Human blood adenosine biomarkers and non‐rapid eye movement sleep stage 3 (NREM3) cortical functional connectivity associations during a 30‐day head‐down‐tilt bed rest analogue: Potential effectiveness of a reactive sledge jump as a countermeasure

2021 ◽  
Author(s):  
Christiane M. Nday ◽  
Christos A. Frantzidis ◽  
Christina Plomariti ◽  
Sotiria C. Gilou ◽  
Giorgos Ntakakis ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Eye Movement ◽  
Human Blood ◽  
Sleep Stage ◽  
Bed Rest ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Potential Effectiveness

High-throughput visual assessment of sleep stages in mice using machine learning

SLEEP ◽  
2021 ◽  
Author(s):  
Brian Geuther ◽  
Mandy Chen ◽  
Raymond J Galante ◽  
Owen Han ◽  
Jie Lian ◽  
...  
Keyword(s):  
Machine Learning ◽  
Eye Movement ◽  
High Throughput ◽  
Data Augmentation ◽  
Sleep Stage ◽  
Visual Assessment ◽  
Video Data ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep

Abstract Study Objectives Sleep is an important biological process that is perturbed in numerous diseases, and assessment its substages currently requires implantation of electrodes to carry out electroencephalogram/electromyogram (EEG/EMG) analysis. Although accurate, this method comes at a high cost of invasive surgery and experts trained to score EEG/EMG data. Here, we leverage modern computer vision methods to directly classify sleep substages from video data. This bypasses the need for surgery and expert scoring, provides a path to high-throughput studies of sleep in mice. Methods We collected synchronized high-resolution video and EEG/EMG data in 16 male C57BL/6J mice. We extracted features from the video that are time and frequency-based and used the human expert-scored EEG/EMG data to train a visual classifier. We investigated several classifiers and data augmentation methods. Results Our visual sleep classifier proved to be highly accurate in classifying wake, non-rapid eye movement sleep (NREM), and rapid eye movement sleep (REM) states, and achieves an overall accuracy of 0.92 +/- 0.05 (mean +/- SD). We discover and genetically validate video features that correlate with breathing rates, and show low and high variability in NREM and REM sleep, respectively. Finally, we apply our methods to non-invasively detect that sleep stage disturbances induced by amphetamine administration. Conclusions We conclude that machine learning based visual classification of sleep is a viable alternative to EEG/EMG based scoring. Our results will enable non-invasive high-throughput sleep studies and will greatly reduce the barrier to screening mutant mice for abnormalities in sleep.

scholarly journals Altered Functional Connectivity in Idiopathic Rapid Eye Movement Sleep Behavior Disorder: A Resting-State EEG Study

SLEEP ◽  
2017 ◽  
Vol 40 (6) ◽  
Author(s):  
Jun-Sang Sunwoo ◽  
Sanghun Lee ◽  
Jung-Hoon Kim ◽  
Jung-Ah Lim ◽  
Tae-Joon Kim ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Eye Movement ◽  
Resting State ◽  
Behavior Disorder ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Sleep Behavior

Influence of sleep on tensor palatini EMG and upper airway resistance in normal men

1991 ◽  
Vol 70 (6) ◽  
pp. 2574-2581 ◽  
Author(s):  
D. J. Tangel ◽  
W. S. Mezzanotte ◽  
D. P. White
Keyword(s):  
Eye Movement ◽  
Airway Resistance ◽  
Sleep Stage ◽  
Upper Airway ◽  
Sleep Stages ◽  
Normal Male ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Airway Narrowing ◽  
Upper Airway Resistance

We propose that a sleep-induced decrement in the activity of the tensor palatini (TP) muscle could induce airway narrowing in the area posterior to the soft palate and therefore lead to an increase in upper airway resistance in normal subjects. We investigated the TP to determine the influence of sleep on TP muscle activity and the relationship between changing TP activity and upper airway resistance over the entire night and during short sleep-awake transitions. Seven normal male subjects were studied on a single night with wire electrodes placed in both TP muscles. Sleep stage, inspiratory airflow, transpalatal pressure, and TP moving time average electromyogram (EMG) were continuously recorded. In addition, in two of the seven subjects the activity (EMG) of both the TP and the genioglossus muscle simultaneously was recorded throughout the night. Upper airway resistance increased progressively from wakefulness through the various non-rapid-eye-movement sleep stages, as has been previously described. The TP EMG did not commonly demonstrate phasic activity during wakefulness or sleep. However, the tonic EMG decreased progressively and significantly (P less than 0.05) from wakefulness through the non-rapid-eye-movement sleep stages [awake, 4.6 +/- 0.3 (SE) arbitrary units; stage 1, 2.6 +/- 0.3; stage 2, 1.7 +/- 0.5; stage 3/4, 1.5 +/- 0.8]. The mean correlation coefficient between TP EMG and upper airway resistance across all sleep states was (-0.46). This mean correlation improved over discrete sleep-awake transitions (-0.76). No sleep-induced decrement in the genioglossus activity was observed in the two subjects studied.(ABSTRACT TRUNCATED AT 250 WORDS)

scholarly journals Dream Recall upon Awakening from Non-Rapid Eye Movement Sleep in Older Adults: Electrophysiological Pattern and Qualitative Features

2020 ◽  
Vol 10 (6) ◽  
pp. 343 ◽  
Author(s):  
Serena Scarpelli ◽  
Aurora D’Atri ◽  
Chiara Bartolacci ◽  
Maurizio Gorgoni ◽  
Anastasia Mangiaruga ◽  
...  
Keyword(s):  
Eye Movement ◽  
Sleep Stage ◽  
Nrem Sleep ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep ◽  
Dream Recall ◽  
Cortical Arousal ◽  
Beta Power ◽  
Dream Report

