during motor preparation. To uncover the optimal psychological state, extensive EEG studies have established a link between the Mu rhythm (8–13 Hz at Cz) and cognitive resource allocation during visuomotor tasks (i.e., golf or shooting). In addition, the new approach in EEG neurofeedback training (NFT), called the function-specific instruction (FSI) approach, for sports involves providing function-directed verbal instructions to assist individuals to control specific EEG parameters and align them with targeted brain activity features. While this approach was initially hypothesized to aid individuals in attaining a particular mental state during NFT, the impact of EEG-NFT involving Mu rhythm on visuomotor performance, especially when contrasting the traditional instruction (TI) approach with the FSI approach, underscores the necessity for additional exploration. Hence, the objective of this study is to investigate the impact of the FSI approach on modulating Mu rhythm through EEG-NFT in the context of visuomotor performance.MethodsThirty novice participants were recruited and divided into three groups: function-specific instruction (FSI, four females, six males; mean age = 27.00 ± 7.13), traditional instruction (TI, five females, five males; mean age = 27.00 ± 3.88), and sham control (SC, five females, five males; mean age = 27.80 ± 5.34). These groups engaged in a single-session EEG-NFT and performed golf putting tasks both before and after the EEG-NFT.ResultsThe results showed that within the FSI group, single-session NFT with augmented Mu power led to a significant decrease in putting performance (p = 0.013). Furthermore, we noted a marginal significance indicating a slight increase in Mu power and a reduction in the subjective sensation of action control following EEG-NFT (p = 0.119). While there was a positive correlation between Mu power and mean radial error in golf putting performance (p = 0.043), it is important to interpret this relationship cautiously in the context of reduced accuracy in golf putting.DiscussionThe findings emphasize the necessity for extended investigation to attain a more profound comprehension of the nuanced significance of Mu power in visuomotor performance. The study highlights the potential effectiveness of the FSI approach in EEG-NFT and in enhancing visuomotor performance, but it also emphasizes the potential impact of skill level and attentional control, particularly in complex visuomotor tasks.

A rapid recurrent neural network (RNN)-based physical feasibility test algorithm for base parameters during the identification process of a robot dynamic model is proposed in this paper. Firstly, related physical constraints such as inertia tensor, drive chain inertia, and friction are combined into the formulation of linear matrix inequality (LMI) to examine the physical consistency of the base parameters. The optimization problem of LMI is then solved by a matrix-oriented gradient-type RNN. Since the network structure of this type of RNN is simple and the process for solving the optimization problem of LMI is parallel distributed, the physical feasibility test can be completed more quickly than when utilizing commonly used semi-definite programming techniques. By taking advantage of highly efficient computation capabilities, the proposed physical feasibility test algorithm is particularly suitable for identification approaches that require rapid feasibility assessment such as on-line identification methods or optimization-based identification methods. An evolutionary algorithm-based identification method is used as an illustrative example to assess the performance of the proposed approach. In addition, a stability proof for the proposed gradient-type RNN is also provided. Results of the experiments conducted on a 6-DOF industrial robot manipulator verify the effectiveness of the proposed approach.

The impact of sleep deprivation on working memory can only be reversed by recovery sleep (RS). However, there are limited electrophysiological studies on the effect of RS on the improvement in working memory after sleep deprivation, and the changes in the early components of event-related potentials (ERPs) before and after RS are still unclear. Therefore, this study aims to explore the effects of RS on the earlier ERP components related to object working memory following 36 h of total sleep deprivation (TSD). Twenty healthy male participants performed an object working memory task after 36 h of TSD and after 8 h of RS. Electroencephalogram data were recorded accordingly while the task was performed. Repeated ANOVA showed that P2 amplitudes related to object working memory decreased significantly after 8 h of RS compared to after a 36 h period of TSD, but there was no significant difference from baseline (BS), which indicates a trend of recovery to the baseline state. An 8 h RS can partially improve impaired object working memory caused by TSD. However, a longer period of RS is needed for the complete recovery of cognitive function after a long period of TSD.

