Motorcycling performance and sleepiness during an extended ride on a dynamic simulator: relationship with stress biomarkers

Embracing sleep-onset complexity

Sleep is crucial for many vital functions and has been extensively studied. By contrast, the sleep-onset period (SOP), often portrayed as a mere prelude to sleep, has been largely overlooked and remains poorly characterized. Recent findings, however, have reignited interest in this transitional period and have shed light on its neural mechanisms, cognitive dynamics, and clinical implications. This review synthesizes the existing knowledge about the SOP in humans. We first examine the current definition of the SOP and its limits, and consider the dynamic and complex electrophysiological changes that accompany the descent to sleep. We then describe the interplay between internal and external processing during the wake-to-sleep transition. Finally, we discuss the putative cognitive benefits of the SOP and identify novel directions to better diagnose sleep-onset disorders.

Sleepiness and the transition from wakefulness to sleep

The transition from wakefulness to sleep is a progressive process that is reflected in the gradual loss of responsiveness, an alteration of cognitive functions, and a drastic shift in brain dynamics. These changes do not occur all at once. The sleep onset period (SOP) refers here to this period of transition between wakefulness and sleep. For example, although transitions of brain activity at sleep onset can occur within seconds in a given brain region, these changes occur at different time points across the brain, resulting in a SOP that can last several minutes. Likewise, the transition to sleep impacts cognitive and behavioral levels in a graded and staged fashion. It is often accompanied and preceded by a sensation of drowsiness and the subjective feeling of a need for sleep, also associated with specific physiological and behavioral signatures. To better characterize fluctuations in vigilance and the SOP, a multidimensional approach is thus warranted. Such a multidimensional approach could mitigate important limitations in the current classification of sleep, leading ultimately to better diagnoses and treatments of individuals with sleep and/or vigilance disorders. These insights could also be translated in real-life settings to either facilitate sleep onset in individuals with sleep difficulties or, on the contrary, prevent or control inappropriate sleep onsets.

Sleep deprivation detected by voice analysis

Sleep deprivation has an ever-increasing impact on individuals and societies. Yet, to date, there is no quick and objective test for sleep deprivation. Here, we used automated acoustic analyses of the voice to detect sleep deprivation. Building on current machine-learning approaches, we focused on interpretability by introducing two novel ideas: the use of a fully generic auditory representation as input feature space, combined with an interpretation technique based on reverse correlation. The auditory representation consisted of a spectro-temporal modulation analysis derived from neurophysiology. The interpretation method aimed to reveal the regions of the auditory representation that supported the classifiers' decisions. Results showed that generic auditory features could be used to detect sleep deprivation successfully, with an accuracy comparable to state-of-the-art speech features. Furthermore, the interpretation revealed two distinct effects of sleep deprivation on the voice: changes in slow temporal modulations related to prosody and changes in spectral features related to voice quality. Importantly, the relative balance of the two effects varied widely across individuals, even though the amount of sleep deprivation was controlled, thus confirming the need to characterize sleep deprivation at the individual level. Moreover, while the prosody factor correlated with subjective sleepiness reports, the voice quality factor did not, consistent with the presence of both explicit and implicit consequences of sleep deprivation. Overall, the findings show that individual effects of sleep deprivation may be observed in vocal biomarkers. Future investigations correlating such markers with objective physiological measures of sleep deprivation could enable "sleep stethoscopes" for the cost-effective diagnosis of the individual effects of sleep deprivation.

Nationwide Analysis of Motorcycle-Associated Injuries and Fatalities in the United States: Insufficient Prevention Policies or Abandoned Laws?

BACKGROUND

Motorcycle road traffic collisions are a major cause of mortality in the United States. We aimed to analyze the temporal and statewide trends in motorcycle collision fatalities (MCFs) nationwide and their association with state laws regarding motorcycle helmet requirements, lane splitting, speeding, intoxicating driving, and red light cameras.

METHODS

A retrospective review of United States MCF/capita from 2015 to 2019 was performed using the Fatality Analysis Reporting System database. MCF/capita was defined as a motorcyclist death per 100 000 motorcyclist registrations. Independent-samples t-test and ANOVA were used to determine differences, with significance defined as P < .05. Linear regression analysis and Pearson's correlation were used to further determine associations between variables.

RESULTS

The majority of fatalities occurred in males (n = 21 354, 91.0%), ages 25-54 (n = 13 728, 58.5%), and Caucasians (n = 19 195, 81.8%). A total of 24 states and DC exhibited positive trends in MCF/capita from 2015 to 2019. There was no significant difference in MCF/capita between states who had mandatory helmet laws for all, partial requirements, and states with no law (63.4 vs 54.3 vs 33.6, P = .360). Among fatalities involving alcohol, a significantly greater number of MCF/capita were found above the legal limit of .08 compared to the group with a blood alcohol concentration of .01-.07 (17.8 vs 4.5, P < .001).

CONCLUSION

Motorcyclist fatalities continue to pose a public health risk, with 24 states showing an upward trend. Additional interventions and laws are needed to decrease the number of motorcyclist deaths. Further strategy on implementation and enforcement of helmet laws and alcohol consumption may be an essential component.

