Secondary Task Research Articles

Driver behavior while using Level 2 vehicle automation: a hybrid naturalistic study

Vehicle automation is becoming more prevalent. Understanding how drivers use this technology and its safety implications is crucial. In a 6–8 week naturalistic study, we leveraged a hybrid naturalistic driving research design to evaluate driver behavior with Level 2 vehicle automation, incorporating unique naturalistic and experimental control conditions. Our investigation covered four main areas: automation usage, system warnings, driving demand, and driver arousal, as well as secondary task engagement. While on the interstate, drivers were advised to engage Level 2 automation whenever they deemed it safe, and they complied by using it over 70% of the time. Interestingly, the frequency of system warnings increased with prolonged use, suggesting an evolving relationship between drivers and the automation features. Our data also revealed that drivers were discerning in their use of automation, opting for manual control under high driving demand conditions. Contrary to common safety concerns, our data indicated no significant rise in driver fatigue or fidgeting when using automation, compared to a control condition. Additionally, observed patterns of engagement in secondary tasks like radio listening and text messaging challenge existing assumptions about automation leading to dangerous driver distraction. Overall, our findings provide new insights into the conditions under which drivers opt to use automation and reveal a nuanced behavioral profile that emerges when automation is in use.

Effects of caffeine and blue-enriched light on spare visual attention during simulated space teleoperation

Safe and successful operation of the International Space Station robotic arm is a complex task requiring difficult bimanual hand coordination and spatial reasoning skills, adherence to operating procedures and rules, and systems knowledge. These task attributes are all potentially affected by chronic sleep loss and circadian misalignment. In a randomized, placebo-controlled, cross-over trial examining the impact of regularly timed low-dose caffeine (0.3 mg kg−1 h−1) and moderate illuminance blue-enriched white light (~90 lux, ~88 melEDI lux, 6300 K), 16 participants performed 3 types of realistic robotic arm tasks using a high-fidelity desktop simulator overnight. Our goal was to determine how these countermeasures, separately and combined, impacted telerobotic task performance and the ability to allocate attention to an unrelated secondary visual task. We found that all participants maintained a similar level of robotic task performance throughout the primary task but the application of caffeine separately and with blue-enriched light significantly decreased response time to a secondary visual task by −9% to −13%, whereas blue-enriched light alone changed average response times between −4% and +2%. We conclude that, for sleep-restricted individuals, caffeine improved their ability to divide their visual attention, while the effect of blue-enriched light alone was limited. Light and caffeine together was most effective. Use of these countermeasures should improve the margin of safety if astronauts perform familiar tasks under degraded conditions or novel tasks where task workload is increased.

Distraction-level recognition based on stacking ensemble learning for IVIS secondary tasks

Driver distraction-level recognition while performing secondary tasks in full-touch in-vehicle information systems (FTIVISs) is essential for the harmonious co-driving of human and intelligent vehicle systems. However, there has been little research on this topic. To respond to this issue, this paper proposes a distraction-level recognition framework with a combination of semi-supervised learning, unsupervised learning, and supervised learning. First, unsupervised learning and semi-supervised is used to divide the collected unlabeled samples of driving distraction behavior into three categories of distraction levels: high, medium, and low. Second, the factors influencing the distraction level are explored through a mixed model analysis. Finally, a stacking-based ensemble learning model is proposed to recognize the driver distraction level by supervised learning, with the influencing factors of the distraction level used as model input parameters. To improve the recognition performance of the stacking model, four heterogeneous classifiers selected as the base classifiers, and principal component analysis (PCA) is introduced in the base classifier layer, which improves the ability of the meta-classifier to process raw features based on overfitting resistance. We conducted a real road experiment under different road and FTIVIS task conditions, and the proposed model performed better than traditional machine learning models. In addition, the model exhibited the greatest advantage when the deep neural network (DNN) algorithm was used as the meta-classifier of the model, with a recognition accuracy of 92.5%. The study findings are significant for developing a human–machine co-driving control strategy and improving vehicle driving safety.

Event Related Brain Responses Reveal the Impact of Spatial Augmented Reality Predictive Cues on Mental Effort.

