Objective Of Task Research Articles

Decreased Knee Extensor Torque During Single-Limb Stance: A Computer Simulation Study of Compensations and Consequences

Background/Objectives: For over 50 years, it has been suggested that the plantar flexors and hip extensors can compensate for weak knee extensors and prevent collapse of the leg during a single-limb stance. However, the effects of these compensations have not been studied thoroughly. The purpose of this computer simulation study was to determine, for a given posture, the hip and ankle net joint torque (NJT) required to prevent leg collapse due to systematic decreases in knee NJT and to determine the effect of these compensations on the horizontal ground reaction force. Methods: Single-limb stance was simulated using a static, multisegmented model in eight different postures. For each posture, the knee NJT was systematically decreased. The ankle and knee NJT necessary to prevent lower extremity collapse, along with any net horizontal ground reaction forces, were then calculated. Results: Decreases in knee NJT required linear increases in ankle and hip NJT to prevent the limb from collapsing. There were greater increases in ankle NJT compared to hip NJT, resulting in posteriorly-directed horizontal ground reaction forces. While the magnitudes were different, these findings applied to all postures simulated. Conclusions: For a given posture, ankle and hip NJTs can compensate for a decrease in knee NJT. However, this resulted in a horizontal ground reaction force, which was in the posterior direction for all the postures examined. This horizontal ground reaction force would induce an acceleration on the body’s center of mass that, if not accounted for, could have deleterious effects on achieving a task objective.

An efficient deep reinforcement learning based task scheduler in cloud-fog environment

Efficient task scheduling in cloud and fog computing environments remains a significant challenge due to the diverse nature and critical processing requirements of tasks originating from heterogeneous devices. Traditional scheduling methods often struggle with high latency and inadequate processing times, especially in applications demanding strict computational efficiency. To address these challenges, this paper proposes an advanced fog-cloud integration approach utilizing a deep reinforcement learning-based task scheduler, DRLMOTS (Deep Reinforcement Learning based Multi Objective Task Scheduler in Cloud Fog Environment). This novel scheduler intelligently evaluates task characteristics, such as length and processing capacity, to dynamically allocate computation to either fog nodes or cloud resources. The methodology leverages a Deep Q-Learning Network model and includes extensive simulations using both randomized workloads and real-world Google Jobs Workloads. Comparative analysis demonstrates that DRLMOTS significantly outperforms existing baseline algorithms such as CNN, LSTM, and GGCN, achieving a substantial reduction in makespan by up to 26.80%, 18.84, and 13.83% and decreasing energy consumption by up to 39.60%, 30.29%, and 27.11%. Additionally, the proposed scheduler enhances fault tolerance, showcasing improvements of up to 221.89%, 17.05%, and 11.05% over conventional methods. These results validate the efficiency and robustness of DRLMOTS in optimizing task scheduling in fog-cloud environments.

EDLIoT: A method for decreasing energy consumption and latency using scheduling algorithm in Internet of Things

Decreasing energy consumption in networks with limited resources, such as the Internet of Things, has always been one of the main challenges in guaranteeing network performance. In this article, cooperative game theory is employed to improve the cooperation patterns of fog computing resources. The EDLIoT method consists of two main steps: “Topology Construction” and “Determining Optimal Fog Computing Resources to Process IoT Object Tasks”. In the first step of the proposed method, the set of reliable communications in the network is identified to establish connections between IoT objects and fog computing resources in the form of a tree structure. Then, in the second step, a model based on cooperative game theory and the cost function is used to determine the optimal computing resources in the fog layer for outsourcing the processing tasks of IoT objects. In EDLIoT, active IoT objects perform computation in the fog layer instead of locally, to conserve energy. This is done so that IoT objects, if possible, discover the most suitable processing resources in the fog based on characteristics such as energy consumption, delay, and processing power of the computing resource. The efficiency of the proposed method has been evaluated in a simulated environment, and the results have been compared with those of previous algorithms. The results demonstrate that using the EDLIoT method, in addition to decreasing energy consumption and delay, more computing tasks can be processed through fog resources, thereby increasing the quality of service for IoT users.

The Remedial Values of Adaptive Ball Types for Children with Autism Spectrum Disorders

Previous studies in the area of motor impairments in children with autism spectrum disorders (ASDs) have warranted an urgent need to review interventions that support fundamental movement skills (FMS). This paper intends to investigate the effectiveness of adaptive ball types used within Physical Education (PE) on the object control proficiency (a subgroup of FMS), in children with ASDs. Following pilot work, 12 children (aged 14.70 ± 2.70) performed four object control tasks (throwing, catching, kicking and soccer style dribbling), using three different ball types (the Developmental Ball, an underweight ball and a control ball). A repeated measures ANOVA was run to statically analyse performance scores. The ANOVA indicated that the type of ball used (f(2,22) 22.798, p<0.001), activity undertaken (f(3,33)= 12.377, p<0.01) and the interaction between the two (f(6,66)=-70.163, p<0.01) ultimately, had a significant effect on motor proficiency. Moreover, the Developmental Ball proved to be consistently beneficial across the object control skills, with post hoc t-tests showing strong significance against the underweight ball in kicking (t(11)=-3,031, p<0. 033) and soccer style dribbling (t(11)=-8.603, p<0.016). This paper concludes Skogstad’s creation to be an invaluable blueprint for the development of fundamental object control skills, in children with ASDs.

A large-scale examination of inductive biases shaping high-level visual representation in brains and machines

The rapid release of high-performing computer vision models offers new potential to study the impact of different inductive biases on the emergent brain alignment of learned representations. Here, we perform controlled comparisons among a curated set of 224 diverse models to test the impact of specific model properties on visual brain predictivity – a process requiring over 1.8 billion regressions and 50.3 thousand representational similarity analyses. We find that models with qualitatively different architectures (e.g. CNNs versus Transformers) and task objectives (e.g. purely visual contrastive learning versus vision- language alignment) achieve near equivalent brain predictivity, when other factors are held constant. Instead, variation across visual training diets yields the largest, most consistent effect on brain predictivity. Many models achieve similarly high brain predictivity, despite clear variation in their underlying representations – suggesting that standard methods used to link models to brains may be too flexible. Broadly, these findings challenge common assumptions about the factors underlying emergent brain alignment, and outline how we can leverage controlled model comparison to probe the common computational principles underlying biological and artificial visual systems.

Investigating the impact of mental rehearsal on prefrontal and motor cortical haemodynamic responses in surgeons using optical neuroimaging.

Inadequate exposure to real-life operating can impede timely acquisition of technical competence among surgical residents, and is a major challenge faced in the current training climate. Mental rehearsal (MR)-the cognitive rehearsal of a motor task without overt physical movement-has been shown to accelerate surgical skills learning. However, the neuroplastic effect of MR of a complex bimanual surgical task is unknown. The aim of this study is to use functional near-infrared spectroscopy (fNIRS) to assess the impact of MR on prefrontal and motor cortical activation during a laparoscopic knot tying task. Twelve surgical residents performed a laparoscopic knot tying task before and after either mental rehearsal (MR, intervention group) or textbook reading (TR, control group). In both groups, fNIRS was used to measure changes in oxygenated hemoglobin concentration (HbO2) in the prefrontal (24 channels) and motor cortices (22 channels). Technical performance was measured using leak volume, objective performance score and task progression score. MR led to a decrease in HbO2 (reduced activation) in the bilateral prefrontal cortex (PFC), and an increase in HbO2 (increased activation) in the left middle frontal gyrus, left precentral gyrus, and left postcentral gyrus. No discernible changes in activation were observed after TR in either the PFC or motor cortex. Moreover, smaller ΔHbO2 responses in the right PFC and greater ΔHbO2 responses in the left motor cortex were observed in the MR group compared with the TR group. Leak volume was significantly less following MR (p = 0.019), but not after TR (p = 0.347). Mean objective performance score was significantly higher following MR compared with TR (p = 0.043). Mental rehearsal may enhance surgical skill acquisition and technical proficiency by reducing utilization of attentional resources in the prefrontal cortex and improving neural efficiency in motor areas during a laparoscopic surgical task.

Using fMRI to examine nonlinear mixed selectivity tuning to task and category in the human brain

Abstract Recent experimental and theoretical work has shown that nonlinear mixed selectivity, where neurons exhibit interaction effects in their tuning to multiple variables (e.g., stimulus and task) plays a key role in enabling the primate brain to form representations that can adapt to changing task contexts. Thus far all such studies have relied on invasive neural recording techniques. In this study, we demonstrate the feasibility of measuring nonlinear mixed selectivity tuning in the human brain noninvasively using fMRI pattern decoding. To do so, we examined the joint representation of object category and task information across human early, ventral stream, and dorsal stream areas while participants performed either an oddball detection task or a one-back repetition detection task on the same stimuli. These tasks were chosen to equate spatial, object-based, and feature-based attention, in order to test whether task modulations of visual representations still occur when the inputs to visual processing are kept constant between the two tasks, with only the subsequent cognitive operations varying. We found moderate but significant evidence for nonlinear mixed selectivity tuning to object category and task in fMRI response patterns in both human ventral and dorsal areas, suggesting that neurons exhibiting nonlinear mixed selectivity for category and task not only exist in these regions, but cluster at a scale visible to fMRI. Importantly, while such coding in ventral areas corresponds to a rotation or shift in the object representational geometry without changing the representational content (i.e., with the relative similarity among the categories preserved), nonlinear mixed selectivity coding in dorsal areas corresponds to a reshaping of representational geometry, indicative of a change in representational content.

Perceptual Expertise and Attention: An Exploration using Deep Neural Networks.

Perceptual expertise and attention are two important factors that enable superior object recognition and task performance. While expertise enhances knowledge and provides a holistic understanding of the environment, attention allows us to selectively focus on task-related information and suppress distraction. It has been suggested that attention operates differently in experts and in novices, but much remains unknown. This study investigates the relationship between perceptual expertise and attention using convolutional neural networks (CNNs), which are shown to be good models of primate visual pathways. Two CNN models were trained to become experts in either face or scene recognition, and the effect of attention on performance was evaluated in tasks involving complex stimuli, such as superimposed images containing superimposed faces and scenes. The goal was to explore how feature-based attention (FBA) influences recognition within and outside the domain of expertise of the models. We found that each model performed better in its area of expertise-and that FBA further enhanced task performance, but only within the domain of expertise, increasing performance by up to 35% in scene recognition, and 15% in face recognition. However, attention had reduced or negative effects when applied outside the models' expertise domain. Neural unit-level analysis revealed that expertise led to stronger tuning towards category-specific features and sharper tuning curves, as reflected in greater representational dissimilarity between targets and distractors, which, in line with the biased competition model of attention, leads to enhanced performance by reducing competition. These findings highlight the critical role of neural tuning at single as well as network level neural in distinguishing the effects of attention in experts and in novices and demonstrate that CNNs can be used fruitfully as computational models for addressing neuroscience questions not practical with the empirical methods.

Fasudil attenuates lipopolysaccharide-induced cognitive impairment in C57BL/6 mice through anti-oxidative and anti-inflammatory effects: Possible role of aquaporin-4

IntroductionProcesses that generate systemic inflammation are strongly associated with neurodegenerative diseases. This study aimed to explore the potential anti-oxidative and anti-inflammatory effects of fasudil and its role in modulating aquaporin-4 (AQP-4) to improve cognitive impairment in a systemic inflammation model induced by lipopolysaccharide (LPS). Methodfourty C57BL/6 mice were assigned to four groups, including sham, LPS, sham+fasudil, and LPS+fasudil). Intraperitoneal LPS was given (500μg/kg/day) at hours 0, 24, 48, and 72, and fasudil (30mg/kg) administered intraperitoneal injections 2hours after LPS injection. The open field, Y-maze, and Novel object tasks was used to assess learning and memory. The levels of malondialdehyde (MDA), superoxide dismutase (SOD), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α) in the hippocampus also measured as markers of oxidative stress and inflammation. Furthermore, the expression of AQP-4 measured in the intact and experimental groups. ResultsThe results showed that Fasudil significantly improved memory and anxiety behavior induced by LPS in the open field maze, spatial recognition memory in the Y-maze, and performance in the novel object recognition task. It also mitigates hippocampal MDA and SOD levels. Additionally, fasudil ameliorated LPS-induced hippocampal levels of TNFα and IL-10 and increased hippocampal levels of AQP-4 expression in mice. ConclusionOur results suggest that fasudil in the LPS model of systemic inflammation could improve cognition by suppressing oxidative stress and inflammation and increasing AQP-4 protein expression. These findings highlighted the potential of fasudil as a neuroprotective agent. However, further research is required to fully understand its neuroprotective properties in the treatment of neurodegenerative disorders.

The Moderating Role of Interest in the Relationship between Perceived Task Difficulty and Invested Mental Effort

Including motivational variables such as interest in the cognitive load framework is an ongoing process. Of particular interest is the question of how motivational variables influence the investment of mental effort. In this study, we investigated how topic interest affects the investment of mental effort in simple tasks. A total of 1543 students’ judgments regarding invested mental effort, perceived task difficulty, and topic interest for 32 tasks of a chemistry test were analyzed at the task level based on item response theory parameters. Additionally, objective task difficulty was calculated. The Rasch parameters were used for correlation and moderated regression analyses. The results indicated that when perceived task difficulty was low, students invested more mental effort in solving tasks of low topic interest compared to tasks of high topic interest. With increasing perceived task difficulty, the amount of invested mental effort rose for tasks of low as well as high topic interest. However, the difference between tasks of low and high topic interest in the amount of invested mental effort decreased as perceived task difficulty increased and even vanished when perceived task difficulty roughly corresponded to students’ performance capability. These results are in line with flow theory and the expectancy-value-cost model of motivation. When solving tasks that match their performance capability, students can experience a flow situation. However, when solving rather easy tasks of low interest, students can experience motivational costs in terms of additional effort, such as an increased need for motivational self-regulation. The results of this study provide a basis for systematically investigating and better understanding the relationship between interest, task difficulty, invested mental effort, flow experience, and emotional costs.

The inflexible mind: A critical factor in understanding and addressing COVID-19 vaccine hesitancy

BackgroundVaccine hesitancy has gained heightened relevance amid the COVID-19 pandemic, underscoring the urgency of understanding its determinants. This study explores the association between Covid-19 vaccine hesitancy, mental health variables and inflexible thinking. MethodsA convenience sample of 252 UK adults was assessed online between June 2021–July 2022 (when Covid-19 lockdown restrictions had finally eased). We assessed participants using the Oxford Covid Vaccine Hesitancy Scale (OCVHS), various aspects of mental health, using: the Obsessive-Compulsive Inventory-Revised (OCI-R), Compulsive Personality Assessment Scale (CPAS), Depression, Anxiety, and Stress scale (DASS-21), and finally, performance on a computerized version of the Wisconsin Card Sort Task (WCST). This study was preregistered at the Open Science Framework (https://osf.io/xd5wz). ResultsMultiple regression analyses showed that only cognitive inflexibility, and specifically the WCST item of perseverative errors, significantly predicted vaccine hesitancy. ConclusionOur exploratory analysis provides the first evidence that cognitive inflexibility, measured using an objective task, is an independent risk-factor for vaccine hesitancy. Public health strategies should consider the impact of an inflexible thinking style on the decision-making of those most at risk of vaccine hesitancy and adapt interventions accordingly.

Scaling Learning based Policy Optimization for Temporal Logic Tasks by Controller Network Dropout

This paper introduces a model-based approach for training feedback controllers for an autonomous agent operating in a highly nonlinear (albeit deterministic) environment. We desire the trained policy to ensure that the agent satisfies specific task objectives and safety constraints, both expressed in Discrete-Time Signal Temporal Logic (DT-STL). One advantage for reformulation of a task via formal frameworks, like DT-STL, is that it permits quantitative satisfaction semantics. In other words, given a trajectory and a DT-STL formula, we can compute the robustness , which can be interpreted as an approximate signed distance between the trajectory and the set of trajectories satisfying the formula. We utilize feedback control, and we assume a feed forward neural network for learning the feedback controller. We show how this learning problem is similar to training recurrent neural networks (RNNs), where the number of recurrent units is proportional to the temporal horizon of the agent's task objectives. This poses a challenge: RNNs are susceptible to vanishing and exploding gradients, and naïve gradient descent-based strategies to solve long-horizon task objectives thus suffer from the same problems. To tackle this challenge, we introduce a novel gradient approximation algorithm based on the idea of dropout or gradient sampling. One of the main contributions is the notion of controller network dropout , where we approximate the NN controller in several time-steps in the task horizon by the control input obtained using the controller in a previous training step. We show that our control synthesis methodology, can be quite helpful for stochastic gradient descent to converge with less numerical issues, enabling scalable backpropagation over long time horizons and trajectories over high dimensional state spaces. We demonstrate the efficacy of our approach on various motion planning applications requiring complex spatio-temporal and sequential tasks ranging over thousands of time-steps.

The relationship between openness to experience and humor production: Exploring the mediating roles of cognitive flexibility and ambiguity tolerance.

The purpose of this study was to examine how individual openness to experience influences humor production and to explore the underlying psychological mechanisms of this relationship, specifically focusing on cognitive flexibility (the cognitive path) and ambiguity tolerance (the motivational path). To comprehensively evaluate individuals' humor production ability, Study 1 employed a subjective self-report questionnaire on sense of humor, while Study 2 used an objective humor dialogue generation task. The results of Study 1 indicated that openness to experience did not directly impact sense of humor; instead, the relationship between openness to experience and sense of humor was fully mediated by cognitive flexibility. In Study 2, findings showed that openness to experience positively predicted humor production ability, with ambiguity tolerance partially mediating this effect. These results suggest that individuals with higher levels of openness to experience have a greater capacity for generating humorous perspectives. Moreover, the study identified two psychological pathways-cognition and motivation-in the process of generating funny ideas. The specific pathway influenced by the measurement method used for humor production further highlights the importance of both cognitive flexibility and ambiguity tolerance in understanding how openness to experience contributes to humor production.

AI translated task setup for non-native English speaking students

University classrooms are increasingly populated by students with diverse nationalities and native languages (L1). The growing number of students in English-led classrooms who speak English as a second or lower language (L2) may face added difficulties in understanding the specific task objectives or directions, as explained by native-English-speaking instructors. Emerging generative AI (genAI) technology offers new opportunities for native-English instructors to provide clear task setup in their students' L1. This single-class activity utilizes genAI software to translate English-language task setup into student L1 and enable L2 students to perform a complex and unfamiliar English comprehension task. The post-activity appraisal compares one cohort of students who performed the task with the genAI translated instructions to a cohort who performed the same task with English-language instructions. Courses English as Second Language (ESL), English Conversation, English Comprehension, and any courses in which groups of L2 students are present. Objectives L2 students will be able to perform complex, unfamiliar ESL comprehension tasks with confidence and clarity of direction. Instructors will be able to transfer this strategy to other tasks and communicate objectives and directions to their L2 students more clearly in the students' L1. This strategy may be transferred to any course with L2 learners.

Information search under uncertainty across transdiagnostic psychopathology and healthy ageing

When making decisions in everyday life, we often rely on an internally generated sense of confidence to help us revise and direct future behaviours. For instance, confidence directly informs whether further information should be sought prior to commitment to a final decision. Many studies have shown that aging and both clinical and sub-clinical symptoms of psychopathology are associated with systematic alterations in confidence. However, it remains unknown whether these confidence distortions influence information-seeking behaviour. We investigated this question in a large general population sample (N = 908). Participants completed a battery of psychiatric symptom questionnaires and performed a perceptual decision-making task with confidence ratings in which they were offered the option to seek helpful information (at a cost) before committing to a final decision. Replicating previous findings, an ‘anxious-depression’ (AD) symptom dimension was associated with systematically low confidence, despite no detriment in objective task accuracy. Conversely, a ‘compulsive behaviour and intrusive thoughts’ (CIT) dimension was associated with impaired task accuracy but paradoxical over-confidence. However, neither symptom dimension was significantly associated with an increased or decreased tendency to seek information. Hence, participants scoring highly for AD or CIT did not use the option to information seek any more than average to either increase their confidence (AD) or improve the accuracy of their decisions (CIT). In contrast, older age was associated with impaired accuracy and decreased confidence initially, but increased information seeking behaviour mediated increases in both accuracy and confidence for final decisions. Hence, older adults used the information seeking option to overcome initial deficits in objective performance and to increase their confidence accordingly. The results show an appropriate use of information seeking to overcome perceptual deficits and low confidence in healthy aging which was not present in transdiagnostic psychopathology.

The influence of absolute and relative spatial cues on change detection performance

ABSTRACT Two experiments investigate how absolute and relative spatial cues influence perceptual comparisons between visual short-term memory (VSTM) and current vision. The core question concerned the role of task demands in this process. Two tasks were given across two experiments, differing in the extent they required object-level comparisons. Experiment 1, a feature comparison task, required reporting if any new colour was present in the second of two interleaved displays of four colours inside a surround; Experiment 2, an object comparison task, required report of any changes in colour-shape pairings in the second of two interleaved displays of four coloured shapes in a surround. Absolute and relative spatial organization was manipulated in both experiments by presenting compared displays on the same or contralateral sides, and by having the second display items in the same locations within the surround, in new locations, or repositioned into previous locations of other items. In sensitivity, both tasks showed an advantage for absolute spatial cues, but only the object task showed an advantage for relative spatial cues. In bias, both tasks were similarly influenced by both absolute and relative cues. Results suggest relative spatial cues are always available but only used when making object-level comparisons.

