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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]

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]

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]

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,* Peng Fang,2,* Ya Li,1,* Lin Wu,2,* 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*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.

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.

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]

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.

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.

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]

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.

Work related accident is a problem that needs to be considered seriously in Indonesia. The number of occupational accidents is increasing significantly from 96,314 in 2009 to 110,285 in 2015. The mortality rate in these cases is very high. This research aims to develop a daily fitness for duty index as a measurement to ensure that workers are able to work effectively and safely. Systematic literature review had been carried out through several stages, i.e. 1) determination of searching strategy, and searching process, 2) determination of searching criteria, 3) quality control for literature, and 4) conclusion. The experiment involved four participants. They divided into two groups: night shift workers and morning shift workers. Total sleep time, heart rate at rest, reaction time, and body weight were recorded during the experiment. The daily fitness for duty index has been developed that consider sleep sufficiency factor, circadian cycle misalignment factor, and individual factor. The daily fitness for duty index has a strong correlation with subjective work readiness measurement. Therefore, it can be concluded that the daily fitness for duty index is trustworthy to measure fitness for duty.

It is unclear if the response to positive airway pressure (PAP) treatment is different between African American (AA) and European Americans (EA). We examined whether race modifies the effects of PAP on sleep and daytime function. We assessed Epworth Sleepiness Scale (ESS), Functional Outcomes of Sleep Questionnaire, Psychomotor Vigilance Task and actigraphy in 185 participants with moderate-to-severe obstructive sleep apnea before and 3–4 months after PAP treatment. The participants were middle-aged (mean, 55.1 years), 83.8% men and 60.5% AA. Linear regression models were used to examine the effect of race on outcomes. The AA had smaller reductions in ESS (mean change (95% confidence interval, CI) AA, −2.30 [−3.35, −1.25] vs. EA, −4.16 [−5.48, −2.84] and frequency of awakenings (AA, −0.73 [−4.92, 3.47] vs. EA, −9.35 [−15.20, −3.51]). A race × PAP usage interaction term was added to the model to examine if the change in outcomes per 1 h increase in PAP usage differed by race. AA exhibited greater improvement in wake after sleep onset (β (95% CI) AA, −8.89 [−16.40, −1.37] vs. EA, 2.49 [−4.15, 9.12]) and frequency of awakening (β (95% CI) AA, −2.59 [−4.44, −0.75] vs. EA, 1.71 [−1.08, 4.50]). The results indicate the importance of race in evaluating outcomes following PAP treatment.

Pilot fatigue is a critical reason for aviation accidents related to human errors. Human-related accidents might be reduced if the pilots’ eye movement measures can be leveraged to predict fatigue. Eye tracking can be a non-intrusive viable approach that does not require the pilots to pause their current task, and the device does not need to be in direct contact with the pilots. In this study, the positive or negative correlations among the psychomotor vigilance test (PVT) measures (i.e., reaction times, number of false alarms, and number of lapses) and eye movement measures (i.e., pupil size, eye fixation number, eye fixation duration, visual entropy) were investigated. Then, fatigue predictive models were developed to predict fatigue using eye movement measures identified through forward and backward stepwise regressions. The proposed approach was implemented in a simulated short-haul multiphase flight mission involving novice and expert pilots. The results showed that the correlations among the measures were different based on expertise (i.e., novices vs. experts); thus, two predictive models were developed accordingly. In addition, the results from the regressions showed that either a single or a subset of the eye movement measures might be sufficient to predict fatigue. The results show the promise of using non-intrusive eye movements as an indicator for fatigue prediction and provides a foundation that can lead us closer to developing a near real-time warning system to prevent critical accidents.

