ArticleSleep2019
Alterations in EEG connectivity in healthy young adults provide an indicator of sleep depth.
Article in Sleep, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- EEG Connectivity is an Objective Signature of Reduced Consciousness and Sleep Depth.Brain topography · 2025Article
- Dynamic brain network modulation by paced breathing and breath-holding: an EEG-based functional connectivity study.Frontiers in physiology · 2025Article
- Sleep-related changes in astrocytic biomarkers are modulated byBrain communications · 2025Article
- Longitudinal single-subject neuroimaging study reveals effects of daily environmental, physiological, and lifestyle factors on functional brain connectivity.PLoS biology · 2024Article
- Effects of gender and age on sleep EEG functional connectivity differences in subjects with mild difficulty falling asleep.Frontiers in psychiatry · 2024Article
- Characterizing brain stage-dependent pupil dynamics based on lateral hypothalamic activity.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- Brain and brain-heart Granger causality during wakefulness and sleep.Frontiers in neuroscience · 2022Article
- Article
- Glutamatergic Neurons in the Preoptic Hypothalamus Promote Wakefulness, Destabilize NREM Sleep, Suppress REM Sleep, and Regulate Cortical Dynamics.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2021Article
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Authors and funding
11 authors.
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Abstract
Current sleep analyses have used electroencephalography (EEG) to establish sleep intensity through linear and nonlinear measures. Slow wave activity (SWA) and entropy are the most commonly used markers of sleep depth. The purpose of this study is to evaluate changes in brain EEG connectivity during sleep in healthy subjects and compare them with SWA and entropy. Four different connectivity metrics: coherence (MSC), synchronization likelihood (SL), cross mutual information function (CMIF), and phase locking value (PLV), were computed focusing on their correlation with sleep depth. These measures provide different information and perspectives about functional connectivity. All connectivity measures revealed to have functional changes between the different sleep stages. The averaged CMIF seemed to be a more robust connectivity metric to measure sleep depth (correlations of 0.78 and 0.84 with SWA and entropy, respectively), translating greater linear and nonlinear interdependences between brain regions especially during slow wave sleep. Potential changes of brain connectivity were also assessed throughout the night. Connectivity measures indicated a reduction of functional connectivity in N2 as sleep progresses. The validation of connectivity indexes is necessary because they can reveal the interaction between different brain regions in physiological and pathological conditions and help understand the different functions of deep sleep in humans.
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