This article presents the results from a Spatial Augmented Reality (SAR) study which evaluated the cognitive cost of several predictive cues. Participants performed a validated procedural button pressing task, where the predictive cue annotations guided them to the upcoming task. While existing research has evaluated predictive cues based on their performance and self-rated mental effort, actual cognitive cost has yet to be investigated. To measure the user's brain activity, this study utilized electroencephalogram (EEG) recordings. Cognitive load was evaluated by measuring brain responses for a secondary auditory oddball task, with reduced brain responses to oddball tones expected when cognitive load in the primary task is highest. A simple monitor n-back task and procedural task comparing monitor versus SAR were conducted, followed by a version of the procedural task comparing the SAR predictive cues. Results from the brain responses were able to distinguish between performance enhancing cues with a high and low cognitive load. Electrical brain responses also revealed that having an arc or arrow guide towards the upcoming task required the least amount of mental effort.

Habits, attitudes, and expectations of regular users of partial driving automation systems

Introduction: Little is known about regular users’ perceptions of partial (Level 2) automation or how those perceptions affect behind-the-wheel behavior. Method: A mixed mode (phone and online) survey explored the habits, expectations, and attitudes among regular users of General Motors Super Cruise (n = 200), Nissan/Infiniti ProPILOT Assist (n = 202), and Tesla Autopilot (n = 202). Results: All three groups reported being more likely to engage in non-driving-related activities while using their systems than while driving unassisted. Super Cruise and Autopilot users especially were more likely to report engaging in activities that involved taking their hands off the wheel or their eyes off the road. Many Super Cruise and Autopilot users also said they could perform secondary (non-driving-related) tasks better and more often while using their systems, while fewer ProPILOT Assist users shared this opinion. Super Cruise users were most likely and ProPILOT Assist users least likely to think that secondary activities were safer to perform while using their systems. While some drivers said they found user safeguards (e.g., attention reminders, lockouts) annoying and tried to circumvent them, most people said they found them helpful and felt safer with them. Large percentages of users (53% Super Cruise, 42% Autopilot and 12% ProPILOT Assist) indicated they were comfortable treating their systems as self-driving. Conclusions: Some regular users have a poor understanding of their technology’s limits. System design appears to contribute to user perceptions and behavior. However, owner populations also differ, which means habits, attitudes, and expectations may not generalize. Most people value user safeguards, but some implementations may not be effective for everyone. Practical Applications: Multifaceted, proactive user-centric safeguards are needed to shape proper behavior and understanding about drivers’ roles and responsibilities while using partial driving automation.

Comparing attentional disengagement between Prolific and MTurk samples

Attention often disengages from primary tasks in favor of secondary tasks (i.e., multitasking) and task-unrelated thoughts (i.e., mind wandering). We assessed whether attentional disengagement, in the context of a cognitive task, can substantially differ between samples from commonly used online participant recruitment platforms, Prolific and Mechanical Turk (MTurk). Initially, eighty participants were recruited through Prolific to perform an attention task in which the risk of losing points for errors was varied (high risk = 80% chance of loss, low risk = 20% chance of loss). Attentional disengagement was measured via task performance along with self-reported mind wandering and multitasking. On Prolific, we observed surprisingly low levels of disengagement. We then conducted the same experiment on MTurk. Strikingly, MTurk participants exhibited more disengagement than Prolific participants. There was also an interaction between risk and platform, with the high-risk group exhibiting less disengagement, in terms of better task performance, than the low-risk group, but only on MTurk. Platform differences in individual traits related to disengagement and relations among study variables were also observed. Platform differences persisted, but were smaller, after increasing MTurk reputation criteria and remuneration in a second experiment. Therefore, recruitment platform and recruitment criteria could impact results related to attentional disengagement.

Human and machine-induced social stress in complex work environments: Effects on performance and subjective state

Social stress at work can lead to severe consequences. As a result of technological developments, social stress will increasingly be induced by machines. It is therefore crucial to understand how machine-induced social stress affects operators. The present study aimed to compare human and machine-induced social stress with regard to its effect on primary and secondary task performance, and on subjective state (e.g., self-esteem, mood and justice). 90 participants worked on a high-fidelity simulation of a complex work environment, on which they had received extensive training (2h15). Social stress was induced by a human or a machine using a combination of negative performance feedback and ostracism. Results indicate that social stress did not affect performance, affect or state self-esteem. Machine-induced and human-induced social stress overall had similar effects, except for the latter impairing perceived justice. We discuss implications of these results for automation at the workplace and outline future research directions.

Measuring the Contributions of Perceptual and Attentional Processes in the Complete Composite Face Paradigm.

Theories of holistic face processing vary widely with respect to conceptualizations, paradigms, and stimuli. These divergences have left several theoretical questions unresolved. Namely, the role of attention in face perception is understudied. To rectify this gap in the literature, we combined the complete composite face task (allowing for predictions of multiple theoretical conceptualizations and connecting with a large body of research) with a secondary auditory discrimination task at encoding (to avoid a visual perceptual bottleneck). Participants studied upright, intact faces within a continuous recognition paradigm, which intermixes study and test trials at multiple retention intervals. Within subjects, participants studied faces under full or divided attention. Test faces varied with respect to alignment, congruence, and retention intervals. Overall, we observed the predicted beneficial outcomes of holistic processing (e.g., higher discriminability for Congruent, Aligned faces relative to Congruent, Misaligned faces) that persisted across retention intervals and attention. However, we did not observe the predicted detrimental outcomes of holistic processing (e.g., higher discriminability for Incongruent, Misaligned faces relative to Incongruent, Aligned faces). Because the continuous recognition paradigm exerts particularly strong demands on attention, we interpret these findings through the lens of resource dependency and domain specificity.

How manoeuvre information via auditory (spatial and beep) and visual UI can enhance trust and acceptance in automated driving

In conditionally automated driving (SAE level 3), drivers may take their eyes off the road but will still need to be ready to take control and will, therefore, benefit from information on automation. This study aims to investigate the effectiveness of automation manoeuvre information provided through spatial sound, traditional notification sound (beep), and a visual interface. Spatial sounds were designed differentiating four distinct driving manoeuvres: overtaking a leading car, slowing down, turning right, and passing a roundabout. The notification sound consisted of one beep being identical for all manoeuvres. The visual interface showed the automation mode with an image and manoeuvre information with text and images. The impact of these interfaces on trust, workload, acceptance, situation awareness, and sense of control was evaluated with questionnaires and visual attention was evaluated with eye tracking while participants engaged in a visual-motor secondary task in a driving simulator. The results indicate that, with all interfaces tested, manoeuvre information enhances trust, acceptance, situation awareness, and sense of control, without significantly affecting the overall workload. These benefits were more profound, adding auditory information and differed marginally between the traditional notification and the spatial sound, as the effectiveness of the different auditory interface types varied depending on the specific manoeuvre. Findings highlight the importance of designing user interfaces for automation manoeuvre information using auditory cues to improve the user experience in automated driving.

An analysis of physiological responses as indicators of driver takeover readiness in conditionally automated driving

By the year 2045, it is projected that Autonomous Vehicles (AVs) will make up half of the new vehicle market. Successful adoption of AVs can reduce drivers’ stress and fatigue, curb traffic congestion, and improve safety, mobility, and economic efficiency. Due to the limited intelligence in relevant technologies, human-in-the-loop modalities are still necessary to ensure the safety of AVs at current or near future stages, because the vehicles may not be able to handle all emergencies. Therefore, it is important to know the takeover readiness of the drivers to ensure the takeover quality and avoid any potential accidents. To achieve this, a comprehensive understanding of the drivers’ physiological states is crucial. However, there is a lack of systematic analysis of the correlation between different human physiological responses and takeover behaviors which could serve as important references for future studies to determine the types of data to use. This paper provides a comprehensive analysis of the effects of takeover behaviors on the common physiological indicators. A program for conditional automation was developed based on a game engine and applied to a driving simulator. The experiment incorporated three types of secondary tasks, three takeover events, and two traffic densities. Brain signals, Skin Conductance Level (SCL), and Heart Rate (HR) of the participants were collected while they were performing the driving simulations. The Frontal Asymmetry Index (FAI) (as an indicator of engagement) and Mental Workload (MWL) were calculated from the brain signals to indicate the mental states of the participants. The results revealed that the FAI of the drivers would slightly decrease after the takeover alerts were issued when they were doing secondary tasks prior to the takeover activities, and the higher difficulty of the secondary tasks could lead to lower overall FAI during the takeover periods. In contrast, The MWL and SCL increased during the takeover periods. The HR also increased rapidly at the beginning of the takeover period but dropped back to a normal level quickly. It was found that a fake takeover alert would lead to lower overall HR, slower increase, and lower peak of SCL during the takeover periods. Moreover, the higher traffic density scenarios were associated with higher MWL, and a more difficult secondary task would lead to higher MWL and HR during the takeover activities. A preliminary discussion of the correlation between the physiological data, takeover scenario, and vehicle data (that relevant to takeover readiness) was then conducted, revealing that although takeover event, SCL, and HR had slightly higher correlations with the maximum acceleration and reaction time, none of them dominated the takeover readiness. In addition, the analysis of the data across different participants was conducted, which emphasized the importance of considering standardization or normalization of the data when they were further used as input features for estimating takeover readiness. Overall, the results presented in this paper offer profound insights into the patterns of physiological data changes during takeover periods. These findings can be used as benchmarks for utilizing these variables as indicators of takeover preparedness and performance in future research endeavors.

SPIRITUAL LEADERSHIP AND TEACHERS' PSYCHOLOGICAL WELL-BEING: THE MEDIATING ROLE OF GRIT: A CONCEPTUAL MODEL

With the comprehensive promotion of social transformation and educational reform, Chinese primary and secondary school teachers shoulder multiple tasks, and their work pressure is increasing, and their mental health is not optimistic. If teachers are in a state of low well-being for a long time, it will certainly bring great hidden dangers to the development of China's education. Therefore, we must attach great importance to the problem of primary and secondary school teachers' psychological well-being. This study aims to propose a conceptual framework involving spiritual leadership, psychological well-being, and grit of primary and secondary school teachers on the basis of previous studies by scholars. By exploring their relationship, we can provide insights for improving primary and secondary school teachers' psychological well-being.

Spatiotemporal gait characteristics during single- and dual-task walking are associated with the burden of cerebral small vessel disease.

Gait impairment is a common symptom among individuals with cerebral small vessel disease (CSVD). However, performance differences between single-task walking (STW) and dual-task walking (DTW) among individuals with CSVD remain unclear. Therefore, we aimed to examine differences in gait characteristics during STW and DTW as well as the association between gait performance and neuroimaging markers. We enrolled 126 older individuals with CSVD. The speed, cadence, stride length, stride time, and their dual-task cost (DTC) or variability were measured under the STW, motor-cognitive DTW (cognitive DTW), and motor-motor DTW (motor DTW) conditions. We examined neuroimaging features such as white matter hyperintensities (WMHs), lacunes, microbleeds, and total burden. Further, we analysed the association of neuroimaging markers with gait performance, including gait variability and DTC. Almost all spatiotemporal characteristics, as well as their DTCs or variabilities, showed significant among-group differences according to disease severity in the cognitive DTW condition; however, relatively lesser differences were observed in the STW and motor DTW conditions. The total CSVD burden score was moderately correlated with all the spatial parameters, as well as their DTCs or variabilities, in the cognitive DTW condition. Moreover, WMHs showed a correlation with speed, stride time, and cadence, as well as their DTCs, in the cognitive DTW condition. Furthermore, lacunes showed a moderate correlation with speed, stride length, and the DTC of speed, whilst microbleeds were only related to the DTC of stride length in the cognitive DTW condition. Neuroimaging biomarkers were not correlated with spatiotemporal parameters in STW and motor DTW conditions after Bonferroni correction. Moreover, the correlation coefficient between the total CSVD burden score and gait parameters was greater than those of other biomarkers. Parameters in the cognitive DTW condition are more appropriate than those in the motor DTW condition for the evaluation of gait abnormalities in patients with CSVD. Moreover, the total CSVD burden score might have better predictive utility than any single neuroimaging marker. Patients with CSVD, especially those with moderate-to-severe disease, should concentrate more on their gait patterns and reduce the load of secondary cognitive tasks whilst walking in daily life.

Losing Awareness of Our Surroundings?

Abstract: Narrative messages have demonstrated consistent effects on attitude change, with transportation as one of the most prominent explanations for their effects. However, the transportation process has yet to be fully understood. The present study investigated how attentional changes during audio narrative exposure, operationalized as secondary task reaction times, related to postexposure self-reports of transportation. Results demonstrated, unexpectedly, that faster reaction times were associated with increased transportation. Additionally, the study investigated multitasking propensity as a moderator, finding that low multitaskers exhibited slower reaction times during narrative compared to nonnarrative exposure whereas high multitaskers showed no differences in reaction time for narratives compared to nonnarratives. There were no differences in self-reported transportation for high and low multitaskers. The findings revealed limitations of the transportation self-report measure to capture attention, while highlighting the nuanced relationship between attention and transportation.

