Now you hear me, now you don't: eyelid closures as an indicator of auditory task disengagement

Sleep, Well-Being, and Cognition in Medical Interns on a Float or Overnight Call Schedule

Importance

Extended work hours and night shifts are essential in health care, but negatively affect physician sleep, well-being, and patient care. Alternative schedules with shorter work hours and/or reduced irregularity might mitigate these issues.

Objective

To compare sleep, well-being, and cognition between interns working irregular, extended shifts (call schedule), and those working a more regular schedule with restricted hours (float schedule).

Design, Setting, and Participants

In this observational longitudinal cohort study, interns in a Singapore-based teaching hospital were studied for 8 weeks from January 2022 to July 2023. Data were analyzed from July 2023 to July 2024.

Exposure

Participants worked either regular approximately 10-hour workdays, interspersed with 24 hour or more overnight calls 4 to 5 times a month, or a float schedule, which included regular approximately 10-hour workdays, and 5 to 7 consecutive approximately 12-hour night shifts every 2 months. Exposure was based on departmental training and operational needs.

Main Outcomes and Measures

Sleep was measured with wearable sleep trackers and an electronic diary. Day-to-day well-being and cognitive assessments were collected through a smartphone application. Assessments included the Sleep Regularity Index (SRI; determines the probability of an individual being in the same state [sleep or wake] at any 2 time points 24 hours apart, with 0 indicating highly random sleep patterns and 100 denoting perfect regularity) and Pittsburgh Sleep Quality Inventory (PSQI; scores ranges from 0 to 21, with higher scores indicating poorer sleep; a score greater than 5 suggests significant sleep difficulties).

Results

Participants (mean [SD] age, 24.7 [1.1] years; 57 female participants [59.4%]; 41 on call schedule [42.7%]; 55 on float schedule [57.3%]) provided 4808 nights of sleep (84.2%) and 3390 days (59.3%) of well-being and cognition assessments. Participants on a float schedule had higher SRI scores (mean [SD] score, 69.4 [6.16]) and had better quality sleep (PSQI mean [SD] score, 5.4 [2.3]), than participants on call schedules (SRI mean [SD] score, 56.1 [11.3]; t91 = 6.81; mean difference, 13.3; 95% CI, 9.40 to 17.22; P < .001; PSQI mean [SD] score, 6.5 [2.3]; t79 = 2.16; 95% CI, 0.09 to 2.15; P = .03). Overnight call shifts, but not night float shifts, were associated with poorer mood (-13%; β = -6.79; 95% CI, -9.32 to -4.27; P < .001), motivation (-21%; β = -10.09; 95% CI, -12.55 to -7.63; P < .001), and sleepiness ratings (29%; β = 15.96; 95% CI, 13.01 to 18.90; P < .001) and impaired vigilance (21 ms slower; β = 20.68; 95% CI, 15.89 to 25.47; P < .001) compared with regular day shifts. Night shifts with naps were associated with better vigilance (16 ms faster; β = -15.72; 95% CI, -28.27 to -3.17; P = .01) than nights without naps.

Conclusions and relevance

In this cohort study, 24-hour call schedules were associated with poorer sleep, well-being, and cognition outcomes than float schedules. Naps during night shifts benefited vigilance in both schedules.

Extended wakefulness alters the relationship between EEG oscillations and performance in a sustained attention task

During drowsiness, maintaining consistent attention becomes difficult, leading to behavioural lapses. Bursts of oscillations in the electroencephalogram (EEG) might predict such lapses, given that alpha bursts increase during inattention and theta bursts increase with time spent awake. Paradoxically, however, alpha bursts decrease with time awake and theta bursts increase during focussed attention and cognitive tasks. Therefore, we investigated to what extent theta and alpha bursts predicted performance in a sustained attention task, either when well rested (baseline, BL) or following 20 h of extended wakefulness (EW). High-density EEG was measured in 18 young adults, and the timing of bursts was related to trial outcomes (fast, slow, and lapse trials). To increase the likelihood of lapses, the task was performed under soporific conditions. Against expectations, alpha bursts were more likely before fast trials and less likely before lapses at baseline, although the effect was substantially reduced during extended wakefulness. Theta bursts showed no significant relationship to behavioural outcome either at baseline or extended wakefulness. However, following exploratory analyses, we found that large-amplitude theta and alpha bursts were more likely to be followed by lapse trials during extended wakefulness but not baseline. In summary, alpha bursts during baseline anticipated better trial outcomes, whereas large-amplitude theta and alpha bursts during extended wakefulness anticipated worse outcomes. Therefore, neither theta nor alpha bursts maintain a consistent relationship with behaviour under different levels of overall vigilance.

