Attention lapses and behavioural microsleeps during tracking, psychomotor vigilance, and dual tasks

Conscious but not thinking-Mind-blanks during visuomotor tracking: An fMRI study of endogenous attention lapses

Attention lapses (ALs) are complete lapses of responsiveness in which performance is briefly but completely disrupted and during which, as opposed to microsleeps, the eyes remain open. Although the phenomenon of ALs has been investigated by behavioural and physiological means, the underlying cause of an AL has largely remained elusive. This study aimed to investigate the underlying physiological substrates of behaviourally identified endogenous ALs during a continuous visuomotor task, primarily to answer the question: Were the ALs during this task due to extreme mind-wandering or mind-blanks? The data from two studies were combined, resulting in data from 40 healthy non-sleep-deprived subjects (20M/20F; mean age 27.1 years, 20-45). Only 17 of the 40 subjects were used in the analysis due to a need for a minimum of two ALs per subject. Subjects performed a random 2-D continuous visuomotor tracking task for 50 and 20 min in Studies 1 and 2, respectively. Tracking performance, eye-video, and functional magnetic resonance imaging (fMRI) were recorded simultaneously. A human expert visually inspected the tracking performance and eye-video recordings to identify and categorise lapses of responsiveness as microsleeps or ALs. Changes in neural activity during 85 ALs (17 subjects) relative to responsive tracking were estimated by whole-brain voxel-wise fMRI and by haemodynamic response (HR) analysis in regions of interest (ROIs) from seven key networks to reveal the neural signature of ALs. Changes in functional connectivity (FC) within and between the key ROIs were also estimated. Networks explored were the default mode network, dorsal attention network, frontoparietal network, sensorimotor network, salience network, visual network, and working memory network. Voxel-wise analysis revealed a significant increase in blood-oxygen-level-dependent activity in the overlapping dorsal anterior cingulate cortex and supplementary motor area region but no significant decreases in activity; the increased activity is considered to represent a recovery-of-responsiveness process following an AL. This increased activity was also seen in the HR of the corresponding ROI. Importantly, HR analysis revealed no trend of increased activity in the posterior cingulate of the default mode network, which has been repeatedly demonstrated to be a strong biomarker of mind-wandering. FC analysis showed decoupling of external attention, which supports the involuntary nature of ALs, in addition to the neural recovery processes. Other findings were a decrease in HR in the frontoparietal network before the onset of ALs, and a decrease in FC between default mode network and working memory network. These findings converge to our conclusion that the ALs observed during our task were involuntary mind-blanks. This is further supported behaviourally by the short duration of the ALs (mean 1.7 s), which is considered too brief to be instances of extreme mind-wandering. This is the first study to demonstrate that at least the majority of complete losses of responsiveness on a continuous visuomotor task are, if not due to microsleeps, due to involuntary mind-blanks.

Multiscale entropy in a 10-minute vigilance task

Research has shown multiscale entropy, brain signal behavior across time scales, to reliably increase at lower time scales with time-on-task fatigue. However, multiscale entropy has not been examined in short vigilance tasks (i.e., ≤ 10 min). Addressing this gap, we examine multiscale entropy during a 10-minute Psychomotor Vigilance Test (PVT). Thirty-four participants provided neural data while completing the PVT. We compared the first 2 min of the task to the 7th and 8th minutes to avoid end-spurt effects. Results suggested increased multiscale entropy at lower time scales later compared to earlier in the task, suggesting multiscale entropy is a strong marker of time-on-task fatigue onset during short vigils. Separate analyses for Fast and Slow performers reveal differential entropy patterns, particularly over visual cortices. Here, observed brain-behavior linkage between entropy and reaction time for slow performers suggests that entropy assays over sensory cortices might have predictive value for fatigue onset or shifts from on- to off-task states.

