Task Response Time Research Articles

Practice makes better? The influence of increased practice on task conflict in the Stroop task.

The Stroop task is widely used to study attentional control and cognitive flexibility. However, questions about its sensitivity to training and the impact of task conflict on attentional control remain open. We investigated the effects of practice and task conflict on attentional control in the Stroop task, with participants completing four sessions of a Stroop task over 3 weeks in low and high task-conflict conditions. Our results show that the level of task conflict had an impact only in the first session, even though participants remained sensitive to task conflict throughout all four sessions. Moreover, we found that practice reduced response times in the Stroop task, for both congruent and incongruent trials. Nevertheless, the interference between congruent and incongruent stimuli remained consistent over the 3-week period, indicating that inter-condition interference is not affected by training. Our study, therefore, suggests that the extent to which the level of task conflict modulates Stroop task performance is only partially sensitive to training. These findings provide further insights into the role of task conflict and practice in attentional control and cognitive flexibility.

Parameter identifiability in evidence-accumulation models: The effect of error rates on the diffusion decision model and the linear ballistic accumulator.

A variety of different evidence-accumulation models (EAMs) account for common response time and accuracy patterns in two-alternative forced choice tasks by assuming that subjects collect and sum information from their environment until a response threshold is reached. Estimates of model parameters mapped to components of this decision process can be used to explain the causes of observed behavior. However, such explanations are only meaningful when parameters can be identified, that is, when their values can be uniquely estimated from data generated by the model. Prior studies suggest that parameter identifiability is poor when error rates are low but have not systematically compared this issue across different EAMs. We conducted a simulation study investigating the identifiability and estimation properties of model parameters at low error rates in the two most popular EAMs: The diffusion decision model (DDM) and the linear ballistic accumulator (LBA). We found poor identifiability at low error rates for both models but less so for the DDM and for a larger number of trials. The DDM also showed better identifiability than the LBA at low trial numbers for a design with a manipulation of response caution. Based on our results, we recommend tasks with error rates between 15% and 35% for small, and between 5% and 35% for large trial numbers. We explain the identifiability problem in terms of trade-offs caused by correlations between decision-threshold and accumulation-rate parameters and discuss why the models differ in terms of their estimation properties.

Non-dominant hand contractions do not facilitate performance under pressure in common desktop tasks.

Non-dominant hand contractions (NDHCs) have been shown to help expert motor skills in high-pressure scenarios that induce performance anxiety. Most studies of NHDCs under pressure have examined benefits in overlearned specialist movements (e.g., sporting skills), while few have considered if NDHCs can aid common movements with population-wide expertise (e.g., typing). Accordingly, across three experiments, we explored if NDHCs could protect or facilitate performance under time and/or evaluation pressure in a cursor positioning task (Experiments 1 & 2) and a typing task (Experiment 3). Despite varying the nature of the task, pressure manipulation, and design, and successfully manipulating state anxiety in each experiment, we found no evidence that NDHCs assist performance under pressure in these tasks. For the pressure × contraction condition interaction, the largest inclusion Bayes Factor was .40 for task response time and .62 for task error (Experiment 1), indicating evidence in favour of a null result. Our results, along with other recent studies in this area, cast doubt on the benefits of NDHCs under pressure outside sporting tasks and underline the need for a better mechanistic account of the phenomenon.

Beat the heat: wearable-based study of perceived heat stress and physiological strain in swiss track workers in a controlled climate chamber

Increasing temperatures pose new challenges for track workers (TWs), who endure prolonged exposure to extreme heat and humidity. New methods are critically needed to assess their performance and heat tolerance, aiming to mitigate workplace accidents and long-term health consequences. This study aimed to investigate the physiological effects of heat exposure on TWs, using wearable sensors to monitor key physiological parameters under controlled environmental conditions. Nineteen TWs participated in the study, which included two experimental sessions simulating different thermal environments: a typical Swiss summer night and a hot summer day. Participants' core body temperature, heart rate (HR), and skin temperature were monitored using wearable sensors, and physiological indexes were computed. In addition, perceptual strain index (PeSI) and psychomotor vigilance task (PVT) response times were recorded. Statistically significant increases in physiological parameters were observed under hotter conditions. The study identified statistically significant correlations between the PeSI and the physiological strain index and between PeSI and HR. Perceptual scores were consistently higher than the values derived from physiological measurements, suggesting a greater subjective experience of heat strain. The PVT response times were higher on the hotter day, reflecting increased cognitive strain due to heat exposure. The study highlights the critical impact of heat stress on TWs, with statistically significant increases in physiological and cognitive strain under higher temperatures. Future research should focus on real-world applications of heat strain monitoring.

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.

The brain under pressure: Exploring neurophysiological responses to cognitive stress

Stress is an increasingly dominating part of our daily lives and higher performance requirements at work or to ourselves influence the physiological reaction of our body. Elevated stress levels can be reliably identified through electroencephalogram (EEG) and heart rate (HR) measurements. In this study, we examined how an arithmetic stress-inducing task impacted EEG and HR, establishing meaningful correlations between behavioral data and physiological recordings. Thirty-one healthy participants (15 females, 16 males, aged 20 to 37) willingly participated. Under time pressure, participants completed arithmetic calculations and filled out stress questionnaires before and after the task. Linear mixed effects (LME) allowed us to generate topographical association maps showing significant relations between EEG features (delta, theta, alpha, beta, and gamma power) and factors such as task difficulty, error rate, response time, stress scores, and HR. With task difficulty, we observed left centroparietal and parieto-occipital theta power decreases, and alpha power increases. Furthermore, frontal alpha, delta and theta activity increased with error rate and relative response time, while parieto-temporo-occipital alpha power decreased. Practice effects on EEG power included increases in temporal, parietal, and parieto-occipital theta and alpha activity. HR was positively associated with frontal delta, theta and alpha power whereas frontal gamma power decreases. Significant alpha laterality scores were observed for all factors except task difficulty and relative response time, showing overall increases in left parietal regions. Significant frontal alpha asymmetries emerged with increases in error rate, sex, run number, and HR and occipital alpha asymmetries were also found with run number and HR. Additionally we explored practice effects and noted sex-related differences in EEG features, HR, and questionnaire scores. Overall, our study enhances the understanding of EEG/ECG-based mental stress detection, crucial for early interventions, personalized treatment and objective stress assessment towards the development of a neuroadaptive system.

Mind wandering is associated with worsening attentional vigilance.

The tendency for our minds to wander is a pervasive and disruptive influence on continued task performance. Models of sustained attention have implicated mind wandering, moments when attention has turned inwards toward task-unrelated thought, in characteristic patterns of worsening performance with greater time-on-task, known as the vigilance decrement. Despite their theoretical connection, associations between mind wandering and the vigilance decrement have not been investigated systematically. Across two studies (N = 730), we evaluated covariance between within-task change in rates of probe-caught mind wandering and patterns of worsening behavioral task performance that characterize the vigilance decrement. Bivariate growth curve models characterized patterns of intraindividual linear change in mind wandering alongside concomitant changes in task accuracy, response time (RT), and RT variability. Importantly, models assessing the covariance between intraindividual change in mind wandering and behavioral outcome measures confirmed that increases in mind wandering are associated with patterns of worsening behavioral performance with greater time-on-task. In addition, we investigated the role of several moderating factors associated with patterns of within-task change: self-reported task interest and motivation, and individuals' propensity for mind wandering, and mindfulness in their daily lives. These factors moderated either the overall level or rate of within-task change in mind wandering. Our results provide support for models of sustained attention that directly implicate mind wandering in worsening behavioral performance with greater time-on-task in continuous performance tasks requiring sustained attention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Enhanced multisensory gain in older adults may be a by-product of inverse effectiveness: Evidence from a speeded response-time task.