How and when EEG reflects changes in neuronal connectivity due to time awake

Being awake means forming new memories, primarily by strengthening neuronal synapses. The increase in synaptic strength results in increasing neuronal synchronicity, which should result in higher amplitude electroencephalography (EEG) oscillations. This is observed for slow waves during sleep but has not been found for wake oscillations. We hypothesized that this was due to a limitation of spectral power analysis, which does not distinguish between changes in amplitudes from changes in number of occurrences of oscillations. By using cycle-by-cycle analysis instead, we found that theta and alpha oscillation amplitudes increase as much as 30% following 24 h of extended wake. These increases were interrupted during the wake maintenance zone (WMZ), a window just before bedtime when it is difficult to fall asleep. We found that pupil diameter increased during this window, suggesting the ascending arousal system is responsible. In conclusion, wake oscillation amplitudes reflect increased synaptic strength, except during the WMZ.

PERCLOS-based technologies for detecting drowsiness: current evidence and future directions

Drowsiness associated with sleep loss and circadian misalignment is a risk factor for accidents and human error. The percentage of time that the eyes are more than 80% closed (PERCLOS) is one of the most validated indices used for the passive detection of drowsiness, which is increased with sleep deprivation, after partial sleep restriction, at nighttime, and by other drowsiness manipulations during vigilance tests, simulated driving, and on-road driving. However, some cases have been reported wherein PERCLOS was not affected by drowsiness manipulations, such as in moderate drowsiness conditions, in older adults, and during aviation-related tasks. Additionally, although PERCLOS is one of the most sensitive indices for detecting drowsiness-related performance impairments during the psychomotor vigilance test or behavioral maintenance of wakefulness test, no single index is currently available as an optimal marker for detecting drowsiness during driving or other real-world situations. Based on the current published evidence, this narrative review suggests that future studies should focus on: (1) standardization to minimize differences in the definition of PERCLOS between studies; (2) extensive validation using a single device that utilizes PERCLOS-based technology; (3) development and validation of technologies that integrate PERCLOS with other behavioral and/or physiological indices, because PERCLOS alone may not be sufficiently sensitive for detecting drowsiness caused by factors other than falling asleep, such as inattention or distraction; and (4) further validation studies and field trials targeting sleep disorders and trials in real-world environments. Through such studies, PERCLOS-based technology may contribute to preventing drowsiness-related accidents and human error.

Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes

Falling asleep is common in fMRI studies. By using long eyelid closures to detect microsleep onset, we showed that the onset and termination of short sleep episodes invokes a systematic sequence of BOLD signal changes that are large, widespread, and consistent across different microsleep durations. The signal changes are intimately intertwined with shifts in respiration and heart rate, indicating that autonomic contributions are integral to the brain physiology evaluated using fMRI and cannot be simply treated as nuisance signals. Additionally, resting state functional connectivity (RSFC) was altered in accord with the frequency of falling asleep and in a manner that global signal regression does not eliminate. Our findings point to the need to develop a consensus among neuroscientists using fMRI on how to deal with microsleep intrusions. SIGNIFICANCE STATEMENT: Sleep, breathing and cardiac action are influenced by common brainstem nuclei. We show that falling asleep and awakening are associated with a sequence of BOLD signal changes that are large, widespread and consistent across varied durations of sleep onset and awakening. These signal changes follow closely those associated with deceleration and acceleration of respiration and heart rate, calling into question the separation of the latter signals as 'noise' when the frequency of falling asleep, which is commonplace in RSFC studies, correlates with the extent of RSFC perturbation. Autonomic and central nervous system contributions to BOLD signal have to be jointly considered when interpreting fMRI and RSFC studies.

