Effects of dual-task prioritization training on dual-task walking in older people: A single-blinded randomized controlled trial.

Driving is a cognitively demanding task engaging attentional effort and working memory resources, which increases cognitive load. The aim of this study was to evaluate the discriminative capabilities of an objective eye tracking method in comparison to a subjective self-report scale (the NASA–Task Load Index) in distinguishing cognitive load levels during driving. Participants (N = 685) performed highway and urban driving in a fixed-base driving simulator. The N-Back test was used as a secondary task to increase cognitive load. In line with previous studies, the NASA–Task Load Index was shown to be an accurate self-report tool in distinguishing conditions with higher and lower levels of cognitive load due to the additional N-Back task, with best average accuracy of 0.81 within the highway driving scenario. Eye gaze metrics worked best when differentiating between stages of highway and urban driving, with an average accuracy of 0.82. Eye gaze entropy measures were the best indicators for cognitive load dynamics, with average accuracy reaching 0.95 for gaze transition entropy in the urban vs. highway comparison. Eye gaze metrics showed significant correlations with the NASA–Task Load Index results in urban driving stages, but not in highway driving. The results demonstrate that eye gaze metrics can be used in combination with self-reports for developing algorithms of cognitive load evaluation and reliable driver state prediction in different road conditions.

Noise can reduce the intelligibility of spoken language and increase the effort necessary to understand speech. Listening effort, “the deliberate allocation of mental resources to overcome obstacles in goal pursuit when carrying out a [listening] task” (Pichora-Fuller et al., 2016), is commonly assessed by measuring response times to secondary tasks while listening to speech or by testing memory for the content of the speech. Increasing the level of background noise tends to slow responses and impair memory, and these effects are attributed to the resource-intensive process of reevaluating speech that was initially obscured or misheard. However, given that noise can impair performance on cognitive tasks that do not require processing auditory information, it is possible that noise-induced impairments typically ascribed to processing degraded speech may instead reflect increased cognitive load from the presence of noise itself. The current study assessed whether noise, in the absence of a speech task, can affect performance on tasks intended to measure listening effort. In Experiment 1 (positive control), target speech consisting of single words was presented aurally in background noise and we measured listening effort with three commonly-used paradigms. Experiment 2 was identical except that the target words were presented orthographically rather than aurally. Results showed that noise impaired performance on all three tasks when the target stimuli were presented aurally, consistent with a large body of work in the listening effort literature. Experiment 2 revealed that performance on some tasks was impaired by the presence of masking noise (particularly two-talker babble), indicating some domain-general interference. However, the magnitude of the noise-induced interference effects were markedly smaller in Experiment 2 than Experiment 1, suggesting that measures of listening effort capture variability attributable to the challenges associated with listening to speech in noise, and do not simply measure distraction or noise-induced cognitive interference.

Semantic web applications are witnessing a dramatic increase in complexity, data volume, and usage. Likewise, large language models (LLMs) are experiencing significant developments in performance and capabilities. Consequently, LLMs have been utilized in various fields and applications to support primary and secondary tasks. The proven ability of LLMs to process natural language (NL) has opened the door to integration into many tasks, including NL-related tasks such as Knowledge Graph Question Answering (KGQA), which involves translating NL questions into SPARQL queries to retrieve answers from Knowledge Graphs (KG). However, answering questions over domain-specific KGs is challenging due to complex schema structures, specialized vocabularies, and query complexity. Therefore, the development of domain-agnostic and user-friendly KG querying mechanisms has become necessary. Motivated by this need, this paper presents an LLM based approach for translating NL questions into SPARQL queries over domain-specific KG by investigating how various configurations of augmented KG data influence LLM responses. Our approach adopts a streamlined method for zero-shot SPARQL query generation by augmenting LLMs with different arrangements of previously extracted domain-specific KG information. Specifically, our experiments evaluate LLM generated SPARQL responses against twenty manually crafted questions of varying complexity using prompts augmented with different KG information: first, a reduced linearized KG, and second, discrete vocabulary information extracted from a reduced ontology KG. The results indicate that supplementing LLM prompts with discrete vocabulary information extracted from a reduced KG ontology yields competitive performance levels for the target LLM models compared to supplementing them with a reduced ontology. Ultimately, our approach reduces the augmented KG information size while preserving response accuracy, enables off-domain users to interact with domain-specific KG information and retrieve responses through a domain-agnostic interface, and facilitates benchmarking over a wide spectrum of LLM models.

In recent years, there has been an increasing interest in human-machine teaming for search and rescue operations, deep space missions, and agricultural tasks, among others. To be effective teammates, artificial agents should be able to detect and be responsive to systemic human cognitive states such as workload, sense of urgency, mind wandering, interference, and distraction. Here, we introduce an experimental paradigm and a comprehensive multimodal dataset that provides the necessary data for analyzing the relationships among multiple systematic human cognitive states, enables the development of robust prediction models of these states, and details the framework for developing new experiments. The introduced experimental setup allows for the synchronized real-time recording of multiple data streams from various sensing devices including fNIRS, EEG, pupillometry, respiration, electrodermal activity, and plethysmography, and is applicable in many other interactive task settings where human performance needs to be monitored. The dataset was acquired from 80 subjects performing a driving task and several secondary tasks including car braking events, dialogue communications, and tactile stimulations.

The power-space associations are widely discussed in the field of concept representations, with two coding systems proposed to explain this phenomenon: the verbal-spatial and visuospatial codes. However, it remains unclear whether these two coding systems are always activated in all situations, or whether they are context-dependent. To address these problems, the current study adopted two different explicit power judgment tasks, one visual and one verbal. In the visual task, all verbal cues were ruled out, and in the verbal task, all visual cues were ruled out. Each task was coupled with a secondary task-either visuospatial or verbal-spatial-to investigate the underlying activation mechanism. The results showed that both coding systems were sufficient to generate such associations separately. Most importantly, the activation of two different codes was context-dependent and interfered by the related secondary tasks.

ABSTRACT Everyday life demands handling multiple tasks that need attention simultaneously, which may be challenging for children with ADHD. In this study we tested dual-tasks in a cognitive–motor and motor–motor condition in children with and without ADHD. Sixty-six children (42 children with ADHD; 24 typically developing) participated and were tested on a primary Wii Fit balance task, and two secondary tasks: a cognitive task (counting specific sounds) and a motor task (crossing fingers (CF)), performed in single-task and dual-task conditions. In addition, attentional and motor abilities were measured independently. Children with ADHD presented poorer motor performance (Wii-Fit game, finger crossings) in the single task with large effect sizes, but performed equally on cognitive performance compared with their peers. Dual-task interference was not present in the primary Wii-Fit scores, but clearly and similarly present in the cognitive and CF tasks in both groups. The impact of divided attention on Wii Fit dual-task performance was 6–11%, and on dual-task CF performance 28.8% when combined with motor abilities. Children with ADHD are disproportionately impaired in dual-task situations where they must perform two motor tasks, but not when they perform a motor and a cognitive task.

ACL injuries often occur when athletes perform cognitive tasks while performing a landing/cutting movement. This study investigated the effects of secondary cognitive tasks on hip and knee biomechanics during single limb landing. Sixteen recreational athletes (10 females and 6 males, age: 21.6 ± 2.5 years, mass: 65.2 ± 8.9 kg, height 1.66 ± 0.07 m) performed landings on their dominant limb as a single task and while simultaneously performing secondary cognitive tasks (mental arithmetic) provided through audio and visual means. Hip and knee joint angles and moments were calculated in all three planes of motion and analysed using statistical parametric mapping repeated-measures ANOVA. Hip adduction angle was significantly greater in audio and visual secondary task conditions compared to the single task condition during 88% to 100% of the landing period. Hip internal rotation was significantly greater in the visual secondary task condition compared to the single task condition during 68% to 92% of the landing period. There were no significant differences between task conditions for hip moments, knee moments or knee angles in all three planes of motion. These findings suggest secondary cognitive tasks, whether visual or audio, affect hip kinematics which may reflect reduced dynamic stability at the hip, contributing important further knowledge on the effect of secondary cognitive tasks during landing biomechanics.

Impact of age on gait parameters under motor and cognitive dual-task conditions.

Dual-task training comprising cognitive and physical components may enhance cognitive function, and increased prefrontal cortex activation may underpin these improvements. The aim of this pilot study was to examine the effects of cycling and visual foraging on executive function (EF). Twenty-seven participants (mean age 25.44 ± 4.31 years) completed four lab-based sessions, one in which their aerobic capacity (O2max) and baseline EF scores assessed were determined, and three randomized experimental conditions: ergometer cycling (EC), visual foraging (VF) and both combined (EC + VF). Participants’ EF performance was assessed at baseline, and pre-and post- intervention using the 2-Back task (working memory), the Flanker Task (inhibitory control), and the Wisconsin Card Sorting Task (WCST; task switching). Functional near-infrared spectroscopy (fNIRS) and eye-tracking data were collected throughout each condition. Affective state was assessed via the Affect Grid. Repeated measures ANCOVAs, incorporating baseline EF task scores as covariates, revealed condition x time x covariate interactions for the Flanker task only; task performance of participants with poorer baseline scores improved more profoundly in the EC condition. Subjective arousal and prefrontal cortex (PFC) activation were higher in both cycling conditions relative to VF; hence, ergometer cycling, rather than visual foraging, might be the more impactful intervention in these regards. However, these elevations were not associated with EF enhancements; near-ceiling effects in EF task performance may explain this. The EC condition elicited greater energetic investment than the EC + VF condition; possibly because the secondary VF task distracted from the cycling exercise. PFC activation was only correlated with gaze fixations during the EC + VF condition, potentially reflecting concurrent increases in supply of, and demand for, oxygen during the combined condition.

We investigated how separately and sequentially acquired visual and motor experiences shape action prediction mechanisms. There is evidence that physical practice leads to an implicit, motor-based prediction process, compared to visual practice, which is more strategic. However, the relative dominance or flexibility of these mechanisms is not well understood. Here we used a motor secondary task paradigm to evaluate effector-specific interference in action predictions, which has previously given evidence for a motor simulation-based prediction process after physical practice. Participants across two groups (N = 40) received both isolated and sequentially combined motor and visual practice across two days; either throwing darts to three different sections of a dartboard "motor" or watching and predicting outcomes of occluded throws "visual". The Motor-to-Visual group threw on Day 1 and watched on Day 2 and the Visual-to-Motor group did the reverse. Prediction tasks were performed pre and post practice each day, with some trials involving motor secondary tasks, performed with the observed (right) or non-observed hand. Consistent with previous work, the Motor-to-Visual group after physical practice improved prediction accuracy on Day 1, except when performing the secondary task with their right hand. After visual practice on Day 2, prediction accuracy was maintained, but without secondary task interference. The Visual-to-Motor group also improved predictions, but with no secondary task interference on either day, resulting in greater accuracy overall. These data support the suggestion that separately acquired motor and visual experiences either allow flexibility in prediction strategies or lead to a dominance of the visually-acquired strategy.

Artificial newscasters are increasingly replacing human anchors in broadcast media, yet their effects on viewers’ attention and emotional processing remain poorly understood. Using a controlled experiment with secondary task reaction time (STRT) and affective evaluations, this study revealed a dynamic attentional shift: Relative to the human newscaster, the artificial newscaster sustained greater attention to news watching after an initial diverting away from it. In addition, they blunted emotional reactions to unpleasant news, while ratings for neutral news and arousal remained unaffected. This dissociation, where artificial agents sustained attention but dampened emotional experience, advances the Computers Are Social Actors (CASA) paradigm by demonstrating boundary conditions for the Media Equation hypothesis. Practical and ethical implications are discussed, including tradeoffs between engagement and emotional resonance.

Novice drone pilots frequently experience performance difficulties under high cognitive load, particularly when secondary tasks divide attention. This study examined how dual-tasking influences flight performance, workload, and neural activity in 26 novice UAV operators. Participants completed a single-task flight and a dual-task flight combining overhead alignment with a 1-back auditory task, while subjective workload, behavioral measures, and fNIRS data were collected. Dual-tasking increased perceived workload and prefrontal activation, especially in the inferior prefrontal cortex. Although accuracy was maintained, participants adopted compensatory strategies—flying more slowly and reducing control input—to sustain stability. Sliding-window analysis revealed brief increases in interhemispheric connectivity during early dual-task phases, which correlated more strongly with workload ratings than with overall HbO activation. These findings identify bilateral prefrontal coordination as a neural marker of adaptive control under cognitive load, offering insights for pilot training and human–machine interface design.

Unveiling contralesional omissions six years after stroke. Effects of top-down and bottom-up manipulations.

Advanced driver assistance systems (ADAS), such as adaptive cruise control (ACC), have been recently installed in passenger cars. Although the safety performance of these systems is limited in high-risk scenarios, some drivers overtrust the system and perform secondary tasks. Previous research indicated that drivers using ADAS tend to become distracted compared with manual driving. In contrast, the use of ACC has been reported to reduce the collision rate on highways by about half. This study aimed to clarify the mechanism of the effect of ACC on driver behavior and consequently mitigate accidents. Our previous experiments showed that driver reaction time to perform avoidance behaviors in high-risk scenes is shortened when using ACC, even if the driver is distracted. This paper first aims to elucidate the factors influencing driver risk-avoidance strategies in a potentially critical frontal collision scenario. The hypothesis is that the driver’s perception of tactile vehicle motion, accompanied by the deceleration of ACC active intervention, prompts risk awareness and avoidance. The hypothesis was verified through analysis of driver gaze movement and brake operation behavior in critical scenarios using driving simulator experiments. Based on the obtained results, the advanced driver assistance system longitudinal control laws adapted to the driver’s eyes-off state are proposed based on the high-risk scenarios. Finally, the driver acceptance and ability to reduce the risk of the proposed system were quantitatively evaluated using a driving simulator.

Multitasking has become a necessity in our daily routines. Older people in developed countries are subject to ever-increasing cognitive demands, and the way they multitask has been raising significant interest. Recent research has focused on the clinical relevance of the motor-cognitive dual-task, partially neglecting the potential of concurrently using two cognitive tasks. Here, we devised a computer-based, cognitive-cognitive dual task to study the relationship between dual-task cost, age, and cognitive efficiency (MoCA) in a group of sixty-one healthy participants (aged 50–77 years). Participants were tested with a primary visual Memory task (free recall or forced choice) and a secondary phonemic Fluency task, either concurrently (dual-tasking) or non-concurrently (single task). As expected, primary and secondary task performance significantly decreased with concurrent task demands and increasing age. Age and cognitive load however did not interact: The dual-tasking cost in visual Memory and in phonemic Fluency was stable across the age range we investigated. Participants with higher mnestic costs had lower performance also in other measures of divided attention (e.g. TMT) while no correlation was found with the MoCA score. This might be compatible with the presence of a core ability allowing to split attention for the parallel processing of information with different nature. In conclusion, cognitive-cognitive dual-tasks provide a sensitive measure of non-pathological age-related changes in cognitive efficiency and could be used as baseline when developing more sensitive tests for the early detection of abnormal patterns possibly indexing cognitive impairments.

On the effect of using an augmented reality laser projection operator guidance system on cognitive workload and assembly task performance.

Studying human modality preferences in a human-drone framework for secondary task selection

Using AR-based secondary tasks to enhance user cognitive focus in monitoring tasks within intelligent workplaces

Universal domain adaptation with navigator-guided strong alignment and dynamic threshold for rotating machinery fault diagnosis.