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and people with early Parkinson's disease: Study protocol for a cross-sectional Mobile Brain/Body Imaging (MoBI) study.

Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson's Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems. ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).

Evaluation of postural stability under single and dual task conditions in individuals with and without intellectual disability

Background: The aim was to investigate how varying levels of intellectual disability (ID) impact postural stability parameters and response reaction time (RRT). Method: Fifty-nine individuals with low and moderate levels of ID and 55 sex- and age-matched peers without ID performed a bipedal standing postural control task while having their (I) eyes open [OE], (II) eyes closed [CE], and (III) while performing a secondary cognitive task- pressing a trigger button while maintaining still stance (dual task, DT). Seven postural control parameters (total, mediolateral and anteroposterior displacement, sway area, sway mean velocity, mediolateral dispersion, and anteroposterior dispersion) during each experimental condition as well as the RRT during the DT were recorded. Results: The results revealed that (I) CE and DT partially affected postural control parameters when compared to OE condition (in 13 and in 3 out of 21 pairwise comparisons, respectively), (II) individuals with ID had poorer postural control than peers without ID during the OE and DT conditions (p ≤ 0.05), but not during the CE condition (except for the larger total displacement observed in participants with moderate disability compared to participants without ID, p ≤ 0.05), (III) RRT was longer in individuals with ID compared to the group without ID (p ≤ 0.001), and (IV) no postural control parameter (p ≥ 0.05) nor RRT (p = 0.138) revealed differences between the participants with low and moderate levels of ID. Conclusions: These findings suggest that individuals with ID present reduced performance in the postural control parameters especially when they need to respond to DT compared to individuals without ID.

Virtual Reality Sickness Reduces Attention During Immersive Experiences.

In this paper, we show that Virtual Reality (VR) sickness is associated with a reduction in attention, which was detected with the P3b Event-Related Potential (ERP) component from electroencephalography (EEG) measurements collected in a dual-task paradigm. We hypothesized that sickness symptoms such as nausea, eyestrain, and fatigue would reduce the users' capacity to pay attention to tasks completed in a virtual environment, and that this reduction in attention would be dynamically reflected in a decrease of the P3b amplitude while VR sickness was experienced. In a user study, participants were taken on a tour through a museum in VR along paths with varying amounts of rotation, shown previously to cause different levels of VR sickness. While paying attention to the virtual museum (the primary task), participants were asked to silently count tones of a different frequency (the secondary task). Control measurements for comparison against the VR sickness conditions were taken when the users were not wearing the Head-Mounted Display (HMD) and while they were immersed in VR but not moving through the environment. This exploratory study shows, across multiple analyses, that the effect mean amplitude of the P3b collected during the task is associated with both sickness severity measured after the task with a questionnaire (SSQ) and with the number of counting errors on the secondary task. Thus, VR sickness may impair attention and task performance, and these changes in attention can be tracked with ERP measures as they happen, without asking participants to assess their sickness symptoms in the moment.

Drivers’ Reaction Time and Mental Workload: A Driving Simulation Study

Abstract Drivers play a significant role in causing serious accidents, which underscores the need for further investigating the human element in order to improve road safety. Given the predominance of the information processing approach in driver’s behavior research field, an important psychological construct, Mental Workload (MWL), has been introduced to study the behavior of drivers. The objective of this paper is to investigate the impact of increased MWL on driver behavior and specifically the changes in driver’s Reaction Time (RT) under increased MWL. The experiment conducted in the driving simulator of the Hellenic Institute of Transport which is part of the Centre for Research and Technology Hellas, with the participation of 56 subjects from all age groups. For the simulation of the increased MWL conditions during driving, a secondary task was employed. To this end, the MIT AgeLab Delayed Digit Recall Task in the 1-back version was adapted for the needs of the present research. The driving scenario included 4 unexpected events, which further increase driver’s MWL. Driving performance was observed and relative parameters were measured as RT on the unexpected events, accidents occurred, and maneuvers performed. Appropriate statistical analysis was performed to examine the difference in the drivers’ RT in the unexpected events. Results demonstrated that higher MWL increased drivers’ RT in the majority of the participants. Furthermore, results also indicated a number of participants that probably employed adaptive control behaviors to counterbalance the increased MWL. Overall, variance on MWL proved to play an important role on driver performance, and thus further research on its consequences on driving performance, and the factors that influence its variance during driving, is imperative.