Tracking intermediate performance of vigilant attention using multiple eye metrics

Vigilance deficits account for a substantial number of accidents and errors. Current techniques to detect vigilance impairment measure only the most severe level evident in eyelid closure and falling asleep, which is often too late to avoid an accident or error. The present study sought to identify ocular biometrics of intermediate impairment of vigilance and develop a new technique that could detect a range of deficits in vigilant attention (VA). Sixteen healthy adults performed well-validated Psychomotor Vigilance Test (PVT) for tracking vigilance attention while undergoing simultaneous recording of eye metrics every 2 hours during 38 hours of continuous wakefulness. A novel marker was found that measured VA when the eyes were open-the prevalence of microsaccades. Notably, the prevalence of microsaccades decreased in response to sleep deprivation and time-on-task. In addition, a novel algorithm for detecting multilevel VA was developed, which estimated performance on the PVT by integrating the novel marker with other eye-related indices. The novel algorithm also tracked changes in intermediate level of VA (specific reaction times in the PVT, i.e. 300-500 ms) during prolonged time-on-task and sleep deprivation, which had not been tracked previously by conventional techniques. The implication of the findings is that this novel algorithm, named "eye-metrical estimation version of the PVT: PVT-E," can be used to reduce human-error-related accidents caused by vigilance impairment even when its level is intermediate.

Workers’ Aging Management—Human Fatigue at Work: An Experimental Offices Study

The aging issue in the work context is becoming a significant element of the future sustainability of service and industrial companies. It is well known that with increasing worker age the problem of maintaining the performance and the safety level when fatigue increases is a crucial point, and fatigue increases with the age. Due to social and political developments, especially in Western countries, the retirement age is increasing and companies operate with a higher workforce mean age. Therefore, the problem of recognizing and measuring fatigue has become a key aspect in the management of aging. Note that in the scientific engineering field, the problem of fatigue evaluation when a worker is performing his/her work activities is an important issue in the industrial and service world and especially in the context of the researchers that are investigating the human reliability assessment. As it is clear from the literature, the industrial operations management are suffering from some misleading concepts that only the medicine scientific context can clarify. Therefore, the aim of this paper is to define what are the open issues and the misleading concepts present in the classical fatigue evaluation methods, and second to define two experimental curves of fatigue that will help the decision makers to minimize the impact of fatigue on the workers, thus maximizing the sustainability of the working tasks assigned. This aim is achieved by examining the medical literature about the measurement of a particular kind of fatigue related to the circadian cycle, i.e., the cognitive one; after that, a survey about the possible technologies for measurements is performed. On the basis of technology selection, an experiment on real work activities is performed and some remarkable results about the fatigue in the workers observed and the technology use and its limitations are defined.

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.

Sleep deprivation, effort allocation and performance

Sleep deprivation causes physiological alterations (e.g., decreased arousal, intrusion of micro-sleeps), that negatively affect performance on a wide range of cognitive domains. These effects indicate that cognitive performance relies on a capacity-limited system that may be more challenged in the absence of sleep. Additionally, sleep loss can result in a lower willingness to exert effort in the pursuit of performance goals. Such deficits in motivation may interact with the effects of capacity limitations to further stifle cognitive performance. When sleep-deprived, cognitive performance is experienced as more effortful, and intrinsic motivation to perform dwindles. On the other hand, increasing motivation extrinsically (e.g., by monetary incentives) can inspire individuals to allocate more task-related effort, and can partially counter performance deficits associated with sleep deprivation. In this chapter, we review current research on the interplay between sleep deprivation, effort and performance. We integrate these findings into an effort-based decision-making framework in which sleep-related performance impairments may result from a voluntary decision to withdraw effort. We conclude with practical implications of this framework for performance in healthy populations (e.g., work productivity) and clinical conditions.