Is there a u-shaped relationship between load levels and fatigue and recovery? An examination of possible mechanisms

In a previous study, an unexpected u-shaped relationship was observed between load level and fatigue/recovery responses. Moderate load levels resulted in lower perceived discomfort, pain, and fatigue, and shorter recovery times compared to either low or high load levels. This phenomenon has been reported in other studies, but no article has examined the possible mechanisms that might explain this u-shaped relationship. In this paper, we re-examined the previously published data and found that the phenomenon does not appear to be due to the experimental artefact; the u-shape may be due to unexpectedly lower fatigue effects at moderate loads, and higher fatigue effects at lower loads. We then conducted a literature review and identified several possible physiological, perceptual, and biomechanical explanatory mechanisms. No single mechanism explains the entirety of the phenomenon. Further research is needed on the relationship between work exposures, fatigue, and recovery, and the mechanisms related to the u-shaped relationship.Practitioner summary: We examine a previously observed u-shaped relationship between load level and fatigue/recovery, where moderate force resulted in lower perceived fatigue and shorter recovery times. A u-shaped fatigue response suggests that simply minimising load levels might not be an optimal approach to reduce the risk of workplace injuries.

Psychophysiological models of hypovigilance detection: A scoping review

Hypovigilance represents a major contributor to accidents. In operational contexts, the burden of monitoring/managing vigilance often rests on operators. Recent advances in sensing technologies allow for the development of psychophysiology-based (hypo)vigilance prediction models. Still, these models remain scarcely applied to operational situations and need better understanding. The current scoping review provides a state of knowledge regarding psychophysiological models of hypovigilance detection. Records evaluating vigilance measuring tools with gold standard comparisons and hypovigilance prediction performances were extracted from MEDLINE, PsychInfo, and Inspec. Exclusion criteria comprised aspects related to language, non-empirical papers, and sleep studies. The Quality Assessment tool for Diagnostic Accuracy Studies (QUADAS) and the Prediction model Risk Of Bias ASsessment Tool (PROBAST) were used for bias evaluation. Twenty-one records were reviewed. They were mainly characterized by participant selection and analysis biases. Papers predominantly focused on driving and employed several common psychophysiological techniques. Yet, prediction methods and gold standards varied widely. Overall, we outline the main strategies used to assess hypovigilance, their principal limitations, and we discuss applications of these models.

Psychometric curves reveal changes in bias, lapse rate, and guess rate in an online vigilance task

When human monitors are required to detect infrequent signals among noise, they typically exhibit a decline in correct detections over time. Researchers have attributed this vigilance decrement to three alternative mechanisms: shifts in response bias, losses of sensitivity, and attentional lapses. The current study examined the extent to which changes in these mechanisms contributed to the vigilance decrement in an online monitoring task. Participants in two experiments (N = 102, N = 192) completed an online signal detection task, judging whether the separation between two probes each trial exceeded a criterion value. Separation was varied across trials and data were fit with logistic psychometric curves using Bayesian hierarchical parameter estimation. Parameters representing sensitivity, response bias, attentional lapse rate, and guess rate were compared across the first and last 4 minutes of the vigil. Data gave decisive evidence of conservative bias shifts, an increased attentional lapse rate, and a decreased positive guess rate over time on task, but no strong evidence for or against an effect of sensitivity. Sensitivity decrements appear less robust than criterion shifts or attention lapses as causes of the vigilance loss.

Dashcam video footage-based analysis of microsleep-related behaviors in truck collisions attributed to falling asleep at the wheel

OBJECTIVE

With the rapid spread of dashcams, many car accidents have been recorded; however, behavioral approaches using these dashcam video footage have not been sufficiently examined. We employed dashcam video footage to evaluate microsleep-related behaviors immediately prior to real-world truck collisions in professional drivers to explore a new solution to reduce collisions attributed to falling asleep at the wheel.

METHODS

In total, 3,120 s of video footage (60 s/case × 52 cases) from real-world truck collisions of 52 professional drivers obtained from interior and exterior dashcams were used and visually analyzed in a second-by-second manner to simultaneously evaluate any eye changes and microsleep-related behaviors (the driver's anti-sleepiness behavior, behavioral signs of microsleep, and abnormal vehicle behavior) during driving.

RESULTS

Assessment of the frequency of occurrence of each item of microsleep-related behavior in the 52 collisions revealed that the item "touching" in terms of anti-sleepiness behavior, "absence of body movement" in terms of behavioral signs of microsleep, and "inappropriate line crossing" in terms of abnormal vehicle behavior were observed at the highest rate in all drivers (46.2%, 75.0%, and 78.8%, respectively). Decreases in anti-sleepiness behavior coincided with increases in behavioral signs of microsleep and abnormal vehicle behavior, with collisions occurring within approximately 40 s of these changes. Collisions were more common among young people and in the early morning and evening.

