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1.
Sci Rep ; 13(1): 8444, 2023 05 25.
Article in English | MEDLINE | ID: mdl-37231107

ABSTRACT

We performed a mathematical analysis of functional connectivity in electroencephalography (EEG) of patients with obstructive sleep apnea (OSA) (N = 10; age: 52.8 ± 13 years; median age: 49 years; male/female ratio: 7/3), compared with a group of apparently healthy participants (N = 15; age: 51.5 ± 29.5 years; median age: 42 years; male/female ratio: 8/7), based on the calculation of wavelet bicoherence from nighttime polysomnograms. Having observed the previously known phenomenon of interhemispheric synchronization deterioration, we demonstrated a compensatory increase in intrahemispheric connectivity, as well as a slight increase in the connectivity of the central and occipital areas for high-frequency EEG activity. Significant changes in functional connectivity were extremely stable in groups of apparently healthy participants and OSA patients, maintaining the overall pattern when comparing different recording nights and various sleep stages. The maximum variability of the connectivity was observed at fast oscillatory processes during REM sleep. The possibility of observing some changes in functional connectivity of brain activity in OSA patients in a state of passive wakefulness opens up prospects for further research. Developing the methods of hypnogram evaluation that are independent of functional connectivity may be useful for implementing a medical decision support system.


Subject(s)
Sleep Apnea, Obstructive , Sleep , Humans , Female , Male , Middle Aged , Adult , Aged , Young Adult , Aged, 80 and over , Sleep, REM , Electroencephalography/methods , Sleep Stages , Wakefulness
2.
Sci Rep ; 11(1): 18505, 2021 09 16.
Article in English | MEDLINE | ID: mdl-34531434

ABSTRACT

A new approach for detection oscillatory patterns and estimation of their dynamics based by a modified CWT skeleton method is presented. The method opens up additional perspectives for the analysis of subtle changes in the oscillatory activity of complex nonstationary signals. The method was applied to analyze unique experimental signals obtained in usual conditions and after the non-invasive increase in the blood-brain barrier (BBB) permeability in 10 male Wistar rats. The results of the wavelet-analysis of electrocorticography (ECoG) recorded in a normal physiological state and after an increase in the BBB permeability of animals demonstrate significant changes between these states during wakefulness of animals and an essential smoothing of these differences during sleep. Sