Response Task Research Articles

Neural mechanisms underlying perceptual-motor behavioral advantages in athletes: a systematic review and activation likelihood estimation meta-analysis

ABSTRACT This study aimed to uncover the neural mechanisms through which long-term exercise training influences athletes’ perceptual-motor behavior using an Activation Likelihood Estimation meta-analysis. An extensive literature search identified 14 experiments comprising 336 foci related to perceptual tasks and 16 experiments comprising 556 foci related to motor response tasks. We analyzed brain activation in athletes and novices during perceptual and motor response tasks relative to baseline and conducted direct and inverse contrasts in brain activation between the two groups within these tasks. The findings indicated that athletes exhibit neural efficiency in perceptual and motor response tasks, with fewer brain regions activated compared to novices. Notably, athletes showed greater activation in brain regions associated with sensorimotor processing and higher-order cognitive areas related to attention and memory. These results suggest that athletes extract kinematic information about opponents’ movements through sensorimotor simulation and match it with tactical and technical knowledge stored in long-term memory, thereby supporting superior perceptual-motor performance. In contrast, novices lacking athletic experience rely more on the occipital cortex for visual processing of actions. These findings highlight the differences in brain activity between athletes and novices during perceptual-motor behavior, providing valuable insights into how exercise training shapes brain function.

Toward a Free-Response Paradigm of Decision-Making in Spiking Neural Networks.

Spiking neural networks (SNNs) have attracted significant interest in the development of brain-inspired computing systems due to their energy efficiency and similarities to biological information processing. In contrast to continuous-valued artificial neural networks, which produce results in a single step, SNNs require multiple steps during inference to achieve a desired accuracy level, resulting in a burden in real-time response and energy efficiency. Inspired by the tradeoff between speed and accuracy in human and animal decision-making processes, which exhibit correlations among reaction times, task complexity, and decision confidence, an inquiry emerges regarding how an SNN model can benefit by implementing these attributes. Here, we introduce a theory of decision making in SNNs by untangling the interplay between signal and noise. Under this theory, we introduce a new learning objective that trains an SNN not only to make the correct decisions but also to shape its confidence. Numerical experiments demonstrate that SNNs trained in this way exhibit improved confidence expression, reduced trial-to-trial variability, and shorter latency to reach the desired accuracy. We then introduce a stopping policy that can stop inference in a way that further enhances the time efficiency of SNNs. The stopping time can serve as an indicator to whether a decision is correct, akin to the reaction time in animal behavior experiments. By integrating stochasticity into decision making, this study opens up new possibilities to explore the capabilities of SNNs and advance SNNs and their applications in complex decision-making scenarios where model performance is limited.

Influence of Unspecific Visual-Perceptual-Cognitive Task Constraints on Jump Ability and Reactive Strength in Federated Soccer Players.

Soccer players must react quickly and execute complex mental processes to adapt to competitive scenarios while maintaining peak physical performance. Perceptual-cognitive training methods integrate reaction tasks using nonspecific visual stimuli with game-like motor actions, but the impact on explosive strength responses is unclear. This study investigates the effect of nonspecific visual stimuli with varying perceptual-cognitive constraints on jump performance, including countermovement jump height, reactive strength index modified, action time, and reaction time. A total of 299 soccer players were randomly assigned to four groups to assess the impact of different perceptual-cognitive tasks on countermovement jump performance. The results showed a significant reduction in jump height in all groups, with the most pronounced effect in the divided/attention simple reaction time task group (Δ height = -4.74 cm; p < 0.001). Action time was significantly shorter in all experimental jumps compared with controls (p < 0.001), and the reactive strength index modified increased across perceptual-cognitive tasks (p < 0.001) except in the divided/attention simple reaction time (p = 0.593). Reaction time increased in all groups, with the highest in the complex elective reaction time task (487.32 ± 153.75 ms; p < 0.001). These findings suggest that nonspecific visual stimuli negatively affect countermovement jump performance, highlighting the importance of analyzing sport-specific perceptual-cognitive demands in the development of efficient training programs.

A Decision-Making Algorithm of Multiple Reactive Tasks for Autonomous Driving Sweepers Based on Behavior Trees

A Decision-Making Algorithm of Multiple Reactive Tasks for Autonomous Driving Sweepers Based on Behavior Trees

Human-Aware Reactive Task Planning of Sequential Robotic Manipulation Tasks

Human-Aware Reactive Task Planning of Sequential Robotic Manipulation Tasks

EEG-Based Measurement for Detecting Distraction in Coal Mine Workers

In the high-attention-demanding environment of underground coal mines, distraction is a major cause of unsafe behavior and decreased safety performance. Research on the cognitive neural mechanisms and monitoring of distraction in miners is limited. This study used an electroencephalogram (EEG) to examine the correlation between distraction and brain activity in coal miners, aiming to provide an objective method for monitoring distraction in coal miners. Thirty participants completed a simulated hazard recognition task, using the Sustained Attention to Response Task (SART) and noise to induce distraction. Brain activity was recorded and labeled as focused or distracted based on the correctness of the hazard recognition task. EEG features were extracted and selected, and a Random Forest model for distraction identification was constructed based on the selected features. In the focused state, delta power in the temporal region and theta power in the frontal region increased significantly. In the distracted state, alpha power in the temporal and occipital regions and beta power in the occipital and parietal regions increased. The selected EEG features could be used to identify distraction with 84% accuracy. This method can objectively identify distraction in coal miners, highlighting the potential of using EEG for real-time distraction monitoring.

Stability of performance monitoring with prolonged task performance: A study of error-related negativity and error positivity.

The use of forced-choice response tasks to study indices of performance monitoring, such as the error-related negativity (ERN) and error positivity (Pe), is common, and such tasks are often used as a part of larger batteries in experimental research. ERN amplitude typically decreases over the course of a single task, but it is unclear whether amplitude changes persist beyond a single task or whether Pe amplitude changes over time. This preregistered study examined how prolonged task performance affects ERN and Pe amplitude across two study batteries, each with three different tasks. We predicted ERN amplitude would show unique, nonlinear reductions over an individual task and over the task battery, and exploratory analyses were conducted on Pe. Electrophysiological data were recorded during two studies: 156 participants who completed three versions of the flanker task and 161 participants who completed flanker, Go/NoGo, and Stroop tasks. ERN showed unique nonlinear reductions over each flanker task and over the battery of flanker tasks. However, ERN showed a linear reduction in amplitude over the battery of three different tasks, and within-task changes were only observed during the Go/NoGo task, such that ERN increased. Pe generally linearly decreased with prolonged task performance. Variability in ERN and Pe scores generally increased with time, indicating decreases in data quality. Findings suggest that studying ERN and Pe early in a task battery with short tasks is optimal to avoid bias from prolonged performance. Identifying factors affecting ERN and Pe during prolonged performance can help develop optimized paradigms.

Identification of anticipatory brain activity in a time discrimination task

The purpose of this study was to investigate anticipatory functions in temporal cognition, identifying the presence of proactive brain processing specifically preceding a time discrimination task. To this aim, two discriminative response tasks (DRTs) were employed: a feature DRT and a temporal (T-DRT). While the F-DRT required discrimination among different geometrical shapes, the T-DRT required discrimination among different stimulus durations. Specifically, this study investigated the role of premotor and prefrontal cortices, and sensory visual areas in preparatory activity preceding time-processing by electroencephalographic methods and analyzing the event-related potential (ERP). ERP components associated with motor (the BP), cognitive (the pN), and sensory readiness (the vN) were analyzed on 21 participants completing the two DRTs. The results support the involvement of all considered brain areas in temporal cognition but extend this information by indicating that these areas can be engaged during the preparation phase before the stimulus is delivered. Furthermore, the T-DRT requires strong anticipatory activity in the PFC likely serving as a moderator of upcoming motor responses. Finally, visual areas were greatly engaged in the early phase of sensory readiness of the T-DRT probably to create top-down low-level representations of imminent events to facilitate perception.