Servomechanisms and motion stages often encounter many mechanical transmission problems such as friction, backlash, and structural resonance, as well as other factors such as system nonlinearity, servo lags, and unknown disturbances. In contour following applications, these problems are the main causes of deterioration in contour following accuracy. As a result, the issue of dealing with the above problems so as to reduce tracking error and contour error is crucial. The Dynamic Fast Nonsingular Terminal Sliding Mode Control (DFNTSMC) scheme proposed in this paper combines the advantages of Fast Nonsingular Terminal Sliding Mode Control (FNTSMC) and Dynamic PID Sliding Mode Control (DSMC) while avoiding their drawbacks. The proposed DFNTSMC has attractive features such as improvement of contour following accuracy, chattering effect suppression, enhancement of robustness, and finite time convergence. The convergence of the proposed DFNTSMC is proved based on Barbalat’s lemma. Several contour following experiments are performed to assess the performance of the proposed DFNTSMC. Experimental results suggest that the proposed DFNTSMC outperforms both FNTSMC and DSMC, two control schemes also tested in the contour following experiment.

Abstract Transcranial direct current stimulation (tDCS) is a promising tool to enhance cognitive performance. However, its effectiveness has not yet been unequivocally shown. Thus, here we tested whether coupling tDCS with a bout of aerobic exercise (AE) is more effective in modulating cognitive functions than tDCS or AE alone. One hundred twenty-two healthy participants were assigned to five randomized controlled crossover experiments. Two multimodal target experiments (EXP-4: anodal vs. sham tDCS during AE; EXP-5: cathodal vs. sham tDCS during AE) investigated whether anodal (a-tDCS) or cathodal tDCS (c-tDCS) applied during AE over the left dorsolateral prefrontal cortex (left DLPFC) affects executive functioning (inhibition ability). In three unimodal control experiments, the participants were either stimulated (EXP-1: anodal vs. sham tDCS, EXP-2: cathodal vs. sham tDCS) or did AE (EXP-3: AE vs. active control). Participants performed an Eriksen flanker task during ergometer cycling at moderate intensity (in EXP. 3-5). Only c-tDCS during AE had a significant adverse effect on the inhibition task, with decreased accuracy. This outcome provides preliminary evidence that c-tDCS during AE over the left DLPFC might effectively modulate inhibition performance compared to c-tDCS alone. However, more systematic research is needed in the future.

This paper proposes a robotic assistance control scheme for intuitive teaching tasks by integrating the motion intention of human and real-time hand impedance compensation based upon a fuzzy RBF (Radial Basis Function) compensator. The motion intention of a human is estimated using a feedforward neural network. The parameters of the proposed fuzzy RBF hand impedance compensator are adjusted by considering hand impedance and robot dynamics. Three robotic assistance control schemes are compared: 1) robot without an impedance compensator; 2) robot with a constant-parameter impedance compensator; 3) robot with a fuzzy RBF hand impedance compensator. Several experiments have been conducted to verify the effectiveness of the proposed approach by comparing the contour error, exerted force and task time spent on teaching tasks. Experimental results indicate that the proposed fuzzy RBF hand impedance compensator has the best assistance results among the tested robotic assistance control schemes.

This paper focuses on developing a robotic object grasping approach that possesses the ability of self-learning, is suitable for small-volume large variety production, and has a high success rate in object grasping/pick-and-place tasks. The proposed approach consists of a computer vision-based object detection algorithm and a deep reinforcement learning algorithm with self-learning capability. In particular, the You Only Look Once (YOLO) algorithm is employed to detect and classify all objects of interest within the field of view of a camera. Based on the detection/localization and classification results provided by YOLO, the Soft Actor-Critic deep reinforcement learning algorithm is employed to provide a desired grasp pose for the robot manipulator (i.e., learning agent) to perform object grasping. In order to speed up the training process and reduce the cost of training data collection, this paper employs the Sim-to-Real technique so as to reduce the likelihood of damaging the robot manipulator due to improper actions during the training process. The V-REP platform is used to construct a simulation environment for training the deep reinforcement learning neural network. Several experiments have been conducted and experimental results indicate that the 6-DOF industrial manipulator successfully performs object grasping with the proposed approach, even for the case of previously unseen objects.