CONCLUSION

Our dashcam video footage-based analysis in truck collisions attributed to falling asleep at the wheel revealed the process of changes in microsleep-related driver and vehicle behaviors, classified as anti-sleepiness behavior, behavioral signs of microsleep, and abnormal vehicle behavior. Based on these findings, to prevent collisions caused by falling asleep at the wheel, it is crucial to monitor not only the driver's eyes, but also the driver's whole body and vehicle behavior simultaneously to reliably detect microsleep-related behaviors.

Performance, Hemodynamics, and Stress in a Two-Day Vigilance Task: Practical and Theoretical Implications

OBJECTIVE

To explore vigilance task performance, cerebral blood flow velocity (CBFV), workload, and stress in a within-subjects, two-session experiment.

BACKGROUND

Vigilance, or sustained attention, tasks are often characterized by a decline in operator performance and CBFV with time on task, and high workload and stress. Though performance is known to improve with practice, past research has not included measures of CBFV, stress, and workload in a within-subjects multi-session design, which may also provide insight into ongoing theoretical debate.

METHOD

Participants performed a vigilance task on two separate occasions. Performance, CBFV, workload, and self-reported stress were measured.

RESULTS

Within each session, results were consistent with the vigilance profile found in prior research. Across sessions, performance improved but the time on task decrement remained. Mean CBFV and workload ratings did not differ between sessions, but participants reported significantly less distress, worry, and engagement after session two compared to one.

CONCLUSION

Though practice may not disrupt the standard vigilance profile, it may serve to improve overall performance and reduce stress. However, repeated exposure may have negative implications for engagement and mind-wandering.

APPLICATION

It is important to better understand the relationship between experience, performance, physiological response, and self-reported stress and workload in vigilance because real-world environments often require operators to do the same task over many occasions. While performance improvement and reduced distress is an encouraging result, the decline in engagement requires further research. Results across sessions fail to provide support to the mind-wandering theory of vigilance.

Voluntary Urinary Retention Effects on Cognitive Performance

INTRODUCTION: Aircrew in-flight bladder relief remains an understudied stressor; specifically the effects of withholding urination on flight-relevant cognitive performance. This quasi-experimental study investigated whether voluntary urinary retention over a 3-h period negatively impacted cognitive performance.METHODS: We assessed vigilance using the psychomotor vigilance task (PVT) and measured the P3b event-related potential (ERP) in response to PVT stimuli. We also measured working memory (WM) performance using a change detection task and assessed the contralateral delay activity during the WM task using electroencephalography (EEG). Subjects (N = 29) completed a baseline test on both tasks, following bladder voiding and immediately after consuming 0.75 L of water. Subjects performed tasks at 1, 2, and 3 h post-void and urgency to void one's bladder was assessed regularly. A total of 17 subjects were able to complete the entire study protocol. Repeated-measures ANOVAs assessed changes in PVT and WM outcomes.RESULTS: Reaction time (RT) on the PVT was significantly impaired (5% slower) with longer urinary retention time and showed a 2.5-fold increase in the number of lapses (RT > 500 ms) with increased retention time. Together these results indicate that sustained attention was impaired with increased voluntary urine retention. We did not see significant changes in WM performance with our manipulations. Additionally, neural measures acquired with EEG for both tasks did not show any significant effect.DISCUSSION: As measured with the PVT, sustained attention was impaired during 3 h of voluntary urinary retention, highlighting the need for further development of adequate bladder relief systems in military aviation.Griswold CA, Vento KA, Blacker KJ. Voluntary urinary retention effects on cognitive performance. Aerosp Med Hum Perform. 2023; 94(2):79-85.

Effects of total sleep deprivation on execution lapses during vigilance tasks

Total sleep deprivation (TSD) results in reduced efficiency of cognitive resources. Moreover, when the available cognitive resources are less than required, individuals exhibit lapses in responsiveness. Accordingly, this study explored the effects of TSD on executive function and the characteristics of execution lapses. Functional near-infrared spectroscopy was used to monitor the prefrontal cortex's functional connections in resting and tasking states for various sleep deprivation durations. Data from participants' attentional performance test and self-reported fatigue were collected over 30 hours of wakefulness. Task performance was compared based on time of day, time on task, and reaction time. The results show that participants' arousal level significantly decreased post 14 hours (P < .05), while sleepiness increased. The prefrontal cortex connection and attentional performance dropped at the Window of Circadian Low (3:00 ~ 6:00). The number of execution lapses was higher during the initiation, inhibition, and fatigue phases and rose markedly post 14 hours of wakefulness. We conclude that maintaining better inhibition control requires a reasonable extension of the reaction time. Moreover, subjective perception is significantly correlated with task performance and right prefrontal connection strength. This study presents the scientific evidence for measures to address consistently long working hours and disrupted circadian rhythms.