Immunity for counterproductive attentional capture by reward signals among individuals with depressive symptoms

ObjectivesThis study aimed to investigate the characteristics of attentional capture by reward signals in individuals with depression during classical conditioning. MethodsA variant of the additional singleton paradigm was adopted with a high- or low-reward signal as the prominent distracting stimulus. In Experiment 1, 46 participants with depressive symptoms and 46 healthy controls were asked to conduct a keypress response to a visual target. In Experiment 2, 58 participants with depressive symptoms and 58 healthy controls were asked to conduct a fixation response to the visual target. ResultsIn the keypress response task, the presence of high-reward signals slowed down the responses of participants in the control group, whereas the response times of individuals with depression were not significantly affected. In the fixation response task, when the high-reward signal was presented, individuals with depression were more likely to choose the target location as the first saccade destination, compared with healthy controls. In addition, individuals with depression exhibited fewer oculomotor capture by high-reward signals than healthy controls, a trait which was closely linked to the enhanced saccadic inhibition. ConclusionThe results of our study indicated that individuals with depression exhibited an abnormality in attentional capture by reward-related conditioned stimuli during classical conditioning.

High frequency post-pause word choices and task-dependent speech behavior characterize connected speech in individuals with mild cognitive impairment.

Alzheimer's disease (AD) is characterized by progressive cognitive decline, including impairments in speech production and fluency. Mild cognitive impairment (MCI), a prodrome of AD, has also been linked with changes in speech behavior but to a more subtle degree. This study aimed to investigate whether speech behavior immediately following both filled and unfilled pauses (post-pause speech behavior) differs between individuals with MCI and healthy controls (HCs), and how these differences are influenced by the cognitive demands of various speech tasks. Transcribed speech samples were analyzed from both groups across different tasks, including immediate and delayed narrative recall, picture descriptions, and free responses. Key metrics including lexical and syntactic complexity, lexical frequency and diversity, and part of speech usage, both overall and post-pause, were examined. Significant differences in pause usage were observed between groups, with a higher incidence and longer latencies following these pauses in the MCI group. Lexical frequency following filled pauses was higher among MCI participants in the free response task but not in other tasks, potentially due to the relative cognitive load of the tasks. The immediate recall task was most useful at differentiating between groups. Predictive analyses utilizing random forest classifiers demonstrated high specificity in using speech behavior metrics to differentiate between MCI and HCs. Speech behavior following pauses differs between MCI participants and healthy controls, with these differences being influenced by the cognitive demands of the speech tasks. These post-pause speech metrics can be easily integrated into existing speech analysis paradigms.

Cognitive impairments after maximal repeated breath-holding in elite breath-hold divers.

Breath-hold (BH) training over several years may result in mild but persistent neurocognitive impairment. Paradoxically, the acute effects of repeated BH generating intermittent hypoxia on neurocognitive functions are still poorly understood. Therefore, we decided to examine the impact of five-repeated maximal BH on attention, processing speed, and reasoning abilities. Thirty six men separated in 3 groups (12 elite BH divers: E<inf>BHD</inf>; 12 novice BH divers: N<inf>BHD</inf>; and 12 non BH divers: CTL) performed before and after 5 maximal BHs, neuropsychological computerized tasks sensitive to hypoxia. Heart rate (HR) and peripheral oxygen saturation were recorded continuously during all tests. Immediately after the five BHs, all the participants presented lower response time on the visual reaction task. E<inf>BHD</inf> did not exhibit difference in neuropsychological performance compared to N<inf>BHD</inf> and CTL, despite enduring longer BH durations. Regardless of BHD training level, repeated maximal BH may affect certain aspects of neuropsychological performance, in particularly visual reaction times. However, elite BHDs may have developed adaptive mechanisms that allow them to maintain their neurocognitive function at levels comparable to those of less trained BHDs and CTL, even with a higher dose of hypoxia.