A major concern voiced by motor behavior scientists is to find useful practice techniques that can be effective in improving motor learning and performance. Neurofeedback and self-controlled practice are among the techniques that have recently drawn attention from specialists in this area. The present study examined the additive and individual effects of sensorimotor rhythm (SMR) neurofeedback as well as self-controlled practice on motor learning and performance in novice golfers. In this semi-empirical study, forty adults (20 females, Meanage = 26.10, SD = 5.56 years) were conveniently selected and randomly assigned to four groups: (1) neurofeedback/self-controlled practice, (2) neurofeedback/yoked practice, (3) sham/self-controlled practice, and (4) sham/yoked practice. The participants performed golf putting task in four stages, namely pretest (12 trials), intervention (one day after pretest; 6 sessions, 36 trails each), post-test (one day after intervention; 12 trials), and follow-up (two weeks after interventions; 12 trials). In addition, the participants had their EEG (SMR wave in Cz point) recorded during pretest, post-test, and follow-up. The results indicated that, although no additive effect was observed for the two practices during different stages of the experiment (p > 0.05), in acquisition and post-test stages, SMR neurofeedback and self-controlled practice independently facilitated golf putting (p ≤ 0.05). However, in the follow-up test, only the neurofeedback practice maintained its positive effects (p ≤ 0.05). The results also showed that participation in SMR neurofeedback practice can enhance the power of the SMR wave (p ≤ 0.05), regardless of the type of the self-controlled practice used. In sum, the two practice techniques seem to be independently effective in facilitating motor learning in instructional settings, particularly for golfers.

Zinc finger and BTB domain containing 1(Zbtb1) is a transcriptional suppressor protein, and a member of the mammalian Zbtb gene family. Previous studies have shown that Zbtb1 is essential for T-cell development. However, the role of Zbtb1 in T-cell lymphoma is undetermined. In this study, an EL4 cell line with Zbtb1 deletion was constructed using the CRISPR-Cas9 technique. The expression profiles of microRNA and circRNA produced by the control and gene deletion groups were determined by RNA-seq. In general, 24 differentially expressed microRNA and 16 differentially expressed circRNA were found between normal group and gene deletion group. Through further analysis of differentially expressed genes, GO term histogram and KEGG scatter plot were drawn, and three pairs of miRNA and circRNA regulatory relationships were found. This study describes the differentially expressed microRNA and circRNA in normal and Zbtb1-deficient EL4 cell lines, thus providing potential targets for drug development and clinical treatment of T-cell lymphoma.

Camera calibration error, vision latency, nonlinear dynamics, and so on present a major challenge for designing the control scheme for a visual servoing system. Although many approaches on visual servoing have been proposed, surprisingly, only a few of them have taken into account system dynamics in the control design of a visual servoing system. In addition, the depth information of feature points is essential in the image-based visual servoing architecture. As a result, to cope with the aforementioned problems, this article proposes a Kalman filter-based depth and velocity estimator and a modified image-based dynamic visual servoing architecture that takes into consideration the system dynamics in its control design. In particular, the Kalman filter is exploited to deal with the problems caused by vision latency and image noise so as to facilitate the estimation of the joint velocity of the robot using image information only. Moreover, in the modified image-based dynamic visual servoing architecture, the computed torque control scheme is used to compensate for system dynamics and the Kalman filter is used to provide accurate depth information of the feature points. Results of visual servoing experiments conducted on a two-degree of freedom planar robot verify the effectiveness of the proposed approach.

The meshed control theory assumes that cognitive control and automatic processes work together in the natural attention of experts for superior performance. However, the methods adopted by previous studies limit their capacity to provide in-depth information on the neuromotor processes. This experiment tested the theory with an alternative approach. Twelve skilled golfers were recruited to perform a putting task under three conditions: (1) normal condition, with no focus instruction (NC), (2) external focus of attention condition (EC), and (3) internal focus of attention condition (IC). Four blocks of 10 putts each were performed under each condition. The putting success rate and accuracy were measured and electroencephalographies (EEGs) were recorded. The behavioral results showed that the NC produced a higher putting success rate and accuracy than the EC and IC. The EEG data showed that the skilled golfers’ attentional processes in the NC initially resembled those in the EC and then moved toward those in the IC just before putting. This indicates a switch from more automatic processes to cognitive control processes while preparing to putt. The findings offer support for the meshed control theory and indicate the dynamic nature of neuromotor processes for the superior performance of athletes in challenging situations.