A novel prompting method for few-shot NER via LLMs

In various natural language processing tasks, significant strides have been made by Large Language Models (LLMs). Researchers leverage prompt method to conduct LLMs in accomplishing specific tasks under few-shot conditions. However, the prevalent use of LLMs’ prompt methods mainly focuses on guiding generative tasks, and employing existing prompts may result in poor performance in Named Entity Recognition (NER) tasks. To tackle this challenge, we propose a novel prompting method for few-shot NER. By enhancing existing prompt methods, we devise a standardized prompts tailored for the utilization of LLMs in NER tasks. Specifically, we structure the prompts into three components: task definition, few-shot demonstration, and output format. The task definition conducts LLMs in performing NER tasks, few-shot demonstration assists LLMs in understanding NER task objectives through specific output demonstration, and output format restricts LLMs’ output to prevent the generation of unnecessary results. The content of these components has been specifically tailored for NER tasks. Moreover, for the few-shot demonstration within the prompts, we propose a selection strategy that utilizes feedback from LLMs’ outputs to identify more suitable few-shot demonstration as prompts. Additionally, to enhance entity recognition performance, we enrich the prompts by summarizing error examples from the output process of LLMs and integrating them as additional prompts.

Power of a Few Vagrant Words: Effects of Direct and Indirect Suggestions for Self-Representation in Art-Based Online Interventions

ABSTRACT This study compares two groups of university students with differing instructions participating in an object drawing task as a part of an art therapy-based self-help online intervention. The intervention aimed to help participants enhance positive mood and subjective feeling of self-control and reduce negative mood. The object task contained suggestive elements in the instructions similar to self-hypnosis with an indirect and a direct way of formulation. Quantitative (positive affect and negative affect scale and Self-Assessment Manikin scale) and qualitative methods (text and picture rating) were used to investigate the difference between the outcome effects on the two groups. The results found a significant decrease in negative mood for indirect suggestion, while a significant increase of positive mood for the direct suggestion condition. Based on qualitative analyses, findings indicated that hidden implications in the art-making instructions modified the chosen imaginary and emotional changes related to art-making. Suggestions in the instructions can make a difference in one’s mood and this should also be considered while designing guidelines for self-hypnosis.

Prestimulus Alpha Phase Modulates Visual Temporal Integration.

When presented shortly after another, discrete pictures are naturally perceived as continuous. The neuronal mechanism underlying such continuous or discrete perception is not well understood. While continuous alpha oscillations are a candidate for orchestrating such neuronal mechanisms, recent evidence is mixed. In this study, we investigated the influence of prestimulus alpha oscillation on visual temporal perception. Specifically, we were interested in whether prestimulus alpha phase modulates neuronal and perceptual processes underlying discrete or continuous perception. Participants had to report the location of a missing object in a visual temporal integration task, while simultaneously MEG data were recorded. Using source reconstruction, we evaluated local phase effects by contrasting phase angle values between correctly and incorrectly integrated trials. Our results show a phase opposition cluster between -0.8 and -0.5 s (relative to stimulus presentation) and between 6 and 20 Hz. These momentary phase angle values were correlated with behavioral performance and event-related potential amplitude. There was no evidence that frequency defined a window of temporal integration.

Too much of a good thing? A multilevel examination of listening to music at work.

Music listening has proliferated in the workplace, yet its effects have been overlooked, and classic investigations offer conflicting results. To advance our understanding, we draw from self-regulation and resource allocation theories to suggest that listening to music has curvilinear effects on attentional focus and performance on work tasks and that willpower belief is a key boundary condition. We test these hypotheses across three studies: a pilot study of 108 employees from a software company who took part in a 2-week experience-sampling methodology study and self-rated their music listening and performance, a laboratory study (Study 1) of 252 undergraduate students in which task attentional focus and objective performance on proofreading tasks were captured across repeated trials while listening to music, and a 3-week experience-sampling methodology study (Study 2) of 247 employees that included a within-person manipulation of music listening (little to no music vs. 1 hr longer than usual vs. 3 hr longer than usual), daily self-ratings of task attentional focus and task performance, and weekly coworker ratings of task performance. We find mixed support for our hypotheses. Time spent listening to music exhibited an inverted, U-shaped relationship with self-rated (pilot study) and objective (Study 1) task performance. Individuals with higher willpower belief maintained higher levels of task attentional focus regardless of the amount of music they listened to (Studies 1 and 2), and the curvilinear relationship of reported music listening with self-rated task performance was more pronounced for individuals who believe that willpower is limited (pilot study and Study 2). (PsycInfo Database Record (c) 2024 APA, all rights reserved).