Bi-objective dynamic tugboat scheduling with speed optimization under stochastic and time-varying service demands

With the growing emphasis on green shipping to reduce the environmental impact of maritime transportation, optimizing fuel consumption with maintaining high service quality has become critical in port operations. Ports are essential nodes in global supply chains, where tugboats play a pivotal role in the safe and efficient maneuvering of ships within constrained environments. However, existing literature lacks approaches that address tugboat scheduling under realistic operational conditions. To fill the research gap, this is the first work to propose the bi-objective dynamic tugboat scheduling problem that optimizes speed under stochastic and time-varying demands, aiming to minimize fuel consumption and manage service punctuality across a heterogeneous fleet. For the first time, we develop an extended Markov decision process framework that integrates both reactive task assignments and proactive waiting decisions, considering the dual objectives. Subsequently, an initial schedule for known requests is established using a mixed-integer linear programming model, and an anticipatory approximate dynamic programming method dynamically incorporates emerging demands through task assignments and waiting plans. This approach is further enhanced by an improved rollout algorithm to anticipate future scenarios and make decisions efficiently. Applied to the Singapore port, our methodology achieves a 12.8% reduction in the total sail cost compared to the tugboat company’s scheduling practices, resulting in significant daily savings. The results with benchmarking against three methods demonstrate improvements in cost efficiency and service punctuality, meanwhile, extensive sensitivity analysis provides managerial insights for operational practice.

Coordinated control strategy for improving frequency security of LCC[sbnd]HVDC sending-end system with large-scale wind power

To improve the frequency security of the LCCHVDC sending-end system with high penetration of wind power system and achieve optimal utilization of frequency regulation resources, a cooperative control strategy involving wind power and LCCHVDC in frequency regulation is proposed. Firstly, under a variety of scenarios, the power support requirements of LCCHVDC sending-end system are analyzed according to the power regulation margin of various frequency regulation resources and the disturbance power, and a multi-time scale frequency regulation control strategy for DFIG based wind farms is proposed, which combines the advantages of variable speed control and variable pitch angel control. And a cooperative control strategy of DFIG and LCCHVDC considering the frequency regulation deadband is proposed. Then, based on the maximum power regulation margin of synchronous generators and wind farms, the key control parameters of relative control links are designed to enable them autonomously adjust the active power according to various scenarios to involve in inertia response and primary frequency regulation task. Finally, the effectiveness of the control strategy is verified by the simulation model of LCCHVDC sending-end system with large-scale wind power, which significantly improves the frequency security and stability.

The effects of a dual task on gaze behavior examined during a simulated flight in low-time pilots.

Cognitive load can impair an operator's ability to optimally scan and process relevant information that is critical to the safe and successful operation of an aircraft. Since the cognitive demands experienced by pilots fluctuate throughout a given flight due to changes in task demands that range from high to low cognitive load, it has become increasingly important to objectively track and quantify these changes accordingly. The analysis of eye movements has been shown to be a promising method to understand information acquisition, processing efficiency, and how these aspects of cognition impact pilot performance. Therefore, the aim of the current study was to assess the impact of a dual task paradigm on low-time pilot flight performance and gaze behavior during two phases of flight with varying levels of cognitive load. Twenty-two licensed pilots (<350 h) completed simulated flight circuits alongside an auditory oddball task under visual flight rules conditions. Self-reported situation awareness scores and auditory task performance revealed the dual task was more demanding than the single tasks. Flight performance and gaze behavior indicated that primary task performance and information processing remained unaffected. These results suggest that the recruited pilots attained a level of skill proficiency that enabled the efficient deployment of cognitive resources to successfully complete the flying task under states of increased cognitive load. Combined with previous research findings, the results suggest that the effect of secondary tasks depends on the type of tasks used (i.e., simple/choice response tasks, memory recall, etc.). The utility of using a dual task and gaze behavior to probe flight proficiency and information processing efficiency throughout training are discussed.

Neural activation patterns in open-skilled and closed-skilled athletes during motor response tasks: insights from ERP analysis.

