Key points Inadequate sleep and irregular work schedules have not only adverse consequences for individual health and well‐being, but also enormous economic and safety implications for society as a whole.This study demonstrates that visual motion processing and coordinated eye movements are significantly impaired when performed after sleep loss and during the biological night, and thus may be contributing to human error and accidents.Because affected individuals are often unaware of their sensorimotor and cognitive deficits, there is a critical need for non‐invasive, objective indicators of mild, yet potentially unsafe, impairment due to disrupted sleep or biological rhythms.Our findings show that a set of eye‐movement measures can be used to provide sensitive and reliable indicators of such mild neural impairments. AbstractSleep loss and circadian misalignment have long been known to impair human cognitive and motor performance with significant societal and health consequences. It is well known that human reaction time to a visual cue is impaired following sleep loss and circadian misalignment, but it has remained unclear how more complex visuomotor control behaviour is altered under these conditions. In this study, we measured 14 parameters of the voluntary ocular tracking response of 12 human participants (six females) to systematically examine the effects of sleep loss and circadian misalignment using a constant routine 24‐h acute sleep‐deprivation paradigm. The combination of state‐of‐the‐art oculometric and sleep‐research methodologies allowed us to document, for the first time, large changes in many components of pursuit, saccades and visual motion processing as a function of time awake and circadian phase. Further, we observed a pattern of impairment across our set of oculometric measures that is qualitatively different from that observed previously with other mild neural impairments. We conclude that dynamic vision and visuomotor control exhibit a distinct pattern of impairment linked with time awake and circadian phase. Therefore, a sufficiently broad set of oculometric measures could provide a sensitive and specific behavioural biomarker of acute sleep loss and circadian misalignment. We foresee potential applications of such oculometric biomarkers assisting in the assessment of readiness‐to‐perform higher risk tasks and in the characterization of sub‐clinical neural impairment in the face of a multiplicity of potential risk factors, including disrupted sleep and circadian rhythms.

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The current study demonstrates the dose-dependent impairment in oculomotor and ocular behaviours across a range of ultra-low BACs (<0.035%). r Processing of target speed and direction, as well as pursuit eye movements, are significantly impaired at 0.015% BAC, suggesting impaired neural activity within brain regions associated with the visual processing of motion. r Catch-up saccades during steady visual tracking of the moving target compensate for the reduced vigour of smooth eye movements that occurs with the ingestion of low-dose alcohol. r Saccade dynamics start to become 'sluggish' at as low as 0.035% BAC. r Pupillary light responses appear unaffected at BAC levels up to 0.065%.

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Introduction Sleep deprivation and circadian misalignment impairs human sensorimotor performance and reduces vigilant attention, which increases the potential for errors in occupations that require 24-hour operations. The psychomotor vigilance task (PVT) is the gold-standard measure for evaluating the impact of sleepiness on performance, however, it is not practical to administer in many operational environments, because it only provides a snapshot of performance and requires an individual to focus on the task for several minutes, multiple times over a work shift. As a result, passive, continuous monitoring of sleepiness is desirable for operational environments. The goal of the present study was to determine if complex oculomotor behavioral metrics track PVT performance during sleep deprivation. Methods Twelve healthy adults (mean age 24.8 ± 5.4 years; 6F) maintained a fixed schedule with 8.5 hours in bed for two weeks, during which they abstained from caffeine, alcohol, and other medications, followed by a ~24 hours constant routine laboratory stay. Participants completed the PVT and a radial step-ramp ocular tracking task hourly throughout the study. Twelve oculometrics were derived from smooth pursuit and saccadic eye movements collected through video-oculography and were compared to the PVT and Karolinska Sleepiness Scale (KSS) using linear regression and receiver operating characteristic curves. Results Nine oculometrics spanning pursuit, saccade, and directional motion processing performance correlated with the PVT and KSS (p &lt; 0.05), including: (a) pursuit latency; (b) open-loop pursuit acceleration; (c) proportion smooth; (d) steady-state pursuit gain; (e) saccadic amplitude; (f) saccadic dispersion; (g) saccadic rate; (h) direction asymmetry; and (i) direction noise. Conclusion The oculometrics that we examined exhibited a distinct pattern that tracked PVT performance. Future studies should examine whether these metrics can be extracted through passive monitoring techniques. Support None

Human error has been implicated as a causal factor in a large proportion of road accidents. Automated driving systems purport to mitigate this risk, but self-driving systems that allow a driver to entirely disengage from the driving task also require the driver to monitor the environment and take control when necessary. Given that sleep loss impairs monitoring performance and there is a high prevalence of sleep deficiency in modern society, we hypothesized that supervising a self-driving vehicle would unmask latent sleepiness compared to manually controlled driving among individuals following their typical sleep schedules. We found that participants felt sleepier, had more involuntary transitions to sleep, had slower reaction times and more attentional failures, and showed substantial modifications in brain synchronization during and following an autonomous drive compared to a manually controlled drive. Our findings suggest that the introduction of partial self-driving capabilities in vehicles has the potential to paradoxically increase accident risk.

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Objective Assess operator performance in a simulation of US Coast Guard small boat recovery to a larger vessel on a large scale, six degree-of-freedom, full motion simulator. Background Studies of human performance in small boat recovery task have never been conducted on a high amplitude, low frequency simulator. Empirical evidence of small boat recovery task performance in challenging motion conditions is needed to inform future maritime systems designs. Method Experienced active-duty boat crewmembers ( N = 13) conducted a small boat recovery task in three sea states on the Vertical Motion Simulator (VMS) at the NASA Ames Research Center. Task performance was assessed using a task equivalent for time to complete the task. Participant behaviors associated with increasing motion severity were observed. Results Task performance declined as motion conditions became more severe. Participants were more likely to use at least one hand to maintain balance during motion conditions, becoming more frequent with increasing motion severity. Many participants used one hand to complete the task despite contrary instructions and previous experience. Conclusion Two design recommendations were proposed to counter declining task performance in increasingly severe motion conditions. Handholds available to participants during the task, and task design supporting single handed completion were recommended for small boat recovery systems. Application This research is directly applicable to gross motor tasks requiring simultaneous maintenance of balance in a maritime environment, and may be extended to other environments where humans experience complex motions while completing tasks.