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Fluctuations in resting-state functional connectivity and global signal have been found to correspond with vigilance fluctuations, but their associations with other behavioral measures are unclear. We evaluated 52 healthy adolescents after a week of adequate sleep followed by five nights of sleep restriction to unmask inter-individual differences in cognition and mood. Resting state scans obtained at baseline only, analyzed using sliding window analysis, consistently yielded two polar dynamic functional connectivity states (DCSs) corresponding to previously reported ‘ low arousal ’ and ‘ high arousal ’ states. We found that the relative temporal preponderance of two dynamic connectivity states (DCS) in well-rested participants, indexed by a median split of participants, based on the relative time spent in these DCS, revealed highly significant group differences in vigilance at baseline and its decline following multiple nights of sleep restriction. Group differences in processing speed and working memory following manipulation but not at baseline suggest utility of DCS in predicting cognitive vulnerabilities unmasked by a stressor like sleep restriction. DCS temporal predominance was uninformative about mood and sleepiness speaking to specificity in its behavioral predictions. Global signal fluctuation provided information confined to vigilance. This appears to be related to head motion, which increases during periods of low arousal. [ABSTRACT FROM AUTHOR]

We used diffusion modelling to predict vulnerability to decline in psychomotor vigilance task ( PVT) performance following a night of total sleep deprivation ( SD). A total of 135 healthy young adults (69 women, age = 21.9 ± 1.7 years) participated in several within-subject cross-over design studies that incorporated the PVT. Participants were classified as vulnerable (lower tertile) or non-vulnerable (upper tertile) according to their change in lapse rate [lapse = reaction time ( RT) ≥ 500 ms] between the evening before ( ESD) and the morning after SD. RT data were fitted using Ratcliff's diffusion model. Although both groups showed significant change in RT during SD, there was no significant group difference in RT during the ESD session. In contrast, during ESD, the mean diffusion drift of vulnerable subjects was significantly lower than for non-vulnerable subjects. Mean drift and non-decision times were both adversely affected by sleep deprivation. Both mean drift and non-decision time showed significant state × vulnerability interaction. Diffusion modelling appears to have promise in predicting vulnerability to vigilance decline induced by a night of total sleep deprivation. [ABSTRACT FROM AUTHOR]

Robustly linking dynamic functional connectivity (DFC) states to behaviour is important for establishing the utility of the method as a functional measurement. We previously used a sliding window approach to identify two dynamic connectivity states (DCS) related to vigilance. A new sample of 32 healthy participants underwent two sets of task-free functional magnetic resonance imaging (fMRI) scans, once in a well-rested state and once after a single night of total sleep deprivation. Using a temporal difference method, DFC and clustering analysis on the task-free fMRI data revealed five centroids that were highly correlated with those found in previous work. In particular, two of these states were associated with high and low arousal respectively. Individual differences in vulnerability to sleep deprivation were measured by assessing state-related changes in Psychomotor Vigilance Test (PVT) performance. Changes in the duration spent in each of the arousal states from the well-rested to the sleep-deprived condition correlated with declines in PVT performance. The reproducibility of DFC measures and their association with vigilance highlight their utility in serving as a neuroimaging method with behavioural relevance. (178 words). • 32 individuals underwent task-free fMRI twice: while well-rested and sleep deprived. • Clustering of dynamic connectivity matrices replicated centroids found previously. • The profile of time spent in each connectivity state changed with sleep deprivation. • Changes in time spent in arousal-related states correlated with declines in vigilance. [ABSTRACT FROM AUTHOR]