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 multipurpose 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 those objective 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 fatigue and 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 minutes of 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 strategy for mitigating fatigue and sleepiness risks during prolonged driving tasks. [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,MageD21.5, SDD7:4) 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. [ABSTRACT FROM AUTHOR]

Aims: THN102 is a novel combination of modafinil and low‐dose flecainide, targeting glial connexin activity to modulate modafinil effects. We investigated THN102 efficacy compared to modafinil and to placebo on vigilance and cognitive function during 40‐hour total sleep deprivation (TSD). Methods: Twenty healthy men participated in a double‐blind, randomized, incomplete‐block 3‐period cross‐over trial with 5 treatments (n = 12 per group): placebo (PBO), modafinil 100 mg (MOD100), THN102 100/1, 100/3, 100/9 (modafinil 100 mg and flecainide 1, 3 or 9 mg). Each period included a baseline day and a TSD day with treatments administered 3 times (01:00, 09:00 and 19:00). Reaction time in psychomotor vigilance test, subjective somnolence and vital signs were assessed before and during treatment. Working memory (2‐Back) and executive processes (Go/noGo for vigilance and inhibition, Wisconsin card sorting task for mental flexibility, and Tower of London test for planning) were evaluated at 16:30. Results: At 5 hours postdose−1 (after 23 hours TSD, primary endpoint), THN102 100/1 resulted in statistically higher psychomotor vigilance test speed vs MOD100 (3.97 ± 0.09 vs 3.74 ± 0.14, P <.05). No increase in effect was observed with higher flecainide doses in combinations. Most THN102 doses vs MOD100 also improved the number of correct responses in 2‐Back and Go errors in Go/noGo (P <.05 for all doses), and perseverative responses in Wisconsin card sorting task (for 100/1 and 100/9). No impact on cardiac conduction was noted with THN102, and safety was similar to MOD100. Conclusions: THN102 seems more efficient than modafinil on vigilance, working memory and executive functions, opening new perspectives in management of hypersomnolence disorders. [ABSTRACT FROM AUTHOR]

This study evaluated the time-on-task effect of a sustained attention task on the accommodative response, explored the link between ocular accommodation, cardiac autonomic regulation and behavioral performance, and tested the inter-session repeatability of these results by performing the same experimental procedure on different days. The accommodative response was measured in 25 university students using a WAM-5500 autorefractor, while participants performed a 10-minute psychomotor vigilance task at 50 cm. There were no time-on-task effects for the lag of accommodation, whereas the microfluctuations of accommodation and reaction time were modulated as a function of time-on-task, observing a progressive increment of both variables over time. Multiple regression analysis revealed that the microfluctuations of accommodation were a reasonably good predictor of behavioral performance. Analysis of inter-session repeatability showed that ocular accommodation, heart rate variability and reaction time had a low to moderate level of repeatability between two measurements. The microfluctuations of accommodation were sensitive to time-on-task effects during sustained attention, with a lower stability of accommodation being linked to reduced behavioral performance. The predictive capacity of the variability of accommodation for behavioral performance might be explained by the brain mechanisms shared by the ocular dynamics and attentional state; however, future studies would be required to elucidate this association. The low to moderate inter-session repeatability indicated that results in two measurement periods cannot be considered interchangeable, and therefore, the results of this study should be interpreted cautiously in this regard. [ABSTRACT FROM AUTHOR]

• Precuneus may play a crucial role in the interactions of various brain functions. • Sleep deprivation will weaken negative precuneus-related functional connectivity. • Weakened precuneus-related function may lead to a decline in cognitive performance. 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. 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. 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. 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. [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-the-art 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, right-handed 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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Yao, Wang, Gao, Gao and Guo.)

The combat naval vessels require continuous operational preparedness for guarding the vast coastline. Sailors onboard these ships are at risk for sleep deprivation. Sailors may be vulnerable to chronic fatigue; and decreased performance, vigilance, and cognitive functioning owing to sleep debt, which may affect safety during tactical operations and while transportation of ships. In this study we assessed the work-rest pattern and level of alertness during sailing and non sailing days. Thirty-two male participants maintained a 24-h sleep and activity log for 5 days. Furthermore, qualitative gross motor activity was recorded using an actiwatch during these 5 days. Participants also completed four test sessions of personal digital assistant (PDA) based psychomotor vigilance task (PVT) test: pre-sleep, post-sleep, pre-work, and post-work. A comparison of data was performed using the Wilcoxon signed-rank test. Sailors received approximately 1 h less of rest while sailing. There was a significant difference in bedtime, wake-up time, total sleep time, sleep onset latency (SOL), wake up after sleep onset (WASO), and the number of awakenings during the non-sailing and the sailing days. PVT data showed significantly higher reaction times during the sailing days on pre-work and post-sleep sessions. Our study shows that although the sailors are not getting sufficient restorative sleep while sailing as compared to non-sailing days, this is not affecting their cognitive functioning while working. [ABSTRACT FROM AUTHOR]