Older adults experience a greater benefit from multisensory integration than their younger counterparts, but it is unclear why. One hypothesis is that age-related sensory decline weakens unisensory stimulus effectiveness, causing a boost in multisensory gain through inverse effectiveness. Many previous studies present stimuli at the same intensity for both younger and older adults (i.e., stimulus-matched), as opposed to accounting for each participant's unique perceptual ability (i.e., perception-matched). This makes it difficult to discern the source of age-related differences in multisensory gain. As such, we used two experiments to examine whether sensory decline is contributing to age-related differences in multisensory gain. In the first, we presented auditory (pure tones in noise), visual (Gabor patches in noise), and audiovisual stimuli and recorded response times from 31 younger (18-25) and 30 older (55-80) adults. Importantly, all participants were given identical stimuli, with the expectation that older adults would show worse unisensory performance, inducing inverse effectiveness. The second task was identical (younger N = 31, older N = 34), except stimuli were presented at each participant's 50% detection threshold, identified with an adaptive psychophysical staircase, controlling for any influence of inverse effectiveness. Older adults were found to exhibit greater multisensory gain (as measured by race model violations) on stimulus- but not perception-matched tasks, thus aligning with the principle of inverse effectiveness. That is, when accounting for potential age-related differences in perceptual abilities, older adults no longer experienced greater benefit from multisensory integration. These two experiments together suggest that the age-related increases in multisensory integration previously reported may be in part due to age-related declines in vision and audition. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Soundscape and indoor air quality in naturally ventilated educational environments: a multi-domain study

In this study, indoor air quality (IAQ) and acoustics were jointly analysed to determine their i) combined effect on students' performance in a math task, and ii) cross-modal effect on soundscape perception. 192 students (12 to 14 years) took part in a laboratory experiment. Students were separated into two classroom-like chambers with different IAQ conditions: a CO2 concentration of 800 and 2000 ppm, respectively. The participants were asked to solve calculations and answer a soundscape questionnaire in three listening conditions: quiet, a natural scenario with birdsongs, and one scenario with children's playground activity sounds. In the latter two conditions, the sounds were played back through headphones at a level of 47 dBA. Results show that students had faster response times in the math task in quiet compared to the listening condition with children's activity sounds, while maintaining a similar task accuracy. No effect of the IAQ conditions and natural sounds was found on the task performance. No cross-modal effect of CO2 concentration on soundscape perception was detected. Regarding soundscape assessments, playground activity was rated as the most annoying listening condition, while listening to birdsongs was the most pleasant one, despite its noise level exceeding the quiet condition.

A dopaminergic basis of behavioral control.

Both goal-directed and automatic processes shape human behavior, but these processes often conflict. Behavioral control is the decision about which process guides behavior. Despite the importance of behavioral control for adaptive decision-making, its neural mechanisms remain unclear. Critically, it is unknown if there are mechanisms for behavioral control that are distinct from those supporting the formation of goal-relevant knowledge. We performed deep phenotyping of individual dopamine system function by combining multiple PET scans, fMRI, and dopaminergic drug administration in a within-subject, double-blind, placebo-controlled design. Subjects performed a rule-based response time task, with goal-directed and automatic decision-making operationalized as model-based and model-free influences on behavior. We found a double dissociation between two aspects of ventral striatal dopamine physiology: D2/3 receptor availability and dopamine synthesis capacity. Convergent and causal evidence indicated that D2/3 receptors regulate behavioral control by enhancing model-based and blunting model-free influences on behavior but do not affect model-based knowledge formation. In contrast, dopamine synthesis capacity was linked to the formation of model-based knowledge but not behavioral control. D2/3 receptors also modulated frontostriatal functional connectivity, suggesting they regulate behavioral control by gating prefrontal inputs to the striatum. These results identify central mechanisms underlying individual and state differences in behavioral control and point to striatal D2/3 receptors as targets for interventions for improving goal-directed behavior.

Stroop task response time: A comparison between sequential bilinguals

Research on bilingual individuals provides evidence of a cognitive advantage compared with monolingual speakers. The dominant hypothesis is that language switching for bilingual individuals stimulates the executive function system helping to minimize cognitive interference and allow for multitasking situations. That is, bilingual individuals likely need to actively suppress interference from one language when they are in another language environment. Utilizing the Stroop task, a neuropsychological experiment measuring the brain’s speed and capacity to process competing information, researchers have demonstrated that bilingual speakers perform better than monolingual speakers. However, there is a paucity of research investigating the effect of order of language acquisition. This investigation examines accuracy and speed of verbal responses during a written word Stroop task for bilingual individuals who learned English first compared to bilingual individuals who learned English second. Twenty participants, ten whose language acquisition order was English then Spanish and ten whose language acquisition order was Spanish then English, completed the Stroop task in English. Preliminary results demonstrate no differences between the groups, suggesting language acquisition order does not impact the bilingual advantage in executive functioning.