Spontaneous eyelid closures link vigilance fluctuation with fMRI dynamic connectivity states

Fluctuations in resting-state functional connectivity occur but their behavioral significance remains unclear, largely because correlating behavioral state with dynamic functional connectivity states (DCS) engages probes that disrupt the very behavioral state we seek to observe. Observing spontaneous eyelid closures following sleep deprivation permits nonintrusive arousal monitoring. During periods of low arousal dominated by eyelid closures, sliding-window correlation analysis uncovered a DCS associated with reduced within-network functional connectivity of default mode and dorsal/ventral attention networks, as well as reduced anticorrelation between these networks. Conversely, during periods when participants' eyelids were wide open, a second DCS was associated with less decoupling between the visual network and higher-order cognitive networks that included dorsal/ventral attention and default mode networks. In subcortical structures, eyelid closures were associated with increased connectivity between the striatum and thalamus with the ventral attention network, and greater anticorrelation with the dorsal attention network. When applied to task-based fMRI data, these two DCS predicted interindividual differences in frequency of behavioral lapsing and intraindividual temporal fluctuations in response speed. These findings with participants who underwent a night of total sleep deprivation were replicated in an independent dataset involving partially sleep-deprived participants. Fluctuations in functional connectivity thus appear to be clearly associated with changes in arousal.

Retrospective Ratings of Emotions: the Effects of Age, Daily Tiredness, and Personality

Remembering the emotions we have experienced in the past is the core of one's unique life-experience. However, there are many factors, both at the state and trait level that can affect the way past feelings are seen. The main aim of the current study was to examine the impact of individual differences on systematic biases in retrospective ratings compared to the momentary experience of basic emotions such as sadness, fear, happiness, and anger. To this end, an experience sampling study across 2 weeks was conducted using a younger and an older age-group; the experience of momentary emotions was assessed on 7 randomly determined occasions per day, the retrospective ratings being collected at the end of each day about that day, as well as at the end of the study about the previous 2 weeks. The results indicated that age and daily tiredness have significant effects on retrospective emotion ratings over a 1-day period (state level), enhancing the retrospective ratings of negative emotions and decreasing the ratings of felt happiness. Whereas personality traits influence the more long-term emotion experience (trait level), with all Big Five personality traits having selective impact on retrospective emotion ratings of fear, sadness, happiness, and anger. Findings provide further evidence about the systematic biases in retrospective emotion ratings, suggesting that, although retrospective ratings are based on momentary experience, daily tiredness and personality traits systematically influence the way in which past feelings are seen.

Increased Automaticity and Altered Temporal Preparation Following Sleep Deprivation

STUDY OBJECTIVES

Temporal expectation enables us to focus limited processing resources, thereby optimizing perceptual and motor processing for critical upcoming events. We investigated the effects of total sleep deprivation (TSD) on temporal expectation by evaluating the foreperiod and sequential effects during a psychomotor vigilance task (PVT). We also examined how these two measures were modulated by vulnerability to TSD.

DESIGN

Three 10-min visual PVT sessions using uniformly distributed foreperiods were conducted in the wake-maintenance zone the evening before sleep deprivation (ESD) and three more in the morning following approximately 22 h of TSD. TSD vulnerable and nonvulnerable groups were determined by a tertile split of participants based on the change in the number of behavioral lapses recorded during ESD and TSD. A subset of participants performed six additional 10-min modified auditory PVTs with exponentially distributed foreperiods during rested wakefulness (RW) and TSD to test the effect of temporal distribution on foreperiod and sequential effects.

SETTING

Sleep laboratory.

PARTICIPANTS

There were 172 young healthy participants (90 males) with regular sleep patterns. Nineteen of these participants performed the modified auditory PVT.

MEASUREMENTS AND RESULTS

Despite behavioral lapses and slower response times, sleep deprived participants could still perceive the conditional probability of temporal events and modify their level of preparation accordingly. Both foreperiod and sequential effects were magnified following sleep deprivation in vulnerable individuals. Only the foreperiod effect increased in nonvulnerable individuals.

CONCLUSIONS

The preservation of foreperiod and sequential effects suggests that implicit time perception and temporal preparedness are intact during total sleep deprivation. Individuals appear to reallocate their depleted preparatory resources to more probable event timings in ongoing trials, whereas vulnerable participants also rely more on automatic processes.

Sleepiness and Safety: Where Biology Needs Technology

Maintaining human alertness and behavioral capability under conditions of sleep loss and circadian misalignment requires fatigue management technologies due to: (1) dynamic nonlinear modulation of performance capability by the interaction of sleep homeostatic drive and circadian regulation; (2) large differences among people in neurobehavioral vulnerability to sleep loss; (3) error in subjective estimates of fatigue on performance; and (4) to inform people of the need for recovery sleep. Two promising areas of technology have emerged for managing fatigue risk in safety-sensitive occupations. The first involves preventing fatigue by optimizing work schedules using biomathematical models of performance changes associated with sleep homeostatic and circadian dynamics. Increasingly these mathematical models account for individual differences to achieve a more accurate estimate of the timing and magnitude of fatigue effects on individuals. The second area involves technologies for detecting transient fatigue from drowsiness. The Psychomotor Vigilance Test (PVT), which has been extensively validated to be sensitive to deficits in attention from sleep loss and circadian misalignment, is an example in this category. Two shorter-duration versions of the PVT recently have been developed for evaluating whether operators have sufficient behavioral alertness prior to or during work. Another example is online tracking the percent of slow eyelid closures (PERCLOS), which has been shown to reflect momentary fluctuations of vigilance. Technologies for predicting and detecting sleepiness/fatigue have the potential to predict and prevent operator errors and accidents in safety-sensitive occupations, as well as physiological and mental diseases due to inadequate sleep and circadian misalignment.

Sleepiness and Safety: Where Biology Needs Technology

Maintaining human alertness and behavioral capability under conditions of sleep loss and circadian misalignment requires fatigue management technologies due to: (1) dynamic nonlinear modulation of performance capability by the interaction of sleep homeostatic drive and circadian regulation; (2) large differences among people in neurobehavioral vulnerability to sleep loss; (3) error in subjective estimates of fatigue on performance; and (4) to inform people of the need for recovery sleep. Two promising areas of technology have emerged for managing fatigue risk in safety-sensitive occupations. The first involves preventing fatigue by optimizing work schedules using biomathematical models of performance changes associated with sleep homeostatic and circadian dynamics. Increasingly these mathematical models account for individual differences to achieve a more accurate estimate of the timing and magnitude of fatigue effects on individuals. The second area involves technologies for detecting transient fatigue from drowsiness. The Psychomotor Vigilance Test (PVT), which has been extensively validated to be sensitive to deficits in attention from sleep loss and circadian misalignment, is an example in this category. Two shorter-duration versions of the PVT recently have been developed for evaluating whether operators have sufficient behavioral alertness prior to or during work. Another example is online tracking the percent of slow eyelid closures (PERCLOS), which has been shown to reflect momentary fluctuations of vigilance. Technologies for predicting and detecting sleepiness/fatigue have the potential to predict and prevent operator errors and accidents in safety-sensitive occupations, as well as physiological and mental diseases due to inadequate sleep and circadian misalignment.

Time-on-task and sleep deprivation effects are evidenced in overlapping brain areas

Both sleep deprivation and extended task engagement (time-on-task) have been shown to degrade performance in tasks evaluating sustained attention. Here we used pulsed arterial spin labeling (pASL) to study participants engaged in a demanding selective attention task. The participants were imaged twice, once after a normal night of sleep and once after approximately 24h of total sleep deprivation. We compared task-related changes in BOLD signal alongside ASL-based cerebral blood flow (CBF) changes. We also collected resting baseline CBF data prior to and following task performance. Both BOLD fMRI and ASL identified spatially congruent task activation in ventral visual cortex and fronto-parietal regions. Sleep deprivation and time-on-task caused a decline of both measures in ventral visual cortex. BOLD fMRI also revealed such declines in fronto-parietal cortex. Only early visual cortex showed a significant upward shift in resting baseline CBF following sleep deprivation, suggesting that the neural consequences of both SD and ToT are primarily evident in task-evoked signals. We conclude that BOLD fMRI is preferable to pASL in studies evaluating sleep deprivation given its better signal to noise characteristics and the relative paucity of state differences in baseline CBF.