Vigilance degradation usually causes significant performance decrement. It is also considered the major factor causing the out-of-the-loop phenomenon (OOTL) occurrence. OOTL is strongly related to a high level of automation in operative contexts such as the Air Traffic Management (ATM), and it could lead to a negative impact on the Air Traffic Controllers’ (ATCOs) engagement. As a consequence, being able to monitor the ATCOs’ vigilance would be very important to prevent risky situations. In this context, the present study aimed to characterise and assess the vigilance level by using electroencephalographic (EEG) measures. The first study, involving 13 participants in laboratory settings allowed to find out the neurophysiological features mostly related to vigilance decrements. Those results were also confirmed under realistic ATM settings recruiting 10 professional ATCOs. The results demonstrated that (i) there was a significant performance decrement related to vigilance reduction; (ii) there were no substantial differences between the identified neurophysiological features in controlled and ecological settings, and the EEG-channel configuration defined in laboratory was able to discriminate and classify vigilance changes in ATCOs’ vigilance with high accuracy (up to 84%); (iii) the derived two EEG-channel configuration was able to assess vigilance variations reporting only slight accuracy reduction.

Aim: High altitude (HA) hypoxia may affect cognitive performance and sleep quality. Further, vigilance is reduced following sleep deprivation. We investigated the effect on vigilance, actigraphic sleep indices, and their relationships with acute mountain sickness (AMS) during very HA exposure, acclimatization, and re-exposure.Methods: A total of 21 healthy altitude-naive individuals (25 ± 4 years; 13 females) completed 2 cycles of altitude exposure separated by 7 days at low altitude (LA, 520 m). Participants slept at 2900 m and spent the day at HA, (5050 m). We report acute altitude exposure on Day 1 (LA vs. HA1) and after 6 days of acclimatization (HA1 vs. HA6). Vigilance was quantified by reaction speed in the 10-min psychomotor vigilance test reaction speed (PVT-RS). AMS was evaluated using the Environmental Symptoms Questionnaire Cerebral Score (AMS-C score). Nocturnal rest/activity was recorded to estimate sleep duration using actigraphy.Results: In Cycle 1, PVT-RS was slower at HA1 compared to LA (4.1 ± 0.8 vs. 4.5 ± 0.6 s-1, respectively, p = 0.029), but not at HA6 (4.6 ± 0.7; p > 0.05). In Cycle 2, PVT-RS at HA1 (4.6 ± 0.7) and HA6 (4.8 ± 0.6) were not different from LA (4.8 ± 0.6, p > 0.05) and significantly greater than corresponding values in Cycle 1. In both cycles, AMS scores were higher at HA1 than at LA and HA6 (p < 0.05). Estimated sleep durations (TST) at LA, 1st and 5th nights were 431.3 ± 28.7, 418.1 ± 48.6, and 379.7 ± 51.4 min, respectively, in Cycle 1 and they were significantly reduced during acclimatization exposures (LA vs. 1st night, p > 0.05; LA vs. 5th night, p = 0.012; and 1st vs. 5th night, p = 0.054). LA, 1st and 5th nights TST in Cycle 2 were 477.5 ± 96.9, 430.9 ± 34, and 341.4 ± 32.2, respectively, and we observed similar deteriorations in TST as in Cycle 1 (LA vs. 1st night, p > 0.05; LA vs. 5th night, p = 0.001; and 1st vs. 5th night, p < 0.0001). At HA1, subjects who reported higher AMS-C scores exhibited slower PVT-RS (r = -0.56; p < 0.01). Subjects with higher AMS-C scores took longer time to react to the stimuli during acute exposure (r = 0.62, p < 0.01) during HA1 of Cycle 1.Conclusion: Acute exposure to HA reduces the PVT-RS. Altitude acclimatization over 6 days recovers the reaction speed and prevents impairments during subsequent altitude re-exposure after 1 week spent near sea level. However, acclimatization does not lead to improvement in total sleep time during acute and subacute exposures.