Predicting and mitigating fatigue effects due to sleep deprivation: A review

The deleterious effects of insufficient sleep have been well-established in the literature and can lead to a wide range of adverse health outcomes. Some of the most replicated findings demonstrate significant declines in cognitive functions such as vigilance and executive attention, psychomotor and cognitive speed, and working memory. Consequently, these decrements often lead individuals who are in a fatigued state to engage in substandard performance on everyday tasks. In the interest of curtailing these effects, prior work has attempted to identify mechanisms that predict fatigue onset and develop techniques to mitigate its negative consequences. Nonetheless, these results are often confounded by variables such as an individual’s resistance to fatigue, sleep history, and unclear distinctions about whether certain performance decrements are present due to fatigue or due to other confounding factors. Similar areas of research have provided approaches to produce models for the prediction of cognitive performance decrements due to fatigue through the use of multi-modal recording and analysis of fatigue-related responses. Namely, gathering and combining response information from multiple sources (i.e., physiological and behavioral) at multiple timescales may provide a more comprehensive representation of what constitutes fatigue onset in the individual. Therefore, the purpose of this review is to discuss the relevant literature on the topic of fatigue-related performance effects with a special emphasis on a variety of physiological and behavioral response variables that have shown to be sensitive to changes in fatigue. Furthermore, an increasing reliance on sleep loss, meant to assist in meeting the demands of modern society, has led to an upsurge in the relevance of identifying dependable countermeasures for fatigued states. As such, we will also review methods for the mitigation of performance effects due to fatigue and discuss their usefulness in regulating these effects. In sum, this review aims to inspire future work that will create opportunities to detect fatigue and mitigate its effects prior to the onset of cognitive impairments.

Cognitive load mitigates the executive but not the arousal vigilance decrement

Previous research has shown opposite effects of dual tasking on the vigilance decrement phenomenon. We examined the executive (i.e., detecting infrequent critical signals) and arousal (i.e., sustaining a fast reaction to stimuli without much control on responses) vigilance decrements as a function of task load. Ninety-six participants performed either a single signal-detection (i.e., executive vigilance) task, a single reaction time (i.e., arousal vigilance) task, or a dual vigilance task with the same stimuli and procedure. All participants self-reported their fatigue' state along the session. Exploratory analyses included data from a previous study with a triple task condition. Task load significantly modulated the executive but not the arousal vigilance decrement. Interestingly, the largest increase in mental fatigue was observed in the single executive vigilance task condition. We discuss limitations of classic vigilance theories to account for the vigilance decrement and changes in mental fatigue as a function of task load.

European NCAP Program Developments to Address Driver Distraction, Drowsiness and Sudden Sickness

Driver distraction and drowsiness remain significant contributors to death and serious injury on our roads and are long standing issues in road safety strategies around the world. With developments in automotive technology, including driver monitoring, there are now more options available for automotive manufactures to mitigate risks associated with driver state. Such developments in Occupant Status Monitoring (OSM) are being incorporated into the European New Car Assessment Programme (Euro NCAP) Safety Assist protocols. The requirements for OSM technologies are discussed along two dimensions: detection difficulty and behavioral complexity. More capable solutions will be able to provide higher levels of system availability, being the proportion of time a system could provide protection to the driver, and will be able to capture a greater proportion of complex real-word driver behavior. The testing approach could initially propose testing using both a dossier of evidence provided by the Original Equipment Manufacturer (OEM) alongside selected use of track testing. More capable systems will not rely only on warning strategies but will also include intervention strategies when a driver is not attentive. The roadmap for future OSM protocol development could consider a range of known and emerging safety risks including driving while intoxicated by alcohol or drugs, cognitive distraction, and the driver engagement requirements for supervision and take-over performance with assisted and automated driving features.

Visually guided movement with increasing time-on-task: Differential effects on movement preparation and movement execution

Top-down cognitive control seems to be sensitive to the detrimental effects of fatigue induced by time-on-task (ToT). The planning and preparation of the motor responses may be especially vulnerable to ToT. Yet, effects of ToT specific to the different phases of movements have received little attention. Therefore, in three experiments, we assessed the effect of ToT on a mouse-pointing task. In Experiment 1, there were 16 possible target positions with variable movement directions. In Experiment 2, the layout of the targets was simplified. In Experiment 3, using cuing conditions, we examined whether the effects of ToT on movement preparation and execution were caused by an increased orientation deficit or decreased phasic alertness. In each experiment, initiation of movement (preparatory phase) became slower, movement execution became faster and overall response time remained constant with increasing ToT. There was, however, no significant within-person association between the preparatory and execution phases. In Experiments 1 and 2, we found a decreasing movement time/movement error ratio, suggesting a more impulsive execution of the pointing movement. In addition, ToT was also accompanied with imprecise movement execution as indicated by the increased errors, mainly in Experiment 2. The results of Experiment 3 indicated that ToT did not induce orientation and phasic alerting deficits but rather was accompanied by decreased tonic alertness.

Individual differences in attentional lapses are associated with fiber-specific white matter microstructure in healthy adults

Attentional lapses interfere with goal-directed behaviors, which may result in harmless (e.g., not hearing instructions) or severe (e.g., fatal car accident) consequences. Task-related functional MRI (fMRI) studies have shown a link between attentional lapses and activity in the frontoparietal network. Activity in this network is likely to be mediated by the organization of the white matter fiber pathways that connect the regions implicated in the network, such as the superior longitudinal fasciculus I (SLF-I). In the present study, we investigate the relationship between susceptibility to attentional lapses and relevant white matter pathways in 36 healthy adults (23 females, M_age  = 31.56 years). Participants underwent a diffusion MRI (dMRI) scan and completed the global-local task to measure attentional lapses, similar to previous fMRI studies. Applying the fixel-based analysis framework for fiber-specific analysis of dMRI data, we investigated the association between attentional lapses and variability in microstructural fiber density (FD) and macrostructural (morphological) fiber-bundle cross section (FC) in the SLF-I. Our results revealed a significant negative association between higher total number of attentional lapses and lower FD in the left SLF-I. This finding indicates that the variation in the microstructure of a key frontoparietal white matter tract is associated with attentional lapses and may provide a trait-like biomarker in the general population. However, SLF-I microstructure alone does not explain propensity for attentional lapses, as other factors such as sleep deprivation or underlying psychological conditions (e.g., sleep disorders) may also lead to higher susceptibility in both healthy people and those with neurological disorders.

Microsleep versus Sleep Onset Latency during Maintenance Wakefulness Tests: Which One Is the Best Marker of Sleepiness?

The interpretation of the Maintenance Wakefulness Test (MWT) relies on sleep onset detection. However, microsleeps (MSs), i.e., brief periods of sleep intrusion during wakefulness, may occur before sleep onset. We assessed the prevalence of MSs during the MWT and their contribution to the diagnosis of residual sleepiness in patients treated for obstructive sleep apnea (OSA) or hypersomnia. The MWT of 98 patients (89 OSA, 82.6% male) were analyzed for MS scoring. Polysomnography parameters and clinical data were collected. The diagnostic value for detecting sleepiness (Epworth Sleepiness Scale > 10) of sleep onset latency (SOL) and of the first MS latency (MSL) was assessed by the area under the receiver operating characteristic (ROC) curve (AUC, 95% CI). At least one MS was observed in 62.2% of patients. MSL was positively correlated with SOL (r = 0.72, p < 0.0001) but not with subjective scales, clinical variables, or polysomnography parameters. The use of SOL or MSL did not influence the diagnostic performance of the MWT for subjective sleepiness assessment (AUC = 0.66 95% CI (0.56, 0.77) versus 0.63 95% CI (0.51, 0.74)). MSs are frequent during MWTs performed in patients treated for sleep disorders, even in the absence of subjective sleepiness, and may represent physiological markers of the wake-to-sleep transition.

Association between chronotype and psychomotor performance of rotating shift workers

It is known that the chronotype potentially mediates the performance and tolerance to work in shifts and that shift rotation is associated with negative effects on psychomotor performance. This study aimed to evaluate the effect of chronotype on psychomotor performance throughout a complete shift rotation schedule. Thirty males working in clockwise rotating shifts from a mining company were evaluated under a real-life condition over the following shift schedule: 2 days of day work, 2 days of evening work and 2 days of night work. The chronotype was determined using the Munich Chronotype Questionnaire adapted for shift workers and the obtained scores were categorized by tertiles (early-type, intermediate-type and late-type). Work performance was evaluated by Psychomotor Vigilance Test (PVT) daily just before shift starts and after shift ends. Sleep duration was evaluated by actigraphy over the whole shift. No isolated effect of the shift or interaction between shift and chronotype was found in the performance variables evaluated. A significant isolated effect of the chronotype showed that the early-type individuals had higher values of pre- and post-work Mean of Reaction Time (MRT) (308.77 ± 10.03 ms and 306.37 ± 8.53 ms, respectively) than the intermediate-type (257.61 ± 6.63 ms and 252.91 ± 5.97 ms, respectively, p < 0.001) and the late-type (273.35 ± 6.96 ms and 262.88 ± 6.05 ms, respectively, p < 0.001). In addition, late individuals presented a greater number of lapses of attention (5.00 ± 0.92; p < 0.05) than early (1.94 ± 0.50, p < 0.05) and intermediate (1.33 ± 0.30, p < 0.001) ones. We concluded that, compared with intermediates, late-type workers had a greater number of lapses of attention on the shift schedule as a whole, while early-type workers showed the highest pre- and post-work MRT. These findings show that the psychomotor performance of rotating shift workers seems to be influenced by the chronotype, but not by the shift rotation.

Reservoir computing approaches to microsleep detection

The detection of microsleeps in a wide range of professionals working in high-risk occupations is very important to workplace safety. A microsleep classifier is presented that employs a reservoir computing (RC) methodology. Specifically, echo state networks (ESN) are used to enhance previous benchmark performances on microsleep detection. A clustered design using a novel ESN-based leaky integrator is presented. The effectiveness of this design lies with the simplicity of using a fine-grained architecture, containing up to 8 neurons per cluster, to capture individualized state dynamics and achieve optimal performance. This is the first study to have implemented and evaluated EEG-based microsleep detection using RC models for the detection of microsleeps from the EEG. Microsleep state detection was achieved using a cascaded ESN classifier with leaky-integrator neurons employing 60 principal components from 544 power spectral features. This resulted in a leave-one-subject-out average detection in performance of Φ= 0.51 ± 0.07 (mean ± SE), AUC-ROC = 0.88 ± 0.03, and AUC-PR = 0.44 ± 0.09. Although performance of EEG-based microsleep detection systems is still considered modest, this refined method achieved a new benchmark in microsleep detection.

Deep Neural Network for Visual Stimulus-Based Reaction Time Estimation Using the Periodogram of Single-Trial EEG

Multiplexed deep neural networks (DNN) have engendered high-performance predictive models gaining popularity for decoding brain waves, extensively collected in the form of electroencephalogram (EEG) signals. In this paper, to the best of our knowledge, we introduce a first-ever DNN-based generalized approach to estimate reaction time (RT) using the periodogram representation of single-trial EEG in a visual stimulus-response experiment with 48 participants. We have designed a Fully Connected Neural Network (FCNN) and a Convolutional Neural Network (CNN) to predict and classify RTs for each trial. Though deep neural networks are widely known for classification applications, cascading FCNN/CNN with the Random Forest model, we designed a robust regression-based estimator to predict RT. With the FCNN model, the accuracies obtained for binary and 3-class classification were 93% and 76%, respectively, which further improved with the use of CNN (94% and 78%, respectively). The regression-based approach predicted RTs with correlation coefficients (CC) of 0.78 and 0.80 for FCNN and CNN, respectively. Investigating further, we found that the left central as well as parietal and occipital lobes were crucial for predicting RT, with significant activities in the theta and alpha frequency bands.

Neural Correlates of Attention Lapses During Continuous Tasks

Attention lapses (ALs) are common phenomenon, which can affect our performance and productivity by slowing or suspending responsiveness. Occurrence of ALs during continuous monitoring tasks, such as driving or operating machinery, can lead to injuries and fatalities. However, we have limited understanding of what happens in the brain when ALs intrude during such continuous tasks. Here, we analyzed fMRI data from a study, in which participants performed a continuous visuomotor tracking task during fMRI scanning. A total of 68 ALs were identified from 20 individuals, using visual rating of tracking performance and video-based eye-closure. ALs were found to be associated with increased BOLD fMRI activity partially in the executive control network, and sensorimotor network. Surprisingly, we found no evidence of deactivations.