Lactic acid bacteria (LAB) are the primary genera of the intestinal flora and have many probiotic functions. In the present study, Lactobacillus rhamnosus GG (LGG) ATCC 53103 was used to treat BALB/c mice. After LGG intervention, both low and high LGG doses were shown to improve the observed OTU, Chao1, ACE, and Shannon indices, while the Simpson index decreased, demonstrating that LGG can promote intestinal microbiota abundance and diversity. Furthermore, LGG treatment increased the abundances of intestinal Firmicutes, Bacteroides and Actinomycetes while reducing that of Proteobacteria. In addition to its effect on gut the microbiota, LGG could also regulate the host immune system. In the present study, we showed that LGG could affect the percentage of CD3+ T lymphocytes in the spleens (SPLs), mesenteric lymph nodes (MLNs), Peyer’s patches (PPs) and lamina propria lymphocytes (LPLs) of mice, including total CD3+ T, CD3+CD4+ T, and CD3+CD8+ T lymphocytes. Furthermore, LGG could effectively increase the expression of Th1-type cytokines (IFN-γ) and Th2 cytokines (IL-4) in CD4+ T cells, indicating that the proportion of Th1 and Th2 cells in mice with LGG treatment was in a high equilibrium state compared to the control group. In addition, the IFN-γ/IL-4 ratio was greater than 1 in mice with LGG intervention, suggesting that LGG tends to mediate the Th1 immune response. The results of the present study also showed that LGG upregulated the expression of IL-17 in CD4+ T cells and regulated the percentage of CD4+CD25+Foxp3+ Treg cells in various secondary immunological organs, indicating that LGG may promote the balance of Th-17 and Treg cells.

Background: In vitro three-dimensional (3D) hepatic spheroid culture has shown great promise in toxicity testing because it better mimics the cell–cell and cell–matrix interactions found in in vivo conditions than that of the traditional two-dimensional (2D) culture. Despite embedding HepaRG spheroids with collagen type I (collagen I) extracellular matrix (ECM) revealed a much better differentiation capability, almost all the collagen utilized in in vitro hepatocytes cultures is animal-derived collagen that may limit its use in human toxicity testing. Method: Here, a preliminary investigation of HepaRG cells cultured in different dimensionalities and with the addition of ECM was performed. Comparisons of conventional 2D culture with 3D spheroid culture were performed based on their functional or structural differences over 7 days. Rat tail collagen (rtCollagen) I and recombinant human collagen (rhCollagen) I were investigated for their ability in promoting HepaRG spheroid differentiation. Results: An immunofluorescence analysis of the hepatocyte-specific functional protein albumin suggested that HepaRG spheroids demonstrated better hepatic function than spheroids from 2D culture, and the function of HepaRG spheroids improved in a time-dependent manner. The fluorescence intensities per unit area of spheroids formed by 1000 cells on days 7 and 10 were 25.41 and 45.38, respectively, whereas almost undetectable fluorescence was obtained with 2D cells. In addition, the embedding of HepaRG spheroids into rtCollagen and rhCollagen I showed that HepaRG differentiation can be accelerated relative to the differentiation of spheroids grown in suspension, demonstrating the great promise of HepaRG spheroids. Conclusions: The culture conditions established in this study provide a potentially novel alternative for promoting the differentiation of HepaRG spheroids into mature hepatocytes through a collagen-embedded in vitro liver spheroid model. This culture method is envisioned to provide insights for future drug toxicology.

A new method is proposed in this paper which designs a reduced-order observer of a non-observable-form-based dynamical system such that: (i) the eigenvalues are specified to satisfy desired convergence performance, (ii) a full-rank condition is satisfied, and (iii) a quadratic performance measurement of the deviation of the estimates from the actual states is minimized so as to reduce the large error occurring during the transient period of observation. The proposed approach combines the merits of both the orthogonal functions approach and evolutionary optimization. By solving a Sylvester equation, the proposed optimal design method can not only be used to design the reduced-order observer of a non-observable-form-based dynamical system, but also can avoid the shortcomings of approaches already existing in relevant literatures. Two examples are given to demonstrate the effectiveness and efficiency of the proposed new optimization method on the performance of state estimations. From the demonstrative examples, it can be seen that the estimated state errors asymptotically converge quickly to zero. In addition, the performance measurement values based on the proposed optimal design approach are apparently much lower than those based on the existing nonoptimal design method.