The present study explored behavioral outcomes and neural correlates of cognitive control abilities in open-skill sports athletes compared with closed-skill sports athletes. The participants of the study were 16 right-handed male athletes. Nine basketball players formed a group of athletes from open-skill sports, and seven outdoor track and field runners formed a comparison group for closed-skill sports. During the two-color Choice Response Time task with simultaneous EEG registration, psychophysiological observation was performed to assess athletes' functioning. A significant interaction between a sports type and the hand reveals more symmetrical functioning of the hands in basketball players, which is also confirmed by the neural activity of brain regions responsible for motor action (C3 and C4). Although there was no main effect of the sport type, the study revealed closer patterns of motor action and neural regulation of the left and right hand in open-skilled athletes than in closed-skilled athletes.

An enhanced dynamic-network-based framework for quantifying and enhancing the resilience of disaster response networks to old communities under rainstorm waterlogging

Developing effective disaster response networks (DRNs) is crucial for mitigating the impacts of rainstorm waterlogging in old communities. Aiming at providing implementable strategies for enhancing DRN resilience, this paper developed an enhanced dynamic network analysis (DNA)-based framework for DRNs utilizing the DNA and CRITIC-VIKOR method. This framework conceptualizes community disaster response as a three-stage ‘agent-information-resource-task’ (A-I-R-T) dynamic network, facilitating a comprehensive understanding of interactions among stakeholders, disaster information, emergency resources, and response tasks. Subsequently, a hybrid evaluation model combining CRITIC and VIKOR methods was established to quantify DRN resilience by assessing deviations from ideal response scenarios. Validated through a case study of the Y community in Xuzhou city of China, the findings reveal significant variations in stakeholder communication effectiveness across different stages of disaster response, with resilience peaking during the function recovery stage at 0.292. This study not only contributes to the body of knowledge in disaster management and resilience theory but also provides actionable strategies for enhancing DRN resilience, thereby contributing to more resilient urban environments.

How Freely Moving Mind Wandering Relates to Creativity: Behavioral and Neural Evidence.

Background: Previous studies have demonstrated that mind wandering during incubation phases enhances post-incubation creative performance. Recent empirical evidence, however, has highlighted a specific form of mind wandering closely related to creativity, termed freely moving mind wandering (FMMW). In this study, we examined the behavioral and neural associations between FMMW and creativity. Methods: We initially validated a questionnaire measuring FMMW by comparing its results with those from the Sustained Attention to Response Task (SART). Data were collected from 1316 participants who completed resting-state fMRI scans, the FMMW questionnaire, and creative tasks. Correlation analysis and Bayes factors indicated that FMMW was associated with creative thinking (AUT). To elucidate the neural mechanisms underlying the relationship between FMMW and creativity, Hidden Markov Models (HMM) were employed to analyze the temporal dynamics of the resting-state fMRI data. Results: Our findings indicated that brain dynamics associated with FMMW involve integration within multiple networks and between networks (r = -0.11, pFDR < 0.05). The links between brain dynamics associated with FMMW and creativity were mediated by FMMW (c' = 0.01, [-0.0181, -0.0029]). Conclusions: These findings demonstrate the relationship between FMMW and creativity, offering insights into the neural mechanisms underpinning this relationship.

A fast-aware multi-target response prediction approach and its application in aeronautical engineering

Response prediction is a fundamental yet challenging task in aeronautical engineering, requiring an accurate selection of sensor positions correlated with the target responses to achieve precise predictions. Unfortunately, in large-scale structures, the rigorous selection of reliable sensor candidates for multi-target responses remains largely unexplored. In this paper, we propose a flexible and generalized framework for selecting the most relevant sensors to the multi-target response and predicting the target response, referred to as the Fast-aware Multi-Target Response Prediction (FMTRP) approach in the spirit of divide-and-conquer. Specifically, first, a multi-task learning module is designed to predict multi-point response tasks at the same time. Simultaneously, we meticulously devise adaptive mechanisms to facilitate loss-term reweighting and encourage prioritization of challenging tasks in multiple prediction tasks. Second, to ensure ease of interpretation, we introduce a hybrid penalty to select sensors at the group-sparsity, individual-sparsity and element-sparsity levels. Finally, due to the substantial number of candidate sensors posing a significant computational burden, we develop a more efficient search strategy and support computation to make the proposed approach applicable in practice, leading to substantial runtime improvements. Extensive experiments on aircraft standard model response datasets and large airliner test flight datasets validate the effectiveness of the proposed approach in identifying sensor locations and simultaneously predicting responses at multiple points. Compared to state-of-the-art methods, the proposed approach achieves an accuracy of over 99% in sinusoidal excitation and exhibits the shortest runtime (3.514 s).

The effect of Ashwagandha (Withania somnifera) supplementation on sleep, mood, and cognitive function in healthy university students

University students often face high levels of stress and sleep disturbances due to their academic demands and lifestyle factors(1). Ashwagandha (Withania somnifera), an adaptogenic herb, has shown the potential to mitigate stress and improve cognitive function(2). However, limited research has examined its effects on these variables in university students. This study aimed to determine the effects of ashwagandha supplementation on sleep quality, mood, and cognitive function in university students.A randomized, double-blind, placebo-controlled crossover study was used. Nine university students (5 males, 4 females; Age: 21 ± 1 years; BMI: 25 ± 2.5 kg/m2) were randomly assigned to receive 500 mg of standardized ashwagandha root extract capsules for 7 days or a placebo (encapsulated cornstarch) with a 7-day washout between treatments. Sleep was measured during the 7-day supplementation period using the Loughborough Daily Sleep Diary. Postsupplementation mood and cognitive function were measured by the Profile of Mood States (POMS) scale(3) and computerised Stroop, and Deary-Liewald simple and choice reaction tasks(4). Paired sample t-tests were used to determine differences between the ashwagandha and placebo conditions with calculated effect sizes (Cohen’s d).Participants reported lower confusion indicator on the POMS following ashwagandha compared to the placebo (mean ± SD: 4.8 ± 2.0 vs 7.6 ± 3.1 arbitrary units; P = 0.03; d = −0.92). No other differences were found for any other mood indicators, sleep, or cognitive function parameters (P &gt; 0.05).These data suggest that ashwagandha may improve feelings of confusion in university students but further studies with larger sample sizes are needed to verify these findings and elucidate the underlying mechanisms.

The effect of a neuromuscular-cognitive training program on postural stability, hop performance, and agility in Division-I Women's Tennis athletes: A pilot study

BackgroundSituational awareness and cognitive function are often discounted in sports training programs, potentially limiting their effectiveness. ObjectiveThis research aimed to examine the effect of a six-week neuromuscular-cognitive training program on postural stability, hop performance, and agility with and without perceptual-cognitive challenge in a tennis team. DesignDouble baseline, quasi-experimental pretest-posttest. MethodsTen collegiate female tennis athletes volunteered to participate in this study. Participants completed two baseline testing sessions, a six-week training program, and a post-test session one week after the training program. Participants completed the neuromuscular-cognitive training twice a week for six weeks. The training integrated cognitive load (e.g., working memory and inhibitory control) during exercise (e.g., balance and shuffling). At each data collection session, subjects completed a single-limb stance on a force plate with and without an upper extremity reaction test, single-leg hop, single-leg memory hop, reactive agility, and a lower extremity reaction task. Pre-to post-intervention changes were analyzed using t-tests with corresponding Hedge's g effect sizes. Results were considered significant when p ≤ 0.05 and Hedge's g effect sizes were moderate to strong. ResultsStatistically significant improvements were identified for single and dual-task anteroposterior mean center of pressure velocity (g = −0.684–0.803), single-task time-to-boundary mediolateral mean minima (g = 0.921), and single and dual-task time-to-boundary anteroposterior mean minima (0.708–0.830). Additionally, significant improvements were identified in the upper extremity reaction task during the dual-task static balance (g = −0.795). ConclusionNeuromuscular-cognitive training may be beneficial in improving postural stability outcomes; however, more research is needed to develop this type of training further.