This section aims to increase our understanding of the neuronal underpinnings of sleep & circadian rhythms
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Frontiers in Neuroscience | Sleep and Circadian Rhythms section | New and Recent Articles
A sleep staging model based on adversarial domain generalized residual attention network
To solve the problem of poor generalization ability of the model on unknown data and the difference of physiological signals between different subjects. A sleep staging model based on Adversarial Domain Generalized Residual Attention Network (ADG-...
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Nighttime sleep duration and the prevalence of hyperuricemia: a systematic review and network meta-analysis
ObjectiveAccording to clinical observation and recent studies, there is a significant association between night sleep duration and hyperuricemia. In this study, systematic review and network meta-analysis were performed to evaluate the risk of hyp...
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Circadian disruption is associated with altered postural control in aged individuals under eye closed condition
BackgroundSleep loss is reported to affect postural control. However, the relationship between increased postural sway and the circadian rhythm (CR) remains unclear.ObjectivesTo assess performance in the postural control test in aged individuals w...
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Maturation of infant sleep during the first 6 months of life: a mini-scoping review
IntroductionSeveral foundational aspects of neurodevelopment occur during the early months of infant life, most notably the maturation and consolidation of wake/sleep cycles. Past studies have had difficulty quantifying infant sleep, with most res...
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The impact of postoperative pain interventions on circadian rhythm disruptions: mechanisms and clinical implications
Postoperative pain is a prevalent clinical issue that significantly impacts patient recovery, making its management crucial for rehabilitation. Recent studies have shown that postoperative pain not only affects the physiological state of patients ...
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Graph-informed convolutional autoencoder to classify brain responses during sleep
Automated machine-learning algorithms that analyze biomedical signals have been used to identify sleep patterns and health issues. However, their performance is often suboptimal, especially when dealing with imbalanced datasets. In this paper, we ...
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MRI-based machine learning analysis of perivascular spaces and their link to sleep disturbances, dementia, and mental distress in young adults with long-time mobile phone use
ObjectiveLong-term mobile phone use (LTMPU) has been linked to sleep disorders, mood disorders, and cognitive impairment, with MRI-detected enlarged perivascular spaces (EPVSs) as potential imaging markers. This study investigated computational MR...
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Altered connection properties of the left dorsolateral superior frontal gyrus in de novo drug-naïve insomnia disorder
BackgroundInsomnia disorder (ID) is increasingly prevalent, posing significant risks to patients’ physical and mental health. However, its neuropathological mechanisms remain unclear. Despite extensive research on ID using resting-state functional...
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