Assessing Flight Crew Fatigue under Extra Augmented Crew Schedule Using a Multimodality Approach

During the COVID-19 pandemic, the question of how to reduce the risk of viral infection for international airline pilots without increasing the risk of fatigue was a novel and urgent theoretical and practical problem, which had never been encountered in the world civil aviation industry. A new scheduling method implemented by the Civil Aviation Administration of China (CAAC) is the extra augmented crew (EAC) schedule, which avoids crew layover in another country on international flights by extending the maximum duty time and adding two additional crew members to such long-haul flights. In this study, a multi-day flight crew fatigue assessment was conducted to evaluate the impact of EAC flight. We recruited 71 pilots as participants, and their fatigue during EAC flights was measured using a multimodality approach integrating a subjective fatigue report, a psychomotor vigilance task, sleep monitoring, and biomathematical model predictions. The results showed that the subjective fatigue level increased during duty time compared to off-duty time, but still with acceptable levels of under 7, as measured by the Karolinska Sleepiness Scale; objective secondary task performance, as measured by the classic psychomotor vigilance task, showed no differences; pilots were able to get around 6 h of sleep, although they slept less during duty time compared to off-duty time. Model fitting using the FAID biomathematical model of fatigue confirmed that the EAC scheduling was compliant with the FAID tolerance level 91.3% of the time. The results suggest that the EAC flight created some moderate level of increased fatigue but no severe fatigue to cross-continent long-haul flight crews. This research can inform current and future scheduling and fatigue risk control during the pandemic or for future time-sensitive periods.

It's SNARC o' clock: manipulating the salience of the context in a conceptual replication of Bächtold et al.'s (1998) clockfacestudy.

The Spatial-Numerical Association of Response Codes (SNARC) effect consists in faster left-/right-key responses to small/large numbers. (Bächtold et al., Neuropsychologia 36:731-735, 1998) reported the reversal of this effect after eliciting the context of a clockface-where small numbers are represented on the right and large numbers on the left. The present study investigates how the salience of a particular spatial-numerical context, which reflects the level of activation of the context in working memory, can alter Spatial Numerical Associations (SNAs). Four experiments presented the clockface as context and gradually increased its salience using different tasks. In the first two experiments (low salience), the context was presented at the beginning of the experiment and its retrieval was not required to perform the tasks (i.e., random number generation in Experiment 1, magnitude classification and parity judgement in Experiment 2). Results revealed regular left-to-right SNAs, unaffected by the context. In Experiment 3 (medium salience), participants performed magnitude classification and parity judgement (primary task), and a Go/No-go (secondary task) which required the retrieval of the context. Neither the SNARC effect nor a reversed-SNARC emerged, suggesting that performance was affected by the context. Finally, in Experiment 4 (high salience), the primary task required participants to classify numbers based on their position on the clockface. Results revealed a reversed SNARC, as in (Bächtold et al., Neuropsychologia 36:731-735, 1998). In conclusion, SNARC is disrupted when the context is retrieved in a secondary task, but its reversal is observed only when the context is relevant for the primary task.

Toward Workload-Based Adaptive Automation: The Utility of fNIRS for Measuring Load in Multiple Resources in the Brain

We investigate the utility of functional near-infrared spectroscopy (fNIRS) for workload-based adaptive automation through the lens of multiple resource theory. We focus on the criteria of unobtrusiveness, responsiveness, load sensitivity (low vs high load), and load diagnosticity (differentiating types of load). We report a large meta-review, in which we conclude that only a few studies were suitable for evaluating sensitivity and diagnosticity in complex real-world tasks. While these reveal that the fNIRS signal is adequately sensitive to gradations of load level changes (sensitivity), the diagnosticity of fNIRS to different sources of cognitive load remained uncertain. We manipulated mental load of a complex shape sorting task via working memory load (WM) and visual perceptual load (VL), while a secondary auditory task was present throughout. We measured the effect of these manipulations at the group-level using conventional secondary and eyetracking workload measures, as well as hemodynamic response in specific functional regions in the brain, including regions involved in multi-tasking (MT), VL, WM, and auditory load (AL). Our findings revealed that fNIRS is both sensitive and diagnostic to load in complex tasks, with greater sensitivity revealed by deoxyhemoglobin than oxyhemoglobin and the brain regions associated with diagnosticity align with neuroscience literature on perceptual load, WM, and goal-directed multitasking.