Peripheral Brain-Derived Neurotrophic Factor (BDNF) and Its Regulatory miRNAs as Biological Correlates of Impulsivity in Young Adults.

Background: Impulsivity assessment may serve as a valuable clinical tool in the stratification of suicide risk. Acting without forethought is a crucial feature in the psychopathology of many psychiatric disturbances and corresponds with suicidal ideations, behaviors, and attempts. Methods: We present data on biological and psychological correlates of impulsivity among young adults (n = 47). Psychological analysis included both the self-description questionnaire-Barratt Impulsiveness Scale (BIS-11)-and neuropsychological behavioral tests, including the Iowa Gambling Task (IGT), the Simple Response Time task (SRT), and the Continuous Performance Test (CPT). mRNA and micro-RNA were isolated from peripheral blood mononuclear cells (PBMC). Expression levels of Brain-Derived Neurotrophic Factor (BDNF) mRNA and its regulatory micro RNAs, mir-1-3p, mir-15a-5p, mir-26a-5p, mir-26b-5p, and mir-195-5p, were analyzed using the quantitative reverse transcription polymerase chain reaction (RT-qPCR) method. proBDNF and BDNF plasma protein levels were quantified using enzyme-linked immunosorbent assay (ELISA). Results: Significant correlations between BDNF mRNA and mir-15a-5p as well as proBDNF levels and mir-1-3p were detected. proBDNF protein levels correlated with motor and perseverance, while mir-26b correlated with cognitive complexity subdimensions of the BIS-11 scale. Correlations between BDNF, miRNAs, and the results of neuropsychological tests were also detected. Conclusions: The BDNF pathway shows a clinical potential in searching for biomarkers of impulse-control impairment. BDNF-regulatory micro-RNAs are detectable and related to clinical parameters in the studied population, which needs further research.

Neural basis of concurrent deliberation toward a choice and degree of confidence.

Decision confidence plays a key role in flexible behavior and (meta)cognition, but its underlying neural mechanisms remain elusive. To uncover the latent dynamics of confidence formation at the level of population activity, we designed a decision task for nonhuman primates that measures choice, reaction time, and confidence with a single eye movement on every trial. Monkey behavior was well fit by a bounded accumulator model instantiating parallel processing of evidence, rejecting a serial model in which the choice is resolved first followed by post-decision accumulation for confidence. Neurons in area LIP reflected concurrent accumulation, exhibiting covariation of choice and confidence signals across the population, and within-trial dynamics consistent with parallel updating at near-zero time lag. The results demonstrate that monkeys can process a single stream of evidence in service of two computational goals simultaneously-a categorical decision and associated level of confidence-and illuminate a candidate neural substrate for this ability.

Vection and Performance During Attention-Demanding Tasks in Virtual Reality

We investigated how attention-demanding aural and visual discrimination tasks attenuate visually-induced self-motion (vection) and how task accuracy and response time are affected by experiencing various levels of vection-inducing motion in a virtual environment. Seventeen seated observers were presented simulated motion at various virtual camera speeds from stationary to 15 m/s in a straight virtual corridor through a Vive Pro Virtual Reality headset as they performed aural, visual discrimination tasks, or no task at all. Observers generally perceived less vection at all motion levels when they performed visual discrimination tasks compared to when they had no task. Increased vection was associated with reduced accuracy on the visual task and increased response time to the aural task. These results suggest that the amount of vection perceived in virtual reality simulators can be attenuated when users perform attention-demanding tasks related to visual processing, and, conversely, vection-producing motion can affect performance in attention-demanding tasks.

EETS: An energy-efficient task scheduler in cloud computing based on improved DQN algorithm

The huge energy consumption of data centers in cloud computing leads to increased operating costs and high carbon emissions to the environment. Deep Reinforcement Learning (DRL) technology combines of deep learning and reinforcement learning, which has an obvious advantage in solving complex task scheduling problems. Deep Q Network(DQN)-based task scheduling has been employed for objective optimization. However, training the DQN algorithm may result in value overestimation, which can negatively impact the learning effectiveness. The replay buffer technique, while increasing sample utilization, does not distinguish between sample importance, resulting in limited utilization of valuable samples. This study proposes an enhanced task scheduling algorithm based on the DQN framework, which utilizes a more optimized Dueling-network architecture as well as Double DQN strategy to alleviate the overestimation bias and address the shortcomings of DQN. It also incorporates a prioritized experience replay technique to achieve importance sampling of experience data, which overcomes the problem of low utilization due to uniform sampling from replay memory. Based on these improved techniques, we developed an energy-efficient task scheduling algorithm called EETS (Energy-Efficient Task Scheduling). This algorithm automatically learns the optimal scheduling policy from historical data while interacting with the environment. Experimental results demonstrate that EETS exhibits faster convergence rates and higher rewards compared to both DQN and DDQN. In scheduling performance, EETS outperforms other baseline algorithms in key metrics, including energy consumption, average task response time, and average machine working time. Particularly, it has a significant advantage when handling large batches of tasks.

Collaborative learning-based inter-dependent task dispatching and co-location in an integrated edge computing system

Recently, several edge deployment types, such as on-premise edge clusters, Unmanned Aerial Vehicles (UAV)-attached edge devices, telecommunication base stations installed with edge clusters, etc., are being deployed to enable faster response time for latency-sensitive tasks. One fundamental problem is where and how to offload and schedule multi-dependent tasks so as to minimize their collective execution time and to achieve high resource utilization. Existing approaches randomly dispatch tasks naively to available edge nodes without considering the resource demands of tasks, inter-dependencies of tasks and edge resource availability. These approaches can result in the longer waiting time for tasks due to insufficient resource availability or dependency support, as well as provider lock-in. Therefore, we present EdgeColla, which is based on the integration of edge resources running across multi-edge deployments. EdgeColla leverages learning techniques to intelligently dispatch multi-dependent tasks, and a variant bin-packing optimization method to co-locate these tasks firmly on available nodes to optimally utilize them. Extensive experiments on real-world datasets from Alibaba on task dependencies show that our approach can achieve optimal performance than the baseline schemes.

Reliability and minimal detectable change of the Yoni task for the theory of mind assessment.

The Theory of Mind (ToM) assessment is becoming essential to evaluate the response to a social cognition intervention and to monitor the progression of social abilities impairment in atypical conditions. In the Italian setting, the Yoni task has been recently validated in its short version (the Yoni-48 task) to evaluate ToM in the clinical setting. The present study aimed to verify the test-retest reliability and the Minimal Detectable Change (MDC) of the Yoni-48 task. The Yoni-48 task was administered to 229 healthy adults at two evaluation sessions 3 weeks apart (mean days between sessions = 20.35 ± 1.75) by a psychologist. The test-retest reliability of the Yoni-48 task accuracy and response time was tested by the Intraclass Correlation Coefficient (ICC2,1, two-way random model, absolute agreement type). Then, the MDC95 and MDC90 were computed based on the standard error of measurement. Finally, the 95% limits of agreement were plotted (LOA plot) to visualize the difference and mean score of each pair of measurements. The total Yoni-48 task accuracy, but not the response time score, showed a high ICC (>0.80), with an MDC of 0.10. By plotting the LOA plot for the accuracy score no systematic trends were observed. This evidence will support the adoption of the Yoni task in longitudinal designs.