While mindfulness is commonly viewed as a skill to be cultivated through practice, untrained individuals can also vary widely in dispositional mindfulness. Prior research has identified static neural connectivity correlates of this trait. Here, we use dynamic functional connectivity (DFC) analysis of resting-state fMRI to study time-varying connectivity patterns associated with naturally varying and objectively measured trait mindfulness. Participants were selected from the top and bottom tertiles of performers on a breath-counting task to form high trait mindfulness (HTM; N = 21) and low trait mindfulness (LTM; N = 18) groups. DFC analysis of resting state fMRI data revealed that the HTM group spent significantly more time in a brain state associated with task-readiness – a state characterized by high within-network connectivity and greater anti-correlations between task-positive networks and the default-mode network (DMN). The HTM group transitioned between brain states more frequently, but the dwell time in each episode of the task-ready state was equivalent between groups. These results persisted even after controlling for vigilance. Across individuals, certain connectivity metrics were weakly correlated with self-reported mindfulness as measured by the Five Facet Mindfulness Questionnaire, though these did not survive multiple comparisons correction. In the static connectivity maps, HTM individuals had greater within-network connectivity in the DMN and the salience network, and greater anti-correlations between the DMN and task-positive networks. In sum, DFC features robustly distinguish HTM and LTM individuals, and may be useful biological markers for the measurement of dispositional mindfulness. [ABSTRACT FROM AUTHOR]

Fluctuations in resting-state functional connectivity occur but their behavioral significance remains unclear, largely because correlating behavioral state with dynamic functional connectivity states (DCS) engages probes that disrupt the very behavioral state we seek to observe. Observing spontaneous eyelid closures following sleep deprivation permits nonintrusive arousal monitoring. During periods of low arousal dominated by eyelid closures, sliding-window correlation analysis uncovered a DCS associated with reduced withinnetwork functional connectivity of default mode and dorsal/ventral attention networks, as well as reduced anticorrelation between these networks. Conversely, during periods when participants’ eyelids were wide open, a second DCS was associated with less decoupling between the visual network and higher-order cognitive networks that included dorsal/ventral attention and default mode networks. In subcortical structures, eyelid closures were associated with increased connectivity between the striatum and thalamus with the ventral attention network, and greater anticorrelation with the dorsal attention network. When applied to task-based fMRI data, these two DCS predicted interindividual differences in frequency of behavioral lapsing and intraindividual temporal fluctuations in response speed. These findings with participants who underwent a night of total sleep deprivation were replicated in an independent dataset involving partially sleep-deprived participants. Fluctuations in functional connectivity thus appear to be clearly associated with changes in arousal. [ABSTRACT FROM AUTHOR]

The electroencephalographic power spectra of non‐rapid eye movement sleep in adults demonstrate trait‐like consistency within participants across multiple nights, even when prior sleep deprivation is present. Here, we examined the extent to which this finding applies to adolescents who are habitually sleep restricted on school‐days and sleep longer on weekends. We evaluated 78 adolescents across three sleep restriction groups who underwent different permutations of adequate sleep (9 hr time‐in‐bed), sleep restriction (5 hr time‐in‐bed), afternoon naps (1 hr afternoon) and recovery sleep (9 hr time‐in‐bed) that simulate behaviour on school‐days and weekends. The control group comprised a further 22 adolescents who had 9 hr of sleep opportunity each night. Intra‐class correlation coefficients showed moderate to almost perfect within‐subject stability in electroencephalographic power spectra across multiple nights in both sleep restriction and control groups, even when changes to sleep macrostructure were observed. While nocturnal intra‐class correlation metrics were lower in the low‐frequency and spindle frequency bins in the sleep restriction compared with the control group, hierarchical clustering measures could still identify multi‐night electroencephalographic spectra as originating from the same individual. The trait‐like characteristics of electroencephalographic spectra from an adolescent remain identifiable despite the disruptive effects of multi‐night sleep restriction to sleep architecture. [ABSTRACT FROM AUTHOR]

Prior reports on geographical differences in sleep duration have relied on samples collected at different time points with a variety of subjective instruments. Using sleep data from a total of 553,559 nights from 23,680 Fitbit users (aged 15-80y), we found objective evidence for regional disparities in sleep duration of 32-43 min between Oceanian and East Asian users on weekdays. This was primarily driven by later bedtimes in East Asians. Although users in all countries extended sleep on weekends, East Asians continued to sleep less than their Oceanian counterparts. Women generally slept more than men, and older users slept less than younger users. Reasons for shorter sleep duration in East Asians on both weekdays and weekends, across the lifespan and in both sexes remain to be investigated. [ABSTRACT FROM AUTHOR]