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Mobile devices provide new opportunities to draw conclusions about cognitive performance in everyday situations. To gain insights into cognitive performance patterns in healthy adult populations, we adapted three established cognitive tests for smartphone use: the Digit Symbol Substitution Task (DSST), Sustained Attention to Response Task (SART), and Psychomotor Vigilance Task (PVT). To increase their feasibility for ambulatory assessment, we identified the minimum measurement durations that provide reliable and valid state measures of cognitive performance. Over 2 weeks, 46 participants performed each test once per day at random times, along with self-reports (e.g., on concentration, mood, and mental demands). The validity and reliability of change are promising for the 30-second PVT and 90-second DSST and SART. The DSST and SART provide fruitful outcomes for ambulatory field studies linked to mood, stress, and mental demands. We provide digital versions of the adapted DSST and SART online for free. [ABSTRACT FROM AUTHOR]

Purpose: The study aimed to assess the performance of the PVT in patients with suspected OSA, evaluate its role in population screening for OSA. Methods: The NoSAS, STOP-Bang, ESS scores and PVT tests were performed after suspected OSA patients' admission, followed by PSG. Then we compared the PVT results, calculated the sensitivity, specificity and ROC curve of PVT, and analyzed the accuracy of STOP-Bang and NoSAS questionnaire combined with PVT in predicting OSA. Results: A total of 308 patients were divided into four groups based on AHI: primary snoring (2.74 ± 1.4 events/h, n = 37); mild OSA (9.96 ± 3.25 events/h, n = 65); moderate OSA (22.41 ± 4.48 events/h, n = 76); and, severe OSA (59.42 ± 18.37 events/h, n = 130). There were significant differences in PVT lapses (p < 0.001) and reaction time (RT, p = 0.03) among the four groups. The PVT lapses and RT were positively correlated with AHI (p < 0.001) and ODI (p < 0.001), and negatively correlated with LSpO2 (p < 0.001). When diagnosing OSA (AHI ≥ 5 events/h), the AUCs of PVT, ESS, STOP-Bang, and NoSAS were 0.679, 0.579, 0.727, and 0.653, respectively; the AUCs of STOP-Bang and NoSAS combined with PVT increased. After combined PVT, the diagnostic specificity of STOP-Bang and NoSAS at nodes with AHI ≥ 5, ≥ 15 and ≥ 30 events/h increased to varying degrees. Conclusion: Patients with OSA exhibited impairment in the PVT, and the combination of the PVT and STOP-Bang or NoSAS scores can improve the diagnostic efficacy and specificity for OSA. [ABSTRACT FROM AUTHOR]

To investigate the effects of combinations of brief naps (a 90- followed by a 30-min nap vs. a 30- followed by a 90-min nap) on sleep inertia, reducing sleepiness and fatigue, and maintaining performance during night hours. This randomized, comparative, repeated-measure, cross-over study investigated subjective and cognitive performance in 12 healthy females, evaluated in three experimental nap conditions: 1) from 22:30 to 00:00 and 02:30 to 03:00 (Pre90-NAP group), 2) from 23:30 to 00:00 and 02:30 to 04:00 (Pre30-NAP) group, and 3) no naps (NO-NAP group). Participants' body temperature, psychomotor vigilance task (PVT) and Uchida-Kraepelin test (UKT) scores, and subjective feelings of drowsiness and fatigue were evaluated. Sleep state was determined by an actigraphy monitoring device worn by participants. Regardless of timing, both 90-min naps were associated with sleep inertia, and both 30-min naps with minimal sleep inertia. Reaction times were shorter and fewer errors were committed at 2 h post-nap in the Pre30-NAP and Pre90-NAP groups compared with those at the same time in the NO-NAP group. Adding a 90-min nap to a 30-min nap reduced subjective fatigue and shortened reaction times, and adding a 30-min nap to a 90-min nap was effective in maintaining performance, suggesting a synergistic effect. Taking two naps during a night work can mitigate sleepiness and fatigue, and maintain performance. A 90- followed by a 30-min nap reduced fatigue and reaction time, and a 30- followed by a 90-min nap maintained cognitive performance in the early morning. • Taking two naps during a night work can mitigate sleepiness and fatigue, and maintain performance. • A 90- followed by a 30-min nap reduces fatigue and reaction time. • A 30- followed by a 90-min nap maintains cognitive performance in the early morning. • 30-minute naps are associated with minimal sleep inertia. • 90-minute naps are associated with sleep inertia. [ABSTRACT FROM AUTHOR]

Summary: Attention is impaired in many neuropsychiatric disorders, as well as by sleep disruption, leading to decreased workplace productivity and increased risk of accidents. Thus, understanding the neural substrates is important. Here we test the hypothesis that basal forebrain neurons that contain the calcium‐binding protein parvalbumin modulate vigilant attention in mice. Furthermore, we test whether increasing the activity of basal forebrain parvalbumin neurons can rescue the deleterious effects of sleep deprivation on vigilance. A lever release version of the rodent psychomotor vigilance test was used to assess vigilant attention. Brief and continuous low‐power optogenetic excitation (1 s, 473 nm @ 5 mW) or inhibition (1 s, 530 nm @ 10 mW) of basal forebrain parvalbumin neurons was used to test the effect on attention, as measured by reaction time, under control conditions and following 8 hr of sleep deprivation by gentle handling. Optogenetic excitation of basal forebrain parvalbumin neurons that preceded the cue light signal by 0.5 s improved vigilant attention as indicated by quicker reaction times. By contrast, both sleep deprivation and optogenetic inhibition slowed reaction times. Importantly, basal forebrain parvalbumin excitation rescued the reaction time deficits in sleep‐deprived mice. Control experiments using a progressive ratio operant task confirmed that optogenetic manipulation of basal forebrain parvalbumin neurons did not alter motivation. These findings reveal for the first time a role for basal forebrain parvalbumin neurons in attention, and show that increasing their activity can compensate for disruptive effects of sleep deprivation. [ABSTRACT FROM AUTHOR]

Summary Sleep deprivation and poor sleep quality are significant societal challenges that negatively impact individuals' health. The interaction between subjective sleep quality, objective sleep measures, physical and cognitive performance, and their day‐to‐day variations remains poorly understood. Our year‐long study of 20 healthy individuals, using subcutaneous electroencephalography, aimed to elucidate these interactions, assessing data stability and participant satisfaction, usability, well‐being and adherence. In the study, 25 participants were fitted with a minimally invasive subcutaneous electroencephalography lead, with 20 completing the year of subcutaneous electroencephalography recording. Signal stability was measured using covariance of variation. Participant satisfaction, usability and well‐being were measured with questionnaires: Perceived Ease of Use questionnaire, System Usability Scale, Headache questionnaire, Major Depression Inventory, World Health Organization 5‐item Well‐Being Index, and interviews. The subcutaneous electroencephalography signals remained stable for the entire year, with an average participant adherence rate of 91%. Participants rated their satisfaction with the subcutaneous electroencephalography device as easy to use with minimal or no discomfort. The System Usability Scale score was high at 86.3 ± 10.1, and interviews highlighted that participants understood how to use the subcutaneous electroencephalography device and described a period of acclimatization to sleeping with the device. This study provides compelling evidence for the feasibility of longitudinal sleep monitoring during everyday life utilizing subcutaneous electroencephalography in healthy subjects, showcasing excellent signal stability, adherence and user experience. The amassed subcutaneous electroencephalography data constitutes the largest dataset of its kind, and is poised to significantly advance our understanding of day‐to‐day variations in normal sleep and provide key insights into subjective and objective sleep quality. [ABSTRACT FROM AUTHOR]

Vigilance refers to the capability of humans to respond accordingly to relevant and unpredictable tasks and surrounding environment changes over prolonged periods of time. Identifying vigilance decrements can, therefore, have huge and vital impacts on several operational environments in which a simple slip of mind or a deficit in attention can bear life-threatening and disastrous consequences. Several methodologies have been proposed to assess and characterize vigilance, and the results have indicated that the sole measure of performance and self-reports are not enough to obtain reliable and real-time vigilance measure. Nowadays, monitoring head and body movements to obtain information about performance in daily activities, health conditions, and mental states has become very simple and cheap due to the miniaturization of inertial measurement units and their widespread integration into common electronic devices (e.g., smart glasses, smartwatches). The present study aimed to understand the relationship between head micromovements and body posture changes to vigilance decrease while performing the psychomotor vigilance task. The results highlighted that head micromovements can be employed to track vigilance decrement during prolonged periods of time and discriminate between conditions of high or low vigilance. [ABSTRACT FROM AUTHOR]

Aims: The brain function impairment induced by sleep deprivation (SD) is temporary and can be fully reversed with sufficient sleep. However, in many cases, long‐duration recovery sleep is not feasible. Thus, this study aimed to investigate whether a short nap after SD is sufficient to restore brain function. Methods: The data of 38 subjects, including resting state functional magnetic resonance imaging data collected at three timepoints (before SD, after 30 h of SD, and after a short nap following SD) and psychomotor vigilance task (PVT) data, were collected. Dynamic functional connectivity (DFC) analysis was used to evaluate changes in brain states among three timepoints, and four DFC states were distinguished across the three timepoints. Results: Before SD, state 2 (a resting‐like FC matrix) was dominant (48.26%). However, after 30 h SD, the proportion of state 2 dramatically decreased, and state 3 (still resting‐like, but FCs were weakened) became dominant (40.92%). The increased proportion of state 3 positively correlated with a larger PVT "lapse" time. After a nap, the proportions of states 2 and 3 significantly increased and decreased, respectively, and the change in proportion of state 2 negatively correlated with the change in PVT "lapse" time. Conclusions: Taken together, the results indicated that, after a nap, the cognitive function impairment caused by SD may be reversed to some extent. Additionally, DFC differed among timepoints, which was also associated with the extent of cognitive function impairment after SD (state 3) and the extent of recovery therefrom after a nap (state 2). [ABSTRACT FROM AUTHOR]

Summary Air forces have developed several methods for reducing fatigue‐related accidents. In the Israeli Air Force, the “Dead Tired” workshop was developed with the purpose of presenting aircrew with their objective performance under sleep deprivation conditions. The aim of this study was to examine the cognitive abilities of both aircrew and unmanned aerial vehicle operators, both objectively and subjectively. All Israeli aircrew and unmanned aerial vehicle operators participated in a “Dead Tired” workshop. During the workshop, the participants performed the Psychomotor Vigilance Task, a task that tests their attention abilities, while gathering information on their subjective sleepiness in the form of a Karolinska Sleepiness Scale. Data of 366 participants (25 females), of whom 187 were unmanned aerial vehicle operators and 179 were aircrew, were obtained; and the mean age was 21.8 ± 1.2 years (range 19–26 years). A significant decline in task performance was seen following 20 hr of wakefulness in both unmanned aerial vehicle operators and aircrew (p < 0.001). Unmanned aerial vehicle operators' performance was significantly better throughout the majority of the workshop (p < 0.001). Recovery after the full‐night's sleep was seen for unmanned aerial vehicle operators, but not for aircrew (p = 0.008). A high correlation was seen between Psychomotor Vigilance Task performance and Karolinska Sleepiness Scale responses (correlation coefficient = 0.93). Sleep deprivation negatively impacted the performance of both groups of participants. Unmanned aerial vehicle operators were found to be more resilient to the effects of sleep deprivation and were quicker to recover in comparison to aircrew. [ABSTRACT FROM AUTHOR]

Objective: The intricate relationship between sleep deprivation (SD) and cognitive performance has long been a subject of research. Our study offers a novel angle by closely examining the neurobiological underpinnings of sustained attention deficits through the lens of the fronto-parietal network (FPN). Using state-of-theart imaging techniques, we delve into the changes in spontaneous brain activity after SD and explore their associations with performance on the psychomotor vigilance task (PVT). Methods: We conducted an elaborate investigation involving 64 healthy, righthanded participants who underwent resting-state functional MRI scans before and after experiencing 24  h of sleep deprivation. Employing sophisticated statistical analyses, we scrutinized the changes in fractional amplitude of low-frequency fluctuations (fALFF) through paired t-tests. Pearson correlation analyses were then applied to dissect the associations between these neurobiological shifts and behavioral outcomes in PVT. Results: The study yielded remarkable findings, revealing a dramatic decrease in fALFF values within critical areas of the FPN following SD. These alterations predominantly occurred in the frontal and parietal gyri and were inversely correlated with PVT performance metrics. Furthermore, we discovered that baseline fALFF values in the left dorsolateral prefrontal cortex (DLPFC) have the potential to serve as compelling neurobiological markers, with high discriminatory power in identifying individual responses to the adverse effects of SD on cognitive performance. Conclusion: Our groundbreaking research underscores the pivotal role that the FPN plays in modulating attention and executive function, especially under the challenging conditions brought about by sleep deprivation. The findings offer critical insights that could shape the way we understand, assess, and potentially mitigate the cognitive impacts of SD, setting the stage for future research in this riveting domain. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Objective: Intra-individual variability (IIV) in cognitive performance is thought to reflect the efficiency with which attentional resources are allocated in different circumstances requiring cognitive control. IIV in cognitive performance is associated with the strength of the negative correlation between task-positive network and default mode network (DMN) activity. In this study, we investigated the impact of sleep deprivation (SD) on functional connectivity (FC) between the DMN and psychomotor vigilance task-related network (PVT-RN), and its relationship with IIV in cognitive performance. Methods: Two analyses, network-level independent component analysis (NL-ICA) and region-level (RL)-ICA, were employed to compare the coefficient of variation (CV) of the PVT between normal sleep and SD conditions across 67 healthy participants. Results: After SD, in NL-ICA, the FC between the PVT-RN and DMN was positively correlated with the CV of the PVT, as well as the changes therein, compared with normal sleep. Using a mask derived from the DMN and PVT-RN, the RL-ICA revealed that 12 edges/connections between DMN and PVT independent components were associated with the CV of the PVT, with nine of these connections involving the precuneus. Conclusions: These findings suggest that the precuneus may play a crucial role in the interactions of various brain functions during the PVT, with the connections between the precuneus and frontoparietal and somatosensory networks being significantly altered after SD. Moreover, following SD, weakened negative FC between the precuneus and bilateral inferior parietal lobule may disrupt the balance between cognitive and executive control functions, leading to a decline in cognitive performance.

Transcranial photobiomodulation (tPBM) has been suggested as a non-invasive neuromodulation tool. The repetitive administration of light-emitting diode (LED)-based tPBM for several weeks significantly improves human cognition. To understand the electrophysiological effects of LED-tPBM on the human brain, we investigated alterations by repeated tPBM in vigilance performance and brain networks using electroencephalography (EEG) in healthy participants. Active and sham LED-based tPBM were administered to the right forehead of young participants twice a week for four weeks. The participants performed a psychomotor vigilance task (PVT) during each tPBM/sham experiment. A 64-electrode EEG system recorded electrophysiological signals from each participant during the first and last visits in a 4-week study. Topographical maps of the EEG power enhanced by tPBM were statistically compared for the repeated tPBM effect. A new data processing framework combining the group's singular value decomposition (gSVD) with eLORETA was implemented to identify EEG brain networks. The reaction time of the PVT in the tPBM-treated group was significantly improved over four weeks compared to that in the sham group. We observed acute increases in EEG delta and alpha powers during a 10 min LED-tPBM while the participants performed the PVT task. We also found that the theta, beta, and gamma EEG powers significantly increased overall after four weeks of LED-tPBM. Combining gSVD with eLORETA enabled us to identify EEG brain networks and the corresponding network power changes by repeated 4-week tPBM. This study clearly demonstrated that a 4-week prefrontal LED-tPBM can neuromodulate several key EEG networks, implying a possible causal effect between modulated brain networks and improved psychomotor vigilance outcomes. [ABSTRACT FROM AUTHOR]

Summary: Extended wakefulness, or sleep deprivation, impairs cognitive performance and brain glucose metabolism. A ketogenic diet (KD) provides an alternative fuel source, ketone bodies, that could elicit a metabolic benefit during sleep deprivation. A randomised, cross‐over trial was conducted with seven male military personnel. Participants ingested an iso‐energetic ketogenic diet or carbohydrate‐based diet for 14 days, immediately followed by 36 h of extended wakefulness and separated by a 12 day washout. Cognitive performance, mood, subjective sleepiness, capillary blood glucose, and D‐β‐hydroxybutyrate concentrations were measured every 2 h during extended wakefulness. Linear mixed models were used to analyse data. D‐β‐hydroxybutyrate was higher (p < 0.001) and glucose was lower (p < 0.01) on the KD compared with the carbohydrate‐based diet. The KD improved psychomotor vigilance task performance (number of lapses, mean reciprocal response time, mean fastest 10% response time (RT), and mean slowest 10% RT; all p < 0.05), running memory continuous performance test performance (RT and number of correct responses per minute; both p < 0.01), and vigour, fatigue, and sleepiness (all, p ≤ 0.001) compared with the carbohydrate‐based diet. In conclusion, a KD demonstrated beneficial effects on cognitive performance, mood, and sleepiness during 36 h of extended wakefulness compared with a carbohydrate‐based diet. [ABSTRACT FROM AUTHOR]

Vigilance refers to the capability of humans to respond accordingly to relevant and unpredictable tasks and surrounding environment changes over prolonged periods of time. Identifying vigilance decrements can, therefore, have huge and vital impacts on several operational environments in which a simple slip of mind or a deficit in attention can bear life-threatening and disastrous consequences. Several methodologies have been proposed to assess and characterize vigilance, and the results have indicated that the sole measure of performance and self-reports are not enough to obtain reliable and real-time vigilance measure. Nowadays, monitoring head and body movements to obtain information about performance in daily activities, health conditions, and mental states has become very simple and cheap due to the miniaturization of inertial measurement units and their widespread integration into common electronic devices (e.g., smart glasses, smartwatches). The present study aimed to understand the relationship between head micromovements and body posture changes to vigilance decrease while performing the psychomotor vigilance task. The results highlighted that head micromovements can be employed to track vigilance decrement during prolonged periods of time and discriminate between conditions of high or low vigilance.

Sleep inertia (SI) is a time period during the transition from sleep to wakefulness wherein individuals perceive low vigilance with cognitive impairments; SI is generally identified by longer reaction times (RTs) in attention tasks immediately after awakening followed by a gradual RT reduction along with waking time. The sluggish recovery of vigilance in SI involves a dynamic process of brain functions, as evidenced in recent functional magnetic resonance imaging (fMRI) studies in within-network and between-network connectivity. However, these fMRI findings were generally based on the presumption of unchanged neurovascular coupling (NVC) before and after sleep, which remains an uncertain factor to be investigated. Therefore, we recruited 12 young participants to perform a psychomotor vigilance task (PVT) and a breath-hold task of cerebrovascular reactivity (CVR) before sleep and thrice after awakening (A1, A2, and A3, with 20 min intervals in between) using simultaneous electroencephalography (EEG)-fMRI recordings. If the NVC were to hold in SI, we hypothesized that time-varying consistencies could be found between the fMRI response and EEG beta power, but not in neuron-irrelevant CVR. Results showed that the reduced accuracy and increased RT in the PVT upon awakening was consistent with the temporal patterns of the PVT-induced fMRI responses (thalamus, insula, and primary motor cortex) and the EEG beta power (Pz and CP1). The neuron-irrelevant CVR did not show the same timevarying pattern among the brain regions associated with PVT. Our findings imply that the temporal dynamics of fMRI indices upon awakening are dominated by neural activities. This is the first study to explore the temporal consistencies of neurovascular components on awakening, and the discovery provides a neurophysiological basis for further neuroimaging studies regarding SI. [ABSTRACT FROM AUTHOR]

This study aimed to enhance the real-time performance and accuracy of vigilance assessment by developing a hidden Markov model (HMM). Electrocardiogram (ECG) signals were collected and processed to remove noise and baseline drift. A group of 20 volunteers participated in the study. Their heart rate variability (HRV) was measured to train parameters of the modified hidden Markov model for a vigilance assessment. The data were collected to train the model using the Baum–Welch algorithm and to obtain the state transition probability matrix A ^ and the observation probability matrix B ^ . Finally, the data of three volunteers with different transition patterns of mental state were selected randomly and the Viterbi algorithm was used to find the optimal state, which was compared with the actual state. The constructed vigilance assessment model had a high accuracy rate, and the accuracy rate of data prediction for these three volunteers exceeded 80%. Our approach can be used in wearable products to improve their vigilance level assessment functionality or in other fields that have key positions with high concentration requirements and monotonous repetitive work. [ABSTRACT FROM AUTHOR]

Introduction: Excessive daytime sleepiness (EDS) associated with narcolepsy or obstructive sleep apnea (OSA) can impair vigilance/attention. Solriamfetol, a dopamine/norepinephrine reuptake inhibitor, is approved to treat EDS associated with narcolepsy (75–150 mg/day) or OSA (37.5–150 mg/day). The analysis reported here explored the use of the Sleep, Activity, Fatigue, and Task Effectiveness (SAFTE) model (used in transport industries to model performance based on accumulated sleep and circadian variability) as a substitute for healthy controls using psychomotor vigilance task (PVT) data collected during clinical studies. Methods: Data were analyzed from two phase 2 studies of solriamfetol in adults with OSA (NCT02806895, EudraCT 2015-003930-28) or narcolepsy (NCT02806908, EudraCT 2015-003931-36). Participants were randomly assigned 1:1 to solriamfetol 150 mg/day (3 days) followed by 300 mg/day (4 days), or placebo (7 days), then crossed over to the other treatment. Actual task effectiveness scores were calculated from average PVT inverse reaction time (pre-dose; 2 h post-dose; 6 h post-dose). Actigraphy-derived sleep intervals were used in SAFTE to determine modeled healthy control task effectiveness scores. Results: In participants with OSA (N = 31) on placebo or solriamfetol, actual and modeled healthy control task effectiveness did not differ at any time point. In participants with narcolepsy (N = 20) on placebo, actual task effectiveness at 2 h post-dose was lower than modeled healthy control task effectiveness (nominal P = 0.03), a difference not present with solriamfetol. There was no main effect of solriamfetol on actual or modeled healthy control task effectiveness across time points. Conclusion: This study represents a novel application of the SAFTE biomathematical model to approximate healthy controls in sleep disorder research and provides valuable lessons that may optimize future research. Future studies should perform a priori power analyses for model-tested outcomes and use sleep measures that capture sleep fragmentation characteristic of sleep disorders for sleep input (e.g., total sleep time rather than time in bed). Trial Registration: NCT02806895, EudraCT 2015-003930-28: A Randomized, Double-Blind, Placebo-Controlled, Crossover On-Road Driving Study Assessing the Effect of JZP-110 on Driving Performance in Subjects With Excessive Sleepiness Due to Obstructive Sleep Apnea. NCT02806908, EudraCT 2015-003931-36: A Randomized, Double-Blind, Placebo-Controlled, Crossover On-Road Driving Study Assessing the Effect of JZP-110 on Driving Performance in Subjects With Excessive Sleepiness Due to Narcolepsy. [ABSTRACT FROM AUTHOR]

Study Objective To evaluate how nocturnal timing of sleep restriction affects vigilant attention and mood in healthy controls with normal sleep–wake patterns. Methods A convenience sample from two controlled sleep restriction protocols were used to investigate the difference between 4 hours of sleep early in the night, versus 4 hours late in the night. Volunteers stayed in a hospital setting and were randomized to one of the three conditions: a control (8 hours of sleep each night), an early short sleep (ESS, 2300–0300 hours), and a late short sleep (LSS, 0300–0700 hours). Participants were evaluated with psychomotor vigilance task (PVT) and mood ratings via visual analog scales. Results Short sleep conditions led to greater performance decrements than control on PVT. LSS performance impairments were greater than control (lapses, p  = 0.011; median RT, p  = 0.029; fastest 10%, p  = 0.038; reciprocal RT, p  = 0.014; and reciprocal 10%, p  = 0.005), but had higher positive mood ratings (p  = 0.005). LSS also had higher positive mood ratings compared with ESS (p  < 0.001). Conclusions The data underscore the negative mood impact of waking at an adverse circadian phase, for healthy controls. In addition, the paradoxical relationship between mood and performance seen in LSS raises concerns that staying up late and waking at the usual rise time may be rewarding in terms of mood, but nonetheless have performance consequences that may not be fully recognized. [ABSTRACT FROM AUTHOR]

Sleep loss is common in our 24/7 society with many people routinely sleeping less than they need. Sleep debt is a term describing the difference between the amount of sleep needed, and the amount of sleep obtained. Sleep debt can accumulate over time, resulting in poor cognitive performance, increased sleepiness, poor mood, and a higher risk for accidents. Over the last 30 years, the sleep field has increasingly focused attention on recovery sleep and the ways we can recover from a sleep debt faster and more effectively. While there are still many unanswered questions and debates about the nature of recovery sleep, such as the exact components of sleep important for recovery of function, the amount of sleep needed to recover and the impacts of prior sleep history on recovery, recent research has revealed several important attributes about recovery sleep: (1) the dynamics of the recovery process is impacted by the type of sleep loss (acute versus chronic), (2) mood, sleepiness, and other aspects of cognitive performance recover at different rates, and (3) the recovery process is complex and dependent on the length of recovery sleep and the number of recovery opportunities available. This review will summarize the current state of the literature on recovery sleep, from specific studies of recovery sleep dynamics to napping, "banking" sleep and shiftwork, and will suggest the next steps for research in this field. This paper is part of the David F. Dinges Festschrift Collection. This collection is sponsored by Pulsar Informatics and the Department of Psychiatry in the Perelman School of Medicine at the University of Pennsylvania. [ABSTRACT FROM AUTHOR]

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.

Chen Wang,1,&ast; Peng Fang,2,&ast; Ya Li,1,&ast; Lin Wu,2,&ast; Tian Hu,3 Qi Yang,4 Aiping Han,5 Yingjuan Chang,1 Xing Tang,1 Xiuhua Lv,1 Ziliang Xu,1 Yongqiang Xu,1 Leilei Li,1 Minwen Zheng,1 Yuanqiang Zhu1 1Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi’an, People’s Republic of China; 2Department of Military Medical Psychology, Air Force Medical University, Xi’an, People’s Republic of China; 3Department of Radiology, Yan’an University Affiliated Hospital, Yan’an, People’s Republic of China; 4Department of Radiology, Affiliated Hospital of Shaanxi University of Traditional Chinese Medicine, Xianyang, People’s Republic of China; 5Imaging Diagnosis and Treatment Center, Xi’an International Medical Center Hospital, Xi’an, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Yuanqiang Zhu, Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi’an, 710032, People’s Republic of China, Tel/Fax +86-29-84775415, Email Zhu_YQ_fmmu@163.com Minwen Zheng, Department of Radiology, Xijing Hospital, Fourth Military Medical University, No. 127 West Changle Road, Xi’an, 710032, People’s Republic of China, Tel/Fax +86-29-84771938, Email zhengmw2007@163.comBackground: Large individual differences exist in sleep deprivation (SD) induced sustained attention deterioration. Several brain imaging studies have suggested that the activities within frontal-parietal network, cortico-thalamic connections, and inter-hemispheric connectivity might underlie the neural correlates of vulnerability/resistance to SD. However, those traditional approaches are based on average estimates of differences at the group level. Currently, a neuroimaging marker that can reliably predict this vulnerability at the individual level is lacking.Methods: Efficient transfer of information relies on the integrity of white matter (WM) tracts in the human brain, we therefore applied machine learning approach to investigate whether the WM diffusion metrics can predict vulnerability to SD. Forty-nine participants completed the psychomotor vigilance task (PVT) both after resting wakefulness (RW) and after 24 h of sleep deprivation (SD). The number of PVT lapse (reaction time > 500 ms) was calculated for both RW condition and SD condition and participants were categorized as vulnerable (24 participants) or resistant (25 participants) to SD according to the change in the number of PVT lapses between the two conditions. Diffusion tensor imaging were acquired to extract four multitype WM features at a regional level: fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity. A linear support vector machine (LSVM) learning approach using leave-one-out cross-validation (LOOCV) was performed to assess the discriminative power of WM features in SD-vulnerable and SD-resistant participants.Results: LSVM analysis achieved a correct classification rate of 83.67% (sensitivity: 87.50%; specificity: 80.00%; and area under the receiver operating characteristic curve: 0.85) for differentiating SD-vulnerable from SD-resistant participants. WM fiber tracts that contributed most to the classification model were primarily commissural pathways (superior longitudinal fasciculus), projection pathways (posterior corona radiata, anterior limb of internal capsule) and association pathways (body and genu of corpus callosum). Furthermore, we found a significantly negative correlation between changes in PVT lapses and the LSVM decision value.Conclusion: These findings suggest that WM fibers connecting (1) regions within frontal-parietal attention network, (2) the thalamus to the prefrontal cortex, and (3) the left and right hemispheres contributed the most to classification accuracy.Keywords: sleep deprivation, vulnerability, diffusion tensor imaging, machine learning, psychomotor vigilance task

Increasing time spent on the task (i.e., the time-on-task (ToT) effect) often results in mental fatigue. Typical effects of ToT are decreasing levels of task-related motivation and the deterioration of cognitive performance. However, a massive body of research indicates that the detrimental effects can be reversed by extrinsic motivators, for example, providing rewards to fatigued participants. Although several attempts have been made to identify brain areas involved in mental fatigue and related reward processing, the neural correlates are still less understood. In this study, we used the psychomotor vigilance task to induce mental fatigue and blood oxygen-level-dependent functional magnetic resonance imaging to investigate the neural correlates of the ToT effect and the reward effect (i.e., providing extra monetary reward after fatigue induction) in a healthy young sample. Our results were interpreted in a recently proposed neurocognitive framework. The activation of the right middle frontal gyrus, right insula and right anterior cingulate gyrus decreased as fatigue emerged and the cognitive performance dropped. However, after providing an extra reward, the cognitive performance, as well as activation of these areas, increased. Moreover, the activation levels of all of the mentioned areas were negatively associated with reaction times. Our results confirm that the middle frontal gyrus, insula and anterior cingulate cortex play crucial roles in cost-benefit evaluations, a potential background mechanism underlying fatigue, as suggested by the neurocognitive framework.

Objectives/background: Interest in using blood oxygen desaturations in the diagnostics of sleep apnea has risen in recent years. However, no standardized criteria for desaturation scoring exist which complicates the drawing of solid conclusions from literature.Patients/methods: We investigated how different desaturation scoring criteria affect the severity of nocturnal hypoxic load and the prediction of impaired daytime vigilance in 845 patients. Desaturations were scored based on three features: 1) minimum oxygen saturation drop during the event (2-20%, 1% interval), 2) minimum duration of the event (2-20s, 1s interval), and 3) maximum plateau duration within the event (5-60s, 5s interval), resulting in 4332 different scoring criteria. The hypoxic load was described with oxygen desaturation index (ODI), desaturation severity (DesSev), and desaturation duration (DesDur) parameters. Association between hypoxic load and impaired vigilance was investigated with covariate-adjusted area under curve (AUC) analyses by dividing patients into normal (≤5 lapses) and impaired (≥36 lapses) vigilance groups based on psychomotor vigilance task performance.Results: The severity of hypoxic load varied greatly between different scoring criteria. For example, median ODI ranged between 0.4 and 12.9 events/h, DesSev 0.01-0.23 %-point, and DesDur 0.3-9.6 %-point when the minimum transient drop criterion of 3% was used and other two features were altered. Overall, the minimum transient drop criterion had the largest effect on parameter values. All models with differently determined parameters predicted impaired vigilance moderately (AUC = 0.722-0.734).Conclusions: Desaturation scoring criteria greatly affected the severity of hypoxic load. However, the difference in the prediction of impaired vigilance between different criteria was rather small. [ABSTRACT FROM AUTHOR]

Transcranial photobiomodulation (tPBM) has been suggested as a non-invasive neuromodulation tool. The repetitive administration of light-emitting diode (LED)-based tPBM for several weeks significantly improves human cognition. To understand the electrophysiological effects of LED-tPBM on the human brain, we investigated alterations by repeated tPBM in vigilance performance and brain networks using electroencephalography (EEG) in healthy participants. Active and sham LED-based tPBM were administered to the right forehead of young participants twice a week for four weeks. The participants performed a psychomotor vigilance task (PVT) during each tPBM/sham experiment. A 64-electrode EEG system recorded electrophysiological signals from each participant during the first and last visits in a 4-week study. Topographical maps of the EEG power enhanced by tPBM were statistically compared for the repeated tPBM effect. A new data processing framework combining the group’s singular value decomposition (gSVD) with eLORETA was implemented to identify EEG brain networks. The reaction time of the PVT in the tPBM-treated group was significantly improved over four weeks compared to that in the sham group. We observed acute increases in EEG delta and alpha powers during a 10 min LED-tPBM while the participants performed the PVT task. We also found that the theta, beta, and gamma EEG powers significantly increased overall after four weeks of LED-tPBM. Combining gSVD with eLORETA enabled us to identify EEG brain networks and the corresponding network power changes by repeated 4-week tPBM. This study clearly demonstrated that a 4-week prefrontal LED-tPBM can neuromodulate several key EEG networks, implying a possible causal effect between modulated brain networks and improved psychomotor vigilance outcomes.

Attention is a basic human function underlying every other cognitive process. It is demonstrated in the functional Magnetic Resonance Imaging literature that frontoparietal networks are involved with attentive performance while default mode networks are involved with inattentive performance. Yet, it is still not clear whether similar results would be found with functional Near-Infrared Spectroscopy. The goal of our study was to investigate differences in hemodynamic activity measured by functional Near-Infrared Spectroscopy between fast and slow responses on a simple sustained attention task both before and after stimulus onset. Thirty healthy adults took part in the study. Our results have shown differences between fast and slow responses only on channels over medial frontal cortex and inferior parietal cortex (p < 0,05). These differences were observed both before and after stimulus presentation. It is discussed that functional Near-Infrared Spectroscopy is a good tool to investigate the frontoparietal network and its relationship with performance in attention tasks; it could be used to further investigate other approaches on attention, such as the dual network model of cognitive control and brain states views based on complex systems analysis; and finally, it could be used to investigate attention in naturalistic settings. [ABSTRACT FROM AUTHOR]

Objectives: This study used resting-state functional magnetic resonance imaging (rs-fMRI) scans to assess the dominant effects of 36 h total sleep deprivation (TSD) on vigilant attention and changes in the resting-state network. Materials and methods: Twenty-two healthy college students were enrolled in this study. Participants underwent two rs-fMRI scans, once in rested wakefulness (RW) and once after 36 h of TSD. We used psychomotor vigilance tasks (PVT) to measure vigilant attention. The region-of-interest to region-of-interest correlation was employed to analyze the relationship within the salience network (SN) and between other networks after 36 h of TSD. Furthermore, Pearson’s correlation analysis investigated the relationship between altered insular functional connectivity and PVT performance. Results: After 36 h of TSD, participants showed significantly decreased vigilant attention. Additionally, TSD induced decreased functional connectivity between the visual and parietal regions, whereas, a significant increase was observed between the anterior cingulate cortex and insula. Moreover, changes in functional connectivity in the anterior cingulate cortex and insula showed a significant positive correlation with the response time to PVT. Conclusion: Our results suggest that 36 h of TSD impaired vigilant visual attention, resulting in slower reaction times. The decrease in visual-parietal functional connectivity may be related to the decrease in the reception of information in the brain. Enhanced functional connectivity of the anterior cingulate cortex with the insula revealed that the brain network compensation occurs mainly in executive function. [ABSTRACT FROM AUTHOR]

Objective. Obstructive sleep apnoea (OSA) is associated with impaired vigilance. This paper examines the hypothesis that sleep spindle (Sp) characteristics during nocturnal sleep can be mapped to vigilance deficits measured by the psychomotor vigilance task (PVT) in patients with OSA. Approach. The PVT was performed prior to In-laboratory Polysomnography for 250 patients. PVT outcomes were clustered into three vigilance groups (VGs). Spindles were scored manually for a Training Cohort of 55 patients, (9491 Sps) across different blocks of NREM sleep (SBs) and validated in a Test Cohort (25 patients, 4867 Sps). We proposed a novel set of Sp features including a spindle burst index (SBI), which quantifies the burst characteristics of spindles and constructed models mapping them to VGs. We also explored the performance of conventional Sp features (such as Sp number and density) in our modelling approach. Main results. In the Training Cohort, we observed statistically significant differences in the SBI across VGs and SBs independent of OSA severity (1st stage N2 SBI; p = <0.001 across VGs). In the Test Cohort, a Model based on the proposed SBI predicted VG membership with 88% accuracy. A model based on conventional Sp features mapped to VGs with 80% accuracy, and a model using mixed burst and conventional features reached an accuracy of 88%. Significance. Spindle features measured during diagnostic In-laboratory polysomnography measurements can be mapped to PVT outcomes. The novel SBI proved useful for exploring the relationship between PVT outcomes and sleep. Further studies in larger populations are needed to verify these conclusions. [ABSTRACT FROM AUTHOR]

Study Objectives: Menopause is associated with nighttime sleep fragmentation, declining estradiol, and impaired cognition. In a model of pharmacologically induced estradiol suppression mimicking menopause, we examined the impact of menopause-pattern sleep fragmentation on daytime neurobehavioral performance and sleepiness in premenopausal women., Methods: Twenty premenopausal women completed two five-night inpatient studies in the mid-to-late follicular phase (estrogenized) and after pharmacological estradiol suppression (hypo-estrogenized). During each study, participants had an uninterrupted 8-hour sleep opportunity for two nights, followed by three nights where sleep was experimentally fragmented to mimic menopause-pattern sleep disturbance, and during which the sleep opportunity was extended to prevent shortening of the sleep duration. Neurobehavioral performance and subjective sleepiness were measured using the Psychomotor Vigilance Task and Karolinska Sleepiness Scale (KSS)., Results: Compared to unfragmented sleep, sleep fragmentation increased attentional lapses (+ 0.6 lapses, p < .05), slowed reaction time (+ 9.4 milliseconds, p < .01), and increased daytime sleepiness (+ 0.5 KSS score, p < .001). Estradiol suppression increased attentional lapses (+ 0.8; p < .001) and reaction time (+ 12.3, p < .01) but did not significantly affect daytime sleepiness. The effect of sleep fragmentation on neurobehavioral performance differed by estradiol state, such that the adverse effects of sleep fragmentation on attentional lapses (+ 0.9, trend p = .06) and reaction time (+ 15, p < .05) were observed only when estrogenized., Conclusions: Menopause-pattern sleep fragmentation and estradiol suppression worsened neurobehavioral performance and daytime sleepiness, even while sleep duration was not reduced. The adverse effects of sleep fragmentation in the context of an adequate sleep duration highlight the importance of sleep continuity as a vital aspect of good sleep health., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

This study aimed to enhance the real-time performance and accuracy of vigilance assessment by developing a hidden Markov model (HMM). Electrocardiogram (ECG) signals were collected and processed to remove noise and baseline drift. A group of 20 volunteers participated in the study. Their heart rate variability (HRV) was measured to train parameters of the modified hidden Markov model for a vigilance assessment. The data were collected to train the model using the Baum–Welch algorithm and to obtain the state transition probability matrix A^ and the observation probability matrix B^. Finally, the data of three volunteers with different transition patterns of mental state were selected randomly and the Viterbi algorithm was used to find the optimal state, which was compared with the actual state. The constructed vigilance assessment model had a high accuracy rate, and the accuracy rate of data prediction for these three volunteers exceeded 80%. Our approach can be used in wearable products to improve their vigilance level assessment functionality or in other fields that have key positions with high concentration requirements and monotonous repetitive work.

This study aimed to investigate the beneficial effects of tocotrienols (T3) supplementation on one’s attention and memory. Eleven healthy subjects were enrolled to receive placebo followed by T3 in 6 weeks. Psychomotor Vigilance Task (PVT) and Digit Span Test (DST) were used to access subjects’ sustained attention and working memory. Electroencephalogram (EEG) was used to examine the brainwave activity. T3 supplementation significantly improved the memory of the subjects in relative to the baseline as measured by average mean span for forward and reverse DST. Notably, a significant memory enhancement for T3 over placebo was observed. Subjects who consumed T3 have shown faster reaction as compared to placebo as assessed by PVT. T3 supplementation showed an overall reduction in alpha and low-beta power in comparison to placebo, indicating T3 promoted a higher neural efficacy. T3 supplementation may act as a potential nootropic in improving the mental performance and cognitive activity.

OBJECTIVES: The objective was to investigate effects of timed bright light treatment on subjective and objective measures of sleepiness during three consecutive night shifts among hospital nurses. METHODS: Thirty-five nurses were exposed to bright light (10,000 lux) and red dim light (100 lux) during three consecutive night shifts in a counter-balanced crossover trial lasting nine days, which included three days before and three days after the three night shifts. Light exposure for 30 minutes was scheduled between 02:00–03:00 hours on night 1, and thereafter delayed by one hour per night in order to delay the circadian rhythm. Subjective sleepiness was measured daily (heavy eyelids, reduced performance) and every second hour while awake (Karolinska Sleepiness Scale, KSS). Objective sleepiness (Psychomotor Vigilance Task, PVT) was measured at 05:00 hours during each night shift. Beyond nocturnal light exposure on the night shifts, no behavioral restrictions or recommendations were given at or off work. RESULTS: Bright light treatment significantly reduced heavy eyelids during night shifts. However, results on KSS and PVT were unaffected by bright light. There were no differences in subjective sleepiness during the three days following the night shifts. CONCLUSIONS: This bright light treatment protocol did not convincingly reduce sleepiness among nurses during three consecutive night shifts. Nor did bright light impede the readaptation back to a day-oriented rhythm following the night shift period. Too few consecutive night shifts, inappropriate timing of light, and possible use of other countermeasures are among the explanations for the limited effects of bright light in the present study.

Purpose: With a rapidly aging society, there is increasing interest in the health of female workers in the field of care services for older adults due to increasing demands to maintain 24-h care and to support older adults without errors or accidents. Therefore, the purpose of this cross-sectional study was to examine the association between sleep-disordered breathing (SDB) and sustained attention in women caring for older adults in Japan. Methods: The study was conducted in women aged 18–67 years old working in care service facilities for older adults in Japan. The sustained attention of participants was measured by the 10-min psychomotor vigilance task (PVT). SDB was assessed based on the respiratory disturbance index (RDI), which was measured using an ambulatory airflow monitor with a polyvinylidene fluoride (PVDF) film sensor to monitor the respiratory airflow of nasal and oral breathing. The participants wore the monitor to record the breathing status while asleep at home. The severity of SDB was categorized as follows: normal, RDI < 5 events/h; mild SDB, RDI 5–10 events/h; and moderate-to-severe SDB, RDI ≥ 10 events/h. Results: Of 688 women enrolled, medians of age, body mass index (BMI), sleep duration, and prevalence of hypertension tended to be higher with increasing RDI. No significant association was found between RDI and PVT parameters. However, when we limited the analysis to women with BMI ≥ 22 kg/m2, those with moderate-to-severe SDB had significantly higher odds of having the slowest 10% reaction times compared to those without SDB (OR = 2.03; 95% CI = 1.17–3.53). The association did not decrease after adjusting to account for sleep duration, alcohol drinking habits, and history of hypertension (OR = 1.97; 95% CI = 1.10–3.52). A significant increasing trend was also found between RDI and the slowest 10% of reaction times (p for trend = 0.03). Conclusions: Our findings suggest that SDB is associated with reduced sustained attention in participants with BMI ≥ 22 kg/m2, although the number of assessments of SDB and PVT was only once per participant due to the nature of the cross-sectional study. [ABSTRACT FROM AUTHOR]

Nap deprivation is regarded as a sleep loss for habitual nappers. The beneficial effects of napping and moderate-intensity aerobic exercise on the reduction in planning ability following nighttime sleep deprivation have been proven. However, it is still unknown whether it can improve the performance decline caused by daytime nap deprivation in habitual nappers. Seventy-four healthy adults who had a long-term habit of taking naps were assigned to three interventions after receiving nap deprivation: (1) Control group (no intervention); (2) Nap group (15-min sitting naps); (3) Exercise group (15-min aerobic exercise), in which subjective alertness, mood, fatigue, and task performance in objective alertness (Psychomotor Vigilance Task, PVT) and planning ability (the Tower of London Task) were measured. Results showed that nap deprivation negatively influenced some performance on the psychomotor vigilance (i.e., response times and 10% slowest response time) and planning ability (i.e., planning time). And acute moderate-intensity aerobic exercise improved psychomotor alertness (i.e., response times) and planning ability (i.e., execution accuracy, execution time), a 15-min sitting naps only alleviated subjective fatigue, whereas some performance (i.e., response times) deteriorated when no intervention was used. These findings suggested that acute moderate-intensity aerobic exercise has a better restorative effect on the reduced planning ability and objective alertness due to nap deprivation compared to sitting naps.

Summary: We investigated the association of the number of eating occasions and energy intake with alertness and gastrointestinal (GI) complaints in nurses during their night shift. During this observational study we collected data on anthropometrics and demographics, eating frequency, energy intake, alertness and GI complaints in 118 healthy female nurses, aged 20 to 61 years. Nurses completed an alertness test (psychomotor vigilance task) during the night shift and a 24‐hr dietary recall and a questionnaire about GI complaints after the night shift. This was repeated three times, always on the first night shift in a night shift series. The number of eating occasions during the night shift was negatively associated with reaction times (β = −4.81 ms, 95% confidence interval [CI] −9.14 to −0.48; p =.030), and number of lapses (β = −0.04, 95% CI −0.07 to −0.00; p =.030). However, the number of eating occasions was not associated with subjective alertness and GI complaints. Energy intake during the night shift was not associated with objective or subjective alertness or with GI complaints. These associations were independent of caffeine intake, age, body mass index and dependence among the repeated measurements. The present study showed that eating frequency was positively associated with objectively measured alertness levels in female nurses during the night shift. The results need to be confirmed in an intervention study, where also timing, size and composition of the meal will be taken into account. In practice, optimising nutritional guidelines on these aspects could lead to faster responses, less (medical) errors, and a better wellbeing of night shift workers. [ABSTRACT FROM AUTHOR]

Firefighters are at risk for chronic sleep disruption due to their rotating 24-hour on and 48-hour off work schedule and hazardous work conditions. Forty-five firefighters were assessed to determine the impact of their shift schedule on sleep duration, sleep quality, processing speed, sustained attention, vigilance, and mental health. Assessments were conducted at the start and end of shift. Firefighters endorsed sleeping 5 hours 21 minutes at work, and the results suggest that even minimal sleep disruption affected cognitive functioning (e.g. processing speed, visual-motor coordination, and reaction time), increasing the likelihood of poor work performance or injury. [ABSTRACT FROM AUTHOR]

Fatigue and sleepiness are two major factors that have been reported to contribute to road crash and accidents in Indonesia. Fatigue among commercial drivers is probably a common phenomenon, particularly during long-duration driving. This study aimed at characterizing fatigue and sleepiness during long-duration driving. Nine commercial drivers were recruited in this field study and were requested to drive a multi-purpose vehicle for three trips back and forth between two major cities. Each trip was completed within 4 hours, with about 3 to 3.5 hours of continuous driving (and 0.5 to 1 hour of rest). Fatigue was assessed by utilizing the Psychomotor Vigilance Task (PVT), which was administered for 5 minutes immediately following the completion of each trip. A video camera was employed to capture blink frequency, and for each trip, this measure was determined during 5 minutes after two hours of driving. Subjective ratings were also collected during the task and included the Swedish Occupational Fatigue Inventory (SOFI)and the Karolinska Sleepiness Scale (KSS). The results of this study demonstrated a consistent increase in the blink rate and subjective measures of fatigue. A significant association was also found between the blink rate and SOFI measures, indicating an association between thoseobjective and subjective measures. Although not statistically significant, there were also changes in PVT parameters associated with driving duration. However,no significant association was found between PVT parameters and the subjective measures. This study found that a minimum of six hours of intermittent driving was adequate in inducing fatigueand sleepiness, despite the seemingly sufficient amount of rest break. Based on the findings of this study, it is suggested that long-duration driving be limited to a maximum of 12 hours, and that a minimum of 30 minutesof rest be provided after 3 to 4 hours of driving. This finding should be used as a basis for scheduling drivers and for finding the appropriate intervention strategyformitigating fatigue and sleepiness risks during prolonged driving tasks.

It is commonly believed that alertness and attention decrease after sleep deprivation (SD). However, there are not enough studies on the changes in psychomotor vigilance testing (PVT) during SD and the corresponding changes in brain function and brain structure after SD. Therefore, we recruited 30 healthy adult men to perform a 36 h acute SD experiment, including the measurement of five indicators of PVT every 2 h, and analysis of cerebral blood flow (CBF) and grey matter volume (GMV) changes, before and after SD by magnetic resonance imaging (MRI). The PVT measurement found that the mean reaction time (RT), fastest 10% RT, minor lapses, and false starts all increased progressively within 20 h of SD, except for major lapses. Subsequently, all indexes showed a significant lengthening or increasing trend, and the peak value was in the range of 24 h-32 h and decreased at 36 h, in which the number of major lapses returned to normal. MRI showed that CBF decreased in the left orbital part of the superior frontal gyrus, the left of the rolandic operculum, the left triangular part, and the right opercular part of the inferior frontal gyrus, and CBF increased in the left lingual gyrus and the right superior gyrus after 36 h SD. The left lingual gyrus was negatively correlated with the major lapses, and both the inferior frontal gyrus and the superior frontal gyrus were positively correlated with the false starts. Still, there was no significant change in GMV. Therefore, we believe that 36 h of acute SD causes alterations in brain function and reduces alert attention, whereas short-term acute SD does not cause changes in brain structure.

Study Objectives: We previously reported that during a 45-day simulated space mission, a dynamic lighting schedule (DLS) improved circadian phase alignment and performance assessed once on selected days. This study aimed to evaluate how DLS affected performance on a 5-minute psychomotor vigilance task (PVT) administered multiple times per day on selected days., Methods: Sixteen crewmembers (37.4 ± 6.7 years; 5F) underwent six cycles of 2 × 8-hour/night followed by 5 × 5-hour/night sleep opportunities. During the DLS ( n  = 8), daytime white light exposure was blue-enriched (~6000 K; Level 1: 1079, Level 2: 76 melanopic equivalent daytime illuminance (melEDI) lux) and blue-depleted (~3000-4000 K; L1: 21, L2: 2 melEDI lux) 3 hours before bed. In the standard lighting schedule (SLS; n  = 8), lighting remained constant (~4500K; L1: 284, L2 62 melEDI lux). Effects of lighting condition (DLS/SLS), sleep condition (5/8 hours), time into mission, and their interactions, and time awake on PVT performance were analyzed using generalized linear mixed models., Results: The DLS was associated with fewer attentional lapses (reaction time [RT] > 500 milliseconds) compared to SLS. Lapses, mean RT, and 10% fastest/slowest RTs were worse following 5 compared to 8 hours of sleep but not between lighting conditions. There was an effect of time into mission on RTs, likely due to sleep loss. Overall performance differed by time of day, with longer RTs at the beginning and end of the day. There were more lapses and slower RTs in the afternoon in the SLS compared to the DLS condition., Conclusions: Future missions should incorporate DLS to enhance circadian alignment and performance. This paper is part of the Sleep and Circadian Rhythms: Management of Fatigue in Occupational Settings Collection., (© The Author(s) 2024. Published by Oxford University Press on behalf of Sleep Research Society.)

Sleep deprivation (SD) has become very common in contemporary society, where people work around the clock. SD-induced cognitive deficits show large inter-individual differences and are trait-like with known neural correlates. However, few studies have used neuroimaging to predict vulnerability to SD. Here, resting state functional magnetic resonance imaging (fMRI) data and psychomotor vigilance task (PVT) data were collected from 60 healthy subjects after resting wakefulness and after one night of SD. The number of PVT lapses was then used to classify participants on the basis of whether they were vulnerable or resilient to SD. We explored the viability of graph-theory-based degree centrality to accurately classify vulnerability to SD. Compared with during resting wakefulness, widespread changes in degree centrality (DC) were found after SD, indicating significant reorganization of sleep homeostasis with respect to activity in resting state brain network architecture. Support vector machine (SVM) analysis using leave-one-out cross-validation achieved a correct classification rate of 84.75% [sensitivity 82.76%, specificity 86.67%, and area under the receiver operating characteristic curve (AUC) 0.94] for differentiating vulnerable subjects from resilient subjects. Brain areas that contributed most to the classification model were mainly located within the sensorimotor network, default mode network, and thalamus. Furthermore, we found a significantly negative correlation between changes in PVT lapses and DC in the thalamus after SD. These findings suggest that resting-state network measures combined with a machine learning algorithm could have broad potential applications in screening vulnerability to SD.

