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Even when it is critical to stay awake, such as when driving, sleep deprivation weakens one's ability to do so by substantially increasing the propensity for microsleeps. Microsleeps are complete lapses of consciousness but, paradoxically, are associated with transient increases in cortical activity. But do microsleeps provide a benefit in terms of attenuating the need for sleep? And is the neural response to microsleeps altered by the degree of homeostatic drive to sleep? In this study, we continuously monitored eye-video, visuomotor responsiveness, and brain activity via fMRI in 20 healthy subjects during a 20-min visuomotor tracking task following a normally-rested night and a sleep-restricted (4-h) night. As expected, sleep restriction led to an increased number of microsleeps and an increased variability in tracking error. Microsleeps exhibited transient increases in regional activity in the fronto-parietal and parahippocampal area. Network analyses revealed divergent transient changes in the right fronto-parietal, dorsal-attention, default-mode, and thalamo-cortical functional networks. In all subjects, tracking error immediately following microsleeps was improved compared to before the microsleeps. Importantly, post-microsleep recovery in tracking response speed was associated with hyperactivation in the thalamo-cortical network. The temporal evolution of functional connectivity within the frontal and posterior nodes of the default-mode network and between the right fronto-parietal and default-mode networks was associated with temporal changes in visuomotor responsiveness. These findings demonstrate distinct brain-network-level changes in brain activity during microsleeps and suggest that neural activity in the thalamo-cortical network may facilitate the transient recovery from microsleeps. The temporal pattern of evolution in brain activity and performance is indicative of dynamic changes in vigilance during the struggle to stay awake following sleep loss., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Behavioral microsleeps are associated with complete disruption of responsiveness for [Formula: see text][Formula: see text]s to 15[Formula: see text]s. They can result in injury or death, especially in transport and military sectors. In this study, EEGs were obtained from five nonsleep-deprived healthy male subjects performing a 1[Formula: see text]h 2D tracking task. Microsleeps were detected in all subjects. Microsleep-related activities in the EEG were detected, characterized, separated from eye closure-related activity, and, via source-space-independent component analysis and power analysis, the associated sources were localized in the brain. Microsleeps were often, but not always, found to be associated with strong alpha-band spindles originating bilaterally from the anterior temporal gyri and hippocampi. Similarly, theta-related activity was identified as originating bilaterally from the frontal-orbital cortex. The alpha spindles were similar to sleep spindles in terms of frequency, duration, and amplitude-profile, indicating that microsleeps are equivalent to brief instances of Stage-2 sleep.

Sleep-deprived people, or those performing extended monotonous tasks, can exhibit brief episodes in which they suspend performance and appear to fall asleep momentarily-behavioral microsleeps ("microsleeps"). In this study, microsleeps were identified using eye video and tracking response during a 20-min continuous tracking task undertaken by 16 healthy volunteers (mean age 24.9 yrs; 8 females, 8 males) in the early afternoon following a normally rested night and a night of restricted sleep (time-in-bed restricted to 4 h). Sessions were 1 wk apart and counterbalanced. Wrist actigraphy, self-reported sleepiness, and sleep quality were also recorded. We hypothesized that high microsleep rates when normally rested or after a night of sleep restriction would be related to poor sleep quality, sleep disturbance, circadian type, irregular sleep patterns, low daily sleep duration, or poor sleep efficiency. We also hypothesized that prior performance on a 10-min psychomotor vigilance task (PVT) (mean reaction time or number of PVT lapses) would be related to the number of microsleeps during the tracking task and that PVT performance could, therefore, be used as a fitness-for-duty indicator. The number of microsleeps during the tracking task increased following sleep restriction (mean 11.4 versus 27.9; p = 0.03). There were no correlations between the number of microsleeps in the normally rested session and any of the actigraphically measured or self-reported sleep measures. However, the number of microsleeps following sleep restriction was correlated with sleep efficiency (r = 0.73, p = 0.001), sleep onset latency (r = -0.57, p = 0.02), and sleep onset time-of-day standard deviation (r = -0.54, p = 0.03) over 11 normally rested nights. There was no correlation between PVT performance and the subsequent number of microsleeps during the tracking task in either session. Attributes usually associated with beneficial nighttime sleep patterns-going to sleep at a similar time each night, falling asleep quickly, and infrequent arousals-were related to greater vulnerability to microsleeps following sleep restriction. There were intercorrelations between all the sleep measures associated with microsleep rate following sleep restriction, indicating that the measures form a pattern of behaviors and are not independently related to microsleep rate. Perhaps some people maintain a regular sleep pattern because they experience sleepiness the following day when their pattern is disrupted. Conversely, people with more variation in their sleep pattern may do so because this does not substantially increase sleepiness the following day. We conclude that people with consistent sleep patterns and efficient sleep may be more prone to microsleeps than other people when their usual regular pattern is disrupted by sleep restriction.

Behavioural microsleeps (BMs) are brief episodes of absent responsiveness accompanied by slow-eye-closure. They frequently occur as a consequence of sleep-deprivation, an extended monotonous task, and are modulated by the circadian rhythm and sleep homeostatic pressure. In this paper, a multimodal method to investigate the neural correlates of BMs using simultaneous recording of fMRI, eye-video, VEOG, and continuous visuomotor response is presented. The data were collected from 20 healthy volunteers while they performed a continuous visuomotor tracking task inside an MRI scanner for 50 min. The BMs were identified post-hoc by expert visual rating of eye-video and visuomotor response using a set of pre-defined criteria. fMRI analysis of BMs revealed changes in haemodynamic activity in several cortical and sub-cortical regions associated with visuomotor control and arousal.