Relationship Between Physiologically Measured Attention and Behavioral Task Engagement in Persons With Chronic Aphasia

Purpose Persons with aphasia (PWAs) have been shown to have impaired attention skills that may interfere with their ability to successfully participate in speech and language therapy. Fluctuations in attention can be detected using physiological measures such as electroencephalography (EEG), but these measures can be impractical for clinical use. The primary purpose of this study was to investigate observable behavioral signs of attention as a means of measuring within-session fluctuations in attention by comparing behavioral ratings to physiological changes. Other aims were to understand the relationship between observable behaviors and task performance and to determine whether syntactic complexity influences behavioral attention. Method Ten PWAs and 10 neurologically healthy adults underwent a sentence-reading task with 45 active and 45 passive sentences while video/audio and EEG data were recorded continuously. EEG data for each trial were classified into one of four levels of attention using a classification algorithm (Berka et al., 2004), and video/audio data were scored for accuracy and behavioral engagement by two trained speech-language pathologist students using a behavioral rating scale of inattention (Whyte et al., 1996). Results Results showed that behavioral engagement was significantly correlated with task performance, with higher engagement scores associated with fewer errors. Behavioral engagement did not differ based on syntactic complexity for either group, but PWAs had significantly lower behavioral engagement scores when they were in lower/distracted states of physiologically measured vigilant attention. Conclusion Behavioral observation may provide an alternative means of detecting clinically significant lapses in attention during aphasia therapy.

Examining the fatigue-quality relationship in manufacturing

A recent systematic review identified 73 empirical studies that linked human factors (HF) with manufacturing quality. Human fatigue was noted as a frequent (n = 26) issue in the HF-quality relationship - a finding that warrants closer examination. We extend this review by investigating the relationship between fatigue and manufacturing quality by identifying how fatigue has been conceptualized and measured, and we attempted to quantify their relationship. From the original database, 12 of 26 relevant studies (46%) indicated that physical fatigue was the primary contributor to observed quality deficits. There was a positive relationship between fatigue and quality deficits, with fatigue accounting up to 42% of the variance. More studies are needed to improve the resolution, specificity, and power of these analyses. This study sheds light on the role of HF and human fatigue effects on manufacturing quality with macroergonomic implications for embedding HF aspects into design and quality assurance processes.

Microsleep is associated with brain activity patterns unperturbed by auditory inputs

Microsleeps are brief episodes of arousal level decrease manifested through behavioral signs. Brain activity during microsleep in the presence of external stimulus remains poorly understood. In this study, we sought to understand neural responses to auditory stimulation during microsleep. We gave participants the simple task of listening to audios of different pitches and amplitude modulation frequencies during early afternoon functional MRI scans. We found the following: 1) microsleep was associated with cortical activations in broad motor and sensory regions and deactivations in thalamus, irrespective of auditory stimulation; 2) high and low pitch audios elicited different activity patterns in the auditory cortex during awake but not microsleep state; and 3) during microsleep, spatial activity patterns in broad brain regions were similar regardless of the presence or types of auditory stimulus (i.e., stimulus invariant). These findings show that the brain is highly active during microsleep but the activity patterns across broad regions are unperturbed by auditory inputs.NEW & NOTEWORTHY During deep drowsy states, auditory inputs could induce activations in the auditory cortex, but the activation patterns lose differentiation to high/low pitch stimuli. Instead of random activations, activity patterns across the brain during microsleep appear to be structured and may reflect underlying neurophysiological processes that remain unclear.

Modeling stochastic resonance in humans: The influence of lapse rate

Adding noise to sensory signals generally decreases human performance. However, noise can improve performance too, through a process called stochastic resonance (SR). This paradoxical effect may be exploited in psychophysical experiments to provide insights into how the sensory system processes noise. Here, I develop an extension on signal detection theory to model stochastic resonance. I show that the inclusion of lapse rate allows for the occurrence of stochastic resonance in terms of the performance metric d', when the criterion is set suboptimally. High levels of lapse rate, however, cause stochastic resonance to disappear. It is also shown that noise generated in the brain (i.e., internal noise) may obscure any effect of stochastic resonance in experimental settings. I further relate the model to a standard equivalent noise model, the linear amplifier model, and show that lapse rate scales the threshold versus noise (TvN) curve, similar to the efficiency parameter in equivalent noise (EN) models. Therefore, lapse rate provides a psychophysical explanation for reduced efficiency in EN paradigms. Furthermore, I note that ignoring lapse rate may lead to an overestimation of internal noise in EN paradigms. Overall, describing stochastic resonance in terms of signal detection theory, with the inclusion of lapse rate, may provide valuable new insights into how human performance depends on internal and external noise. It may have applications in improving human performance in situations where the criterion is set suboptimally, and it may provide additional insight into internal noise hypotheses related to autism spectrum disorder.

Attentional lapses are reduced by repeated stimuli having own-name during a monotonous task

The goal of the present study was to examine the effect of listening to self-relevant words (i.e., one’s own name) on vigilant attention, arousal, and subjective sleepiness during performance of a psychomotor vigilance test (PVT). Twenty-one participants aged 20–26 years (22.2 ± 1.76) performed a PVT in four experimental conditions: one in which their own full name was pronounced every 20 s in the stimuli epochs, one in which their full name was pronounced in inverted form, one in which beeps were played, and a control condition with no stimuli. Listening to personal names reduced attentional lapses during the PVT (i.e., the number of reaction times no less than 500 ms). The results are a first step in applying the name effect to technologies and devices aimed at maintaining arousal levels and preventing accidents during a monotonous task, such as driving.

Exploring the Relationship of Task Performance and Physical and Cognitive Fatigue During a Daylong Light Precision Task

OBJECTIVE

Our aim was to explore the relationship between fatigue and operation system performance during a simulated light precision task over an 8-hr period using a battery of physical (central and peripheral) and cognitive measures.

BACKGROUND

Fatigue may play an important role in the relationship between poor ergonomics and deficits in quality and productivity. However, well-controlled laboratory studies in this area have several limitations, including the lack of work relevance of fatigue exposures and lack of both physical and cognitive measures. There remains a need to understand the relationship between physical and cognitive fatigue and task performance at exposure levels relevant to realistic production or light precision work.

METHOD

Errors and fatigue measures were tracked over the course of a micropipetting task. Fatigue responses from 10 measures and errors in pipetting technique, precision, and targeting were submitted to principal component analysis to descriptively analyze features and patterns.

RESULTS

Fatigue responses and error rates contributed to three principal components (PCs), accounting for 50.9% of total variance. Fatigue responses grouped within the three PCs reflected central and peripheral upper extremity fatigue, postural sway, and changes in oculomotor behavior.

CONCLUSION

In an 8-hr light precision task, error rates shared similar patterns to both physical and cognitive fatigue responses, and/or increases in arousal level.

APPLICATION

The findings provide insight toward the relationship between fatigue and operation system performance (e.g., errors). This study contributes to a body of literature documenting task errors and fatigue, reflecting physical (both central and peripheral) and cognitive processes.

Rest Is Still Best

OBJECTIVE

We examined the impact task interruptions of differing qualitative and quantitative load have on visuospatial vigilance sensitivity.

BACKGROUND

The vigilance decrement and attempts to develop countermeasures to the decrement is one of the most important human factors issues. There is an ongoing debate between those who interpret the increase in the rate of failures to detect signals over time as being due to objective task monotony or task underload and those who interpret this increased failure proneness as being predominately due to cognitive-resource depletion and task overload.

METHOD

Participants were assigned at random to one of six interruptions: Participants were given a complete rest (rest); participants completed a 1-back verbal working-memory (WM) task, a 3-back verbal WM task, a 1-back spatial WM task, or a 3-back spatial WM task; or participants performed the primary vigilance task (continuous).

RESULTS

Postinterruption performance was best for rest and worst for continuous. A resource theory perspective led us to make two possible predictions of relative interruption effect orders of the six conditions out of 720 possible orderings. We found one of the two orders.

CONCLUSION

Overall, the vigilance sensitivity decrement appears to be due to the recurring use of particular cognitive resources, and resource theorists should explore this more extensively in the future.

APPLICATION

Countermeasures for the vigilance decrement should be based on clear cognitive-resource considerations. Rest is the best countermeasure. Intervening tasks should be chosen that minimize resource-demand overlap with the vigilance task.