Several findings support the activation hypothesis, positing that cortical arousal promotes dream recall (DR). However, most studies have been carried out on young participants, while the electrophysiological (EEG) correlates of DR in older people are still mostly unknown. We aimed to test the activation hypothesis on 20 elders, focusing on the Non-Rapid Eye Movement (NREM) sleep stage. All the subjects underwent polysomnography, and a dream report was collected upon their awakening from NREM sleep. Nine subjects were recallers (RECs) and 11 were non-RECs (NRECs). The delta and beta EEG activity of the last 5 min and the total NREM sleep was calculated by Fast Fourier Transform. Statistical comparisons (RECs vs. NRECs) revealed no differences in the last 5 min of sleep. Significant differences were found in the total NREM sleep: the RECs showed lower delta power over the parietal areas than the NRECs. Consistently, statistical comparisons on the activation index (delta/beta power) revealed that RECs showed a higher level of arousal in the fronto-temporal and parieto-occipital regions than NRECs. Both visual vividness and dream length are positively related to the level of activation. Overall, our results are consistent with the view that dreaming and the storage of oneiric contents depend on the level of arousal during sleep, highlighting a crucial role of the temporo-parietal-occipital zone.

Metabolic rate and breathing during sleep

1985 ◽  
Vol 59 (2) ◽  
pp. 384-391 ◽  
Author(s):  
D. P. White ◽  
J. V. Weil ◽  
C. W. Zwillich
Keyword(s):  
Metabolic Rate ◽  
Eye Movement ◽  
Sleep Stage ◽  
Minute Ventilation ◽  
Respiratory Control ◽  
Normal Subjects ◽  
Co2 Production ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep

Recent investigation suggests that both ventilation (VE) and the chemical sensitivity of the respiratory control system correlate closely with measures of metabolic rate [O2 consumption (VO2) and CO2 production (VCO2)]. However, these associations have not been carefully investigated during sleep, and what little information is available suggests a deterioration of the relationships. As a result we measured VE, ventilatory pattern, VO2, and VCO2 during sleep in 21 normal subjects (11 males and 10 females) between the ages of 21 and 77 yr. When compared with values for awake subjects, expired ventilation decreased 8.2 +/- 2.3% (SE) during sleep and was associated with a 8.5 +/- 1.6% decrement in VO2 and a 12.3 +/- 1.7% reduction in VCO2, all P less than 0.01. The decrease in ventilation was a product primarily of a significant decrease in tidal volume with little change in frequency. None of these findings were dependent on sleep stage with results in rapid-eye-movement (REM) and non-rapid-eye-movement sleep being similar. Through all sleep stages ventilation remained tightly correlated with VO2 and VCO2 both within a given individual and between subjects. Although respiratory rhythmicity was somewhat variable during REM sleep, minute ventilation continued to correlate with VO2 and VCO2. None of the parameters described above were influenced by age or gender, with male and female subjects demonstrating similar findings. Ten of the subjects demonstrated at least occasional apneas. These individuals, however, were not found to differ from those without apnea in any other measure of ventilation or metabolic rate.

Partitioning of inhaled ventilation between the nasal and oral routes during sleep in normal subjects

2003 ◽  
Vol 94 (3) ◽  
pp. 883-890 ◽  
Author(s):  
Michael F. Fitzpatrick ◽  
Helen S. Driver ◽  
Neela Chatha ◽  
Nha Voduc ◽  
Alison M. Girard
Keyword(s):  
Eye Movement ◽  
Slow Wave ◽  
Sleep Stage ◽  
Minute Ventilation ◽  
Normal Subjects ◽  
Sleep Stages ◽  
Rapid Eye Movement ◽  
Nasal Mask ◽  
Rapid Eye Movement Sleep ◽  
Significant Difference

The oral and nasal contributions to inhaled ventilation were simultaneously quantified during sleep in 10 healthy subjects (5 men, 5 women) aged 43 ± 5 yr, with normal nasal resistance (mean 2.0 ± 0.3 cmH2O · l−1 · s−1) by use of a divided oral and nasal mask. Minute ventilation awake (5.9 ± 0.3 l/min) was higher than that during sleep (5.2 ± 0.3 l/min; P < 0.0001), but there was no significant difference in minute ventilation between different sleep stages ( P = 0.44): stage 2 5.3 ± 0.3, slow-wave 5.2 ± 0.2, and rapid-eye-movement sleep 5.2 ± 0.2 l/min. The oral fraction of inhaled ventilation during wakefulness (7.6 ± 4%) was not significantly different from that during sleep (4.3 ± 2%; mean difference 3.3%, 95% confidence interval −2.1–8.8%, P = 0.19), and no significant difference ( P = 0.14) in oral fraction was observed between different sleep stages: stage two 5.1 ± 2.8, slow-wave 4.2 ± 1.8, rapid-eye-movement 3.1 ± 1.7%. Thus the inhaled oral fraction in normal subjects is small and does not change significantly with sleep stage.

First rapid eye movement sleep periods and sleep-onset rapid eye movement periods in sleep-stage sequencing of hypersomnias

2013 ◽  
Vol 14 (9) ◽  
pp. 897-901 ◽  
Author(s):  
Panagis Drakatos ◽  
Christopher A. Kosky ◽  
Sean E. Higgins ◽  
Rexford T. Muza ◽  
Adrian J. Williams ◽  
...  
Keyword(s):  
Eye Movement ◽  
Sleep Stage ◽  
Sleep Onset ◽  
Rapid Eye Movement ◽  
Rapid Eye Movement Sleep
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