Sleep deprivation (SD) can alter the intrinsic brain functional organization. However, its effects on intrinsic low-frequency connectivity in the whole brain have not been well characterized. In this study, we used voxel-based functional connectivity density (FCD) analysis to investigate the effects of SD on the spontaneous functional organization of the brain. Thirty-seven healthy participants underwent this within-subject crossover functional magnetic resonance imaging (fMRI) study during rested wakefulness (RW) and after 36 h of total sleep deprivation (TSD). Decreased long-/short-range FCDs were observed in the posterior cingulate cortex, precuneus, inferior parietal lobule, dorsolateral prefrontal cortex, dorsomedial prefrontal cortex, and ventromedial prefrontal cortex. Increased long-/short-range FCDs were found in the sensory integration and arousal regulating areas, including the postcentral gyrus, thalamus, superior temporal gyrus, and occipital-temporal cortex. Moreover, a significant negative correlation was found between the short-range FCD of the PCC and the reaction time of Psychomotor Vigilance Task. In the present study, spontaneous functional organization with significant group-wise differences between RW and TSD sessions was identified. Our findings extend our understanding of the neural mechanism of how brain activity is altered in sleep-deprived individuals.

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BACKGROUND: Postural control is adversely affected by mental and physical fatigue, but its validity in fatigue assessment has not been investigated systemically among pilots. We explored the correlations of posturographic balance with physiological and psychological signals among cadet pilots.METHODS: In experiment 1, 37 cadet pilots performed a posturographic balance test, heart rate variability (HRV), and profile of mood states (POMS) during 40 h of sleep deprivation. For experiment 2, physiological signals of 60 subjects, including breathing rate (BR), systolic blood pressure (SBP), and heart rate (HR) were measured under the effects of physical fatigue. Then correlations with a mental and physical fatigue index based on effective posturographic parameters with those subjective and objective methods were analyzed by linear regression.RESULTS: The mental fatigue index correlated linearly with the depression score of the POMS (r = 0.212), standard deviation of normal to normal beats (r = 0.286), and square root of the mean differences of successive beat intervals (r = 0.207). Meanwhile, linear correlations with frequency-domain parameters of HRV such as total power, low frequency power, and high frequency power were also statistically significant. With the increase in the physical fatigue index, physiological signals such as SBP (r = 0.300), HR (r = 0.349), and BR (r = 0.266) increased linearly.CONCLUSIONS: Impairment of postural stability can reflect the aggravation of mental and physical fatigue among cadet pilots, which provides a potential method for assessing fatigue level before flight tasks and preventing errors by pilots.Cheng S, Sun J, Ma J, Dang W, Tang M, Hui D, Zhang L, Hu W. Posturographic balance’s validity in mental and physical fatigue assessment among cadet pilots. Aerosp Med Hum Perform. 2018; 89(11):961–966.

BACKGROUND: Based on posturography parameters during sleep deprivation (SD), a mental fatigue index (MFI) was constructed for healthy male cadets.METHODS: There were 37 young male subjects who volunteered for two successive days of SD. Their posturography balance, profile of mood status (POMS), and heart rate variability (HRV) were measured at four different times (10:00 and 22:00 of day 1, 10:00 and 22:00 of day 2). According to the methods used in our previous research, similar MFIs based on posturography parameters were computed. Then, correlations of MFIs with POMS scores and HRV values were evaluated by linear and nonlinear methods including quadratic, S-curve, growth, and exponential analyses.RESULTS: MFI continued to increase during SD and MFI as the independent variable had quadratic relationships with fluster (R2 0.057), depression (R2 0.067), and anger (R2 0.05) scores of POMS. A linear correlation was found between MFI and the depression score (R2 0.045) and MFI correlated linearly (R2 0.029) and nonlinearly (R2 0.03) with heart rate. Similarly, MFI reflected changes in the time and frequency domain parameters of HRV, with linear (R2range: 0.0290.082) or nonlinear (R2range: 0.0300.082) relationships.DISCUSSION: The increase of MFI was linked with amplification of personal negative moods and an imbalance of autonomic nervous system activity. The findings suggest that MFI might be a potential indicator of mental fatigue and provide a method to prevent driving fatigue and human errors.Cheng S, Yang J, Su M, Sun J, Xiong K, Ma J, Hu W. Postural stability change under sleep deprivation and mental fatigue status. Aerosp Med Hum Perform. 2021; 92(8):627632.

Objective To investigate the potential for static upright balance function and brain-blood oxygen parameters to evaluate pilot workload. Methods Phase 1: The NASA Task Load Index (NASA-TLX) was used to compare the workloads of real flights with flight simulator simulated flight tasks in 15 pilots (Cohort 1). Phase 2: To determine the effects of workload, 50 cadets were divided equally into simulated flight task load (experimental) and control groups (Cohort 2). The experimental group underwent 2 h of simulated flight tasks, while the control group rested for 2 h. Their static upright balance function was evaluated using balance index-1 (BI-1), before and after the tasks, with balance system posturography equipment and cerebral blood oxygen parameters monitored with near infrared spectroscopy (NIRS) in real time. Sternberg dual-task and reaction time tests were performed in the experimental and control groups before and after the simulated flight tasks. Results (Phase1) There was a significant correlation between the workload caused by real flight and simulated flight tasks ( P <0.01), indicating that NASA-TLX scales were also a tool for measuring workloads of the stimulated flight tasks. (Phase 2) For the simulated flight task experiments, the NASA-TLX total scores were significantly different between the two groups ( P <0.001) and (pre-to-post) changes of the BI-1 index were greater in the experimental group than in controls ( P <0.001). The cerebral blood oxygen saturation levels (rsO 2 ) ( P <0.01) and ΔHb reductions ( P <0.05) were significantly higher in the experimental, compared to the control group, during the simulated flight task. In contrast to the control group the error rates ( P = 0.002) and accuracy ( P <0.001) changed significantly in the experimental group after the simulated flight tasks. Conclusions The simulated flight task model could simulate the real flight task load and static balance and NIRS were useful for evaluating pilots’ workload/fatigue.