Exercise intervention in middle-aged and elderly individuals with insomnia improves sleep and restores connectivity in the motor network.

Exercise is a potential treatment to improve sleep quality in middle-aged and elderly individuals. Understanding exercise-induced changes in functional plasticity of brain circuits that underlie improvements in sleep among middle-aged and older adults can inform treatment of sleep problems. The aim of the study is to identify the effects of a 12-week exercise program on sleep quality and brain functional connectivity in middle-aged and older adults with insomnia. The trial was registered with Chinese Clinical Trial Register (ChiCTR2000033652). We recruited 84 healthy sleepers and 85 individuals with insomnia. Participants with insomnia were assigned to receive either a 12-week exercise intervention or were placed in a 12-week waitlist control condition. Thirty-seven middle-aged and older adults in the exercise group and 30 in the waitlist group completed both baseline and week 12 assessments. We found that middle-aged and older adults with insomnia showed significantly worse sleep quality than healthy sleepers. At the brain circuit level, insomnia patients showed decreased connectivity in the widespread motor network. After exercise intervention, self-reported sleep was increased in the exercise group (P < 0.001) compared to that in the waitlist group. We also found increased functional connectivity of the motor network with the cerebellum in the exercise group (P < 0.001). Moreover, we observed significant correlations between improvement in subjective sleep indices and connectivity changes within the motor network. We highlight exercise-induced improvement in sleep quality and functional plasticity of the aging brain.

Acute Tai Chi Chuan exercise enhances sustained attention and elicits increased cuneus/precuneus activation in young adults.

BACKGROUND: The potential for acute exercise to enhance attention has been discussed in the literature. However, the neural mechanisms by which acute exercise affects attention remain elusive. METHOD: In this study, we first identified an optimized acute Tai Chi Chuan (ATCC) exercise protocol that enhances sustained attention performance and then aimed to determine the neural substrates of exercise-enhanced attention. Reaction time (RT) from the psychomotor vigilance test (PVT) was used to evaluate sustained attention. In Experiment 1, improvements in RTs were compared among six different exercise protocols. In Experiment 2, the participants completed the PVT in an MRI scanner on both rest and exercise days. RESULTS: Experiment 1 showed that practicing TCC 3 times for a total of 20 minutes, followed by 10-minute rest periods, resulted in the largest improvements in RTs. Experiment 2 showed that ATCC enhanced sustained attention, as evidenced by shorter RTs, and resulted in greater cuneus/precuneus activation after exercise than in the rest condition. Exercise-induced changes in brain activities across a distributed network exhibited significant correlations with attention. CONCLUSION: Therefore, this study indicates that ATCC effectively enhances sustained attention and underscores the key role of the cuneus/precuneus and frontoparietal-cerebellar regions in facilitating vigilance among young adults.

Changes in white matter functional networks during wakefulness and sleep.

Blood oxygenation level-dependent (BOLD) signals in the white matter (WM) have been demonstrated to encode neural activities by showing structure-specific temporal correlations during resting-state and task-specific imaging of fiber pathways with various degrees of correlations in strength and time delay. Previous neuroimaging studies have shown state-dependent functional connectivity and regional amplitude of signal fluctuations in brain gray matter across wakefulness and nonrapid eye movement (NREM) sleep cycles. However, the functional characteristics of WM during sleep remain unknown. Using simultaneous electroencephalography and functional magnetic resonance imaging data during wakefulness and NREM sleep collected from 66 healthy participants, we constructed 10 stable WM functional networks using clustering analysis. Functional connectivity between these WM functional networks and regional amplitude of WM signal fluctuations across multiple low-frequency bands were evaluated. In general, decreased WM functional connectivity between superficial and middle layer WM functional networks was observed from wakefulness to sleep. In addition, functional connectivity between the deep and cerebellar networks was higher during light sleep and lower during both wakefulness and deep sleep. The regional fluctuation amplitude was always higher during light sleep and lower during deep sleep. Importantly, slow-wave activity during deep sleep negatively correlated with functional connectivity between WM functional networks but positively correlated with fluctuation strength in the WM. These observations provide direct physiological evidence that neural activities in the WM are modulated by the sleep-wake cycle. This study provided the initial mapping of functional changes in WM during sleep.

Fast finite Hilbert transform via DE quadrature scheme.

PURPOSE: The finite Hilbert transform (FHT) or inverse finite Hilbert transform (IFHT) is recently found to have some important applications in computerized tomography (CT) arena, where they are used to filter the derivatives of back-projected data in the chord-line based CT reconstruction algorithms. In this paper, we implemented, improved and validated a fast numerical solution to the FHT via a double exponential (DE) integration scheme. A same strategy can be used to compute IFHT. METHODS: To overcome the underflow of floating-point numbers, we first determined the range of variable transformation from the minimum positive value of single or double precision floating point number, the integration step can be further determined by the range of variable transformation and the integration level. Two functions with their known analytical FHTs are used to validate the implementation of the FHT via DE scheme. The surface map and 2D contour of the FHT transformation error with respect to integration level and the range of the variable transformation are used to numerically determine the optimal numbers for a fast FHT. RESULTS: Given a specific precision, the lowest integration level and the optimal range of variable transformation, which are used to transform a signal with a certain degree of fluctuation, can be numerically determined by the surface map and 2D contour of the standard deviation of transformation error. These two numbers can then be taken to efficiently compute the FHT for other signals with the same or less degree of fluctuation. CONCLUSIONS: The FHT via DE scheme and the numerical method to determine the integration level and the range of transformation can be used for fast FHT in certain applications, such as data filtering in chord-line based CT reconstruction algorithms.