People are more error-prone after committing an error

Humans tend to slow down after making an error. A longstanding account of this post-error slowing is that people are simply more cautious. However, accuracy typically does not improve following an error, leading some researchers to suggest that an initial ‘orienting’ response may initially impair performance immediately following error. Unfortunately, characterizing the nature of this error-based impairment remains a challenge in standard tasks that use free response times. By exerting control over the timing of responses, we reveal the time course of stimulus-response processing. Participants are less accurate after an error even when given ample time to make a response. A computational model of response preparation rules out the possibility that errors lead to slower cognitive processing. Instead, we find that the efficacy of cognitive processing in producing an intended response is impaired following errors. Following an error, participants commit more slips of action that tend to be a repetition of the previous mistake. Rather than a strategic shift along a single speed-accuracy tradeoff function, post-error slowing observed in free response time tasks may be an adaptive response to impaired cognitive processing that reflects an altered relationship between the speed and accuracy of responses.

Adding a sustained attention task to a physically demanding cycling exercise exacerbates neuromuscular fatigue and impairs cognitive performance in both normoxia and hypoxia.

Both cognitive motor dual-tasks (CMDT) protocols and hypoxic environments have been associated with significant impairments in cognitive and physical performance. We aimed to determine the effects of hypoxia on cognitive performance and neuromuscular fatigue during a highly physically demanding CMDT. Fifteen young adults completed a first session involving a cognitive task (CTLCOG) followed by cycling exercise (CTLEX) in normoxia. After that, they randomly participated in CMDT sessions in normoxia (DTNOR) and hypoxia (DTHYP). The physical exercise consisted of 20min cycling at a "hard" perceived effort, and the cognitive task consisted of 15min sustained attention to response time task (SART). Concurrent psycho-physiological measurements included: quadriceps neuromuscular fatigue (peripheral/central components from femoral nerve electrostimulation), prefrontal cortex (PFC) oxygenation by near-infrared spectroscopy, and perception of effort. SART performance significantly decreased in DTNOR (-15.7 ± 15.6%, P < 0.01) and DTHYP (-26.2 ± 16.0%, P < 0.01) compared to CTLCOG (-1.0 ± 17.7%, P = 0.61). Peripheral fatigue similarly increased across conditions, whereas the ability of the central nervous system to activate the working muscles was impaired similarly in DTNOR (-6.1 ± 5.9%, P < 0.001) and DTHYP (-5.4 ± 7.3%, P < 0.001) compared to CTLEX (-1.1 ± 0.2%, P = 0.52). Exercise-induced perception of effort was higher in DTHYP vs. DTNOR and in DTNOR vs. CTLEX. This was correlated with cognitive impairments in both normoxia and hypoxia. PFC deoxygenation was more pronounced in DTHYP compared to DTNOR and CTLEX. In conclusion, performing a sustained attention task together with physically challenging cycling exercise promotes central neuromuscular fatigue and impairs cognitive accuracy; the latter is particularly noticeable when the CMDT is performed in hypoxia.

Integrated analysis of reliability, power, and performance for IoT devices and servers

The Internet of Things (IoT) is currently widely used in various sectors and spaces. IoT devices are becoming small yet powerful servers and perform server-like functions. Reliability is a critical aspect in both IoT devices and servers, as they work together to create a robust and dependable IoT ecosystem. Power and performance are two other major considerations of an IoT system. Modeling, analysis, evaluation, and optimization of reliability, power, and performance for IoT devices and servers are major components in IoT systems development and deployment. In this paper, we conduct an integrated study of reliability, power, and performance for IoT devices and servers by mathematically rigorous modeling and analysis. The contributions of the paper can be summarized as follows. We establish a continuous-time Markov chain (CTMC) model that incorporates server failure rate, server repair rate, task arrival rate, and task processing rate. Using such an analytical model, we can calculate the server availability, the average task response time, and the average power consumption. We point out that there is an optimal server speed that minimizes the power-time product and a combined cost-performance metric of power, performance, and reliability. We show the impact of server reliability on response time, power consumption, server utilization, and the power-performance tradeoff. To the best of the author’s knowledge, this is the first paper that takes a combined approach to modeling and analysis of reliability, power, and performance for IoT devices and servers. It has been noticed that there has been little such theoretically solid investigation in the existing literature. Therefore, this paper has made tangible contributions and significant advances in the joint understanding of reliability, power, performance, and their interplay in IoT devices and servers quantitatively and mathematically.