Strategies to Limit Cognitive Impairments under Sleep Restriction: Relationship to Stress Biomarkers

Adding relaxation techniques during nap or auditory stimulation of EEG slow oscillation (SO) during nighttime sleep may limit cognitive impairments in sleep-deprived subjects, potentially through alleviating stress-releasing effects. We compared daytime sleepiness, cognitive performances, and salivary stress biomarker responses in 11 volunteers (aged 18–36) who underwent 5 days of sleep restriction (SR, 3 h per night, with 30 min of daily nap) under three successive conditions: control (SR-CT), relaxation techniques added to daily nap (SR-RT), and auditory stimulation of sleep slow oscillations (SO) during nighttime sleep (SR-NS). Test evaluation was performed at baseline (BASE), the fifth day of chronic SR (SR5), and the third and fifth days after sleep recovery (REC3, REC5, respectively). At SR5, less degradation was observed for percentage of commission errors in the executive Go–noGo inhibition task in SR-RT condition compared to SR-CT, and for sleepiness score in SR-NS condition compared both to SR-CT and SR-RT. Beneficial effects of SR-RT and SR-NS were additionally observed on these two parameters and on salivary α-amylase (sAA) at REC3 and REC5. Adding relaxation techniques to naps may help performance in inhibition response, and adding nocturnal auditory stimulation of SO sleep may benefit daytime sleepiness during sleep restriction with persistent effects during recovery. The two strategies activated the autonomic nervous system, as shown by the sAA response.

Effects of Caffeine Intake on Cognitive Performance Related to Total Sleep Deprivation and Time on Task: A Randomized Cross-Over Double-Blind Study

INTRODUCTION

It is widely admitted that both total sleep deprivation (TSD) and extended task engagement (Time-On-Task, TOT) induce a cognitive fatigue state in healthy subjects. Even if EEG theta activity and adenosine both increase with cognitive fatigue, it remains unclear if these modifications are common mechanisms for both sustained attention and executive processes.

METHODS

We performed a double-blind counter-balanced (placebo (PCBO) and caffeine (CAF) - 2×2.5 mg/kg/24 h)) study on 24 healthy subjects (33.7 ± 5.9 y). Subjects participated in an experimental protocol including an habituation/training day followed by a baseline day (D0 and D1) and a total sleep deprivation (TSD) day beginning on D1 at 23:00 until D2 at 21:00. Subjects performed the psychomotor vigilance test (PVT) assessing sustained attention, followed by the executive Go-NoGo inhibition task and the 2-NBack working memory task at 09:15 on D1 and D2.

RESULTS

We showed differential contributions of TSD and TOT on deficits in sustained attention and both executive processes. An alleviating effect of caffeine intake is only observed on sustained attention deficits related to TSD and not at all on TOT effect. The caffeine dose slows down the triggering of sustained attention deficits related to TOT effect.

DISCUSSION

These results suggest that sustained attention deficits induced by TSD rely on the adenosinergic mechanism whereas TOT effect observed for both sustained attention and executive would not.

Raw scores on subjective sleepiness, fatigue, and vigor metrics consistently define resilience and vulnerability to sleep loss

STUDY OBJECTIVES

Although trait-like individual differences in subjective responses to sleep restriction (SR) and total sleep deprivation (TSD) exist, reliable characterizations remain elusive. We comprehensively compared multiple methods for defining resilience and vulnerability by subjective metrics.

METHODS

41 adults participated in a 13-day experiment:2 baseline, 5 SR, 4 recovery, and one 36h TSD night. The Karolinska Sleepiness Scale (KSS) and the Profile of Mood States Fatigue (POMS-F) and Vigor (POMS-V) were administered every 2h. Three approaches (Raw Score [average SR score], Change from Baseline [average SR minus average baseline score], and Variance [intraindividual SR score variance]), and six thresholds (±1 standard deviation, and the highest/lowest scoring 12.5%, 20%, 25%, 33%, 50%) categorized Resilient/Vulnerable groups. Kendall's tau-b correlations compared the group categorization's concordance within and between KSS, POMS-F, and POMS-V scores. Bias-corrected and accelerated bootstrapped t-tests compared group scores.

RESULTS

There were significant correlations between all approaches at all thresholds for POMS-F, between Raw Score and Change from Baseline approaches for KSS, and between Raw Score and Variance approaches for POMS-V. All Resilient groups defined by the Raw Score approach had significantly better scores throughout the study, notably including during baseline and recovery, whereas the two other approaches differed by measure, threshold, or day. Between-measure correlations varied in strength by measure, approach, or threshold.

CONCLUSION

Only the Raw Score approach consistently distinguished Resilient/Vulnerable groups at baseline, during sleep loss, and during recovery‒‒we recommend this approach as an effective method for subjective resilience/vulnerability categorization. All approaches created comparable categorizations for fatigue, some were comparable for sleepiness, and none were comparable for vigor. Fatigue and vigor captured resilience/vulnerability similarly to sleepiness but not each other.