Background The efficacy of emotional and motivational regulation can determine athletic performance. Giving the short duration and fast changing nature of emotions experienced by athletes in competition, it is important to examine the temporal dynamics of emotional and motivational regulation. The aim of this study was to investigate emotional and motivational regulation as measured by frontal alpha asymmetry in skilled golfers during putting performance after a performance failure. Methods Twenty skilled university golfers were recruited and requested to perform 40 putts at an individualized difficulty level of 40–60% successful putting rate. Trials immediately after a failed putt were selected for analysis. Successful performances were those trials where a hole was and unsuccessful performances were those that failed. The frontal alpha asymmetry index of LnF4-LnF3 was derived for statistical analysis. Results (1) Successful performance was preceded by a larger frontal alpha asymmetry index at T2 than that of T1, and (2) a larger frontal alpha asymmetry index was observed for unsuccessful performance than for successful performance at T1. Discussion The results suggest that successful emotional and motivational regulation was characterized by a progressive increase of frontal alpha asymmetry, which led to subsequent putting success when facing an emotionally provocative putting failure. These findings shed light on the application of frontal alpha asymmetry for the understanding and enhancement of emotional and motivational regulation during sport performance.

Image-based visual servoing (IBVS) has increasingly gained popularity and has been adopted in applications such as industrial robots, quadrotors, and unmanned aerial vehicles. When exploiting IBVS, the image feature velocity command obtained from the visual loop controller is converted to the velocity command of the workspace through the interaction matrix so as to converge image feature error. However, issues such as the noise/disturbance arising from image processing and the smoothness of image feature command are often overlooked in the design of the visual loop controller, especially in a contour following task. In particular, noise in the image feature will contaminate the image feedback signal so that the visual loop performance can be substantially affected. To cope with the aforementioned problem, this article employs the sliding mode controller to suppress the adverse effects caused by image feature noise. Moreover, by exploiting the idea of motion planning, a parametric curve interpolator is developed to generate smooth image feature commands. In addition, a depth observer is also designed to provide the depth information essential in the implementation of the interaction matrix. In order to assess the feasibility of the proposed approach, a two-degrees-of-freedom planar robot that employs an IBVS structure and an eye-to-hand camera configuration is used to conduct a contour following task. Contour following results verify the effectiveness of the proposed approach.

The implementation of a non-contact X-Y mover that utilizes single-grained YBCO bulks and their flux trapping character is discussed. Findings reveal that a passive stable levitation is achievable by balancing the gravitational force of superconductor (SC) and the repulsive/attractive force between the permanent magnet (PM) and SC.

The Hengduan Mountains Region (HMR) is the largest “evolutionary frontier” of the northern temperate zone, and the origin and maintenance of species in this area is a research hotspot. Exploring species-specific responses to historical and contemporary environmental changes will improve our understanding of the role of this region in maintaining biodiversity. In this study, mitochondrial and microsatellite diversities were used to assess the contributions of paleogeological events, Pleistocene climatic oscillations, and contemporary landscape characteristics to the rapid intraspecific diversification of Liangshantriton taliangensis, a vulnerable amphibian species endemic to several sky-island mountains in the southeastern HMR. Divergence date estimations suggested that the East Asian monsoon, local uplifting events (Xigeda Formation strata), and Early-Middle Pleistocene transition (EMPT) promoted rapid divergence of L. taliangensis during the Pleistocene, yielding eight mitochondrial lineages and six nuclear genetic lineages. Moreover, population genetic structures were mainly fixed through isolation by resistance. Multiple in situ refugia were identified by ecological niche models and high genetic diversity, which played crucial roles in the persistence and divergence of L. taliangensis during glacialinterglacial cycles. Dramatic climatic fluctuations further promoted recurrent isolation and admixing of populations in scattered glacial refugia. The apparent mitonuclear discordance was likely the result of introgression by secondary contact and/or femalebiased dispersal. Postglacial expansion generated two major secondary contact zones (Ganluo (GL) and Chuhongjue (CHJ)). Identification of conservation management units and dispersal corridors offers important recommendations for the conservation of this species. [ABSTRACT FROM AUTHOR]