Sleep deprivation (SD) has become very common in contemporary society, where people work around the clock. SD-induced cognitive deficits show large inter-individual differences and are trait-like with known neural correlates. However, few studies have used neuroimaging to predict vulnerability to SD. Here, resting state functional magnetic resonance imaging (fMRI) data and psychomotor vigilance task (PVT) data were collected from 60 healthy subjects after resting wakefulness and after one night of SD. The number of PVT lapses was then used to classify participants on the basis of whether they were vulnerable or resilient to SD. We explored the viability of graph-theory-based degree centrality to accurately classify vulnerability to SD. Compared with during resting wakefulness, widespread changes in degree centrality (DC) were found after SD, indicating significant reorganization of sleep homeostasis with respect to activity in resting state brain network architecture. Support vector machine (SVM) analysis using leave-one-out cross-validation achieved a correct classification rate of 84.75% [sensitivity 82.76%, specificity 86.67%, and area under the receiver operating characteristic curve (AUC) 0.94] for differentiating vulnerable subjects from resilient subjects. Brain areas that contributed most to the classification model were mainly located within the sensorimotor network, default mode network, and thalamus. Furthermore, we found a significantly negative correlation between changes in PVT lapses and DC in the thalamus after SD. These findings suggest that resting-state network measures combined with a machine learning algorithm could have broad potential applications in screening vulnerability to SD. [ABSTRACT FROM AUTHOR]

This article tackles the issue of correct data interpretation when using stimulus detection tasks for determining the operator’s workload.Stimulus detection tasks are a relative simple and inexpensive means of measuring the operator’s state. While stimulus detection tasks may be better geared to measure conditions of high workload, adopting this approach for the assessment of low workload may be more problematic.This mini-review details the use of common stimulus detection tasks and their contributions to the Human Factors practice. It also borrows from the conceptual framework of the inverted-U shape model to discuss the issue of data interpretation.The evidence being discussed here highlights a clear limitation of stimulus detection task paradigms.There is an inherent risk in using a unidimensional tool like stimulus detection tasks as the primary source of information for determining the operator’s psychophysiological state.Two recommendations are put forward to Human Factors researchers and practitioners dealing with the interpretation conundrum of dealing with stimulus detection tasks. [ABSTRACT FROM AUTHOR]

Objectives The objective was to investigate effects of timed bright light treatment on subjective and objective measures of sleepiness during three consecutive night shifts among hospital nurses. Methods Thirty-five nurses were exposed to bright light (10,000 lux) and red dim light (100 lux) during three consecutive night shifts in a counter-balanced crossover trial lasting nine days, which included three days before and three days after the three night shifts. Light exposure for 30 minutes was scheduled between 02:00-03:00 hours on night 1, and thereafter delayed by one hour per night in order to delay the circadian rhythm. Subjective sleepiness was measured daily (heavy eyelids, reduced performance) and every second hour while awake (Karolinska Sleepiness Scale, KSS). Objective sleepiness (Psychomotor Vigilance Task, PVT) was measured at 05:00 hours during each night shift. Beyond nocturnal light exposure on the night shifts, no behavioral restrictions or recommendations were given at or off work. Results Bright light treatment significantly reduced heavy eyelids during night shifts. However, results on KSS and PVT were unaffected by bright light. There were no differences in subjective sleepiness during the three days following the night shifts. Conclusions This bright light treatment protocol did not convincingly reduce sleepiness among nurses during three consecutive night shifts. Nor did bright light impede the readaptation back to a day-oriented rhythm following the night shift period. Too few consecutive night shifts, inappropriate timing of light, and possible use of other countermeasures are among the explanations for the limited effects of bright light in the present study. [ABSTRACT FROM AUTHOR]

Purpose: To clarify the subjective and objective impacts of a change in a 12-h shift schedule, involving a reduction in the number of crews, on workers at an electronic parts production company. Methods: Forty-two workers participated in this study. Subjective indicators (e.g. questionnaires) and objective indicators [e.g., psychomotor vigilance task (PVT)], as well as an activity monitor-based sleep assessment, were measured during a > 1-year period that encompassed the shift schedule change. The study outcome was a comparison of work-related injury rates measured 1 year before and after the change in shift schedule. Results: After the shift schedule change, questionnaire scores regarding work-related burdens and PVT performance parameters, including mean response time and number of lapses, increased significantly. However, we also observed divergences in the trends of the subjective and objective measures 1 year after the change. Despite these variations in both types of measures, we observed no significant differences in work-related injury rates measured before and after the shift schedule change. Conclusion: This study revealed that a reduction in the number of crews in a 12-h shift schedule has a negative impact on the subjective and objective indicator after the change in shift schedule; only indicators of alertness did not recover at 1 year after the change. Assessments of the workers' performances and the regular implementation of health and safety programs for more than 1 year are needed to maintain workers' health after the change in shift schedule. [ABSTRACT FROM AUTHOR]

Anesthesiologists in Egypt as a representative of developing countries with large populations and shortage of trained personnel and extended working hours that may reach 30 continuous hours are susceptible victims of fatigue and sleep deprivation. To evaluate and compare differences in cognitive function of anesthesia residents before and after the 24 hours work shift. Prospective, observational, cohort study that was conducted in tertiary care hospital (Kasr El-Aini Hospital, Faculty of Medicine, Cairo University). Fifty anesthesia residents with 24 hours working shift participated in the study. The cognitive function was assessed before and after the shift using Psychomotor Vigilance Task, Karolinska Sleepiness Scale, Epworth Sleepiness Scale and Trail Making Test before and after the shift. Psychomotor Vigilance Task mean reaction time before and after shift was 302.1 ± 35.2 ms and 371.9 ± 55.4 ms, respectively (P value < 0.001). Karolinska Sleepiness Scale mean before and after shift was 3.34 ± 1.189 and 6.24 ± 1.589, respectively (P value < 0.001). Epworth Sleepiness Scale mean before and after shift was 6.68 ± 2.759 and 14.86 ± 3.423, respectively (P value < 0.001). Trail Making Test mean times in both parts A and B, before shifts were 38.82 ± 8.458 and 63.16 ± 11.557 s, respectively. While, post shifts mean times were 44.86 ± 9.370 and 72.60 ± 12.294 s, respectively (P value < 0.001 for both parts). Sleep deprivation in night shifts increases the day-time sleepiness and affects the anesthesiologist' cognitive processes, such as reaction time, alertness, rapid problem solving, psychomotor skills, attention, mental flexibility, and executive functions. clinicaltrials.gov: NCT03784560. [ABSTRACT FROM AUTHOR]

Background Does the inclusion of a randomized inter-trial interval (ITI) impact performance on an Attentional Blink (AB) task? The AB phenomenon is often used as a test of transient attention (Dux & Marois, 2009); however, it is unclear whether incorporating aspects of sustained attention, by implementing a randomized ITI, would impact task performance. The current research sought to investigate this, by contrasting a standard version of the AB task with a random ITI version to determine whether performance changed, reflecting a change in difficulty, engagement, or motivation. Method Thirty university students (21 female; age range 18–57, Mage= 21.5, SD = 7.4) completed both versions of the task, in counterbalanced order. Results No significant difference in performance was found between the standard AB task and the AB task with the random ITI. Bayesian analyses suggested moderate evidence for the null. Conclusion Temporal unpredictability did not appear to impact task performance. This suggests that the standard AB task has cognitive properties with regards to task difficulty, engagement, and motivation, that are inherently similar to tasks that employ a randomized ITI to measure sustained attention (e.g., the Psychomotor Vigilance Task; PVT; Dinges & Powell, 1985). This finding provides important support for future research which may seek to obtain a more detailed understanding of attention through the comparison of performance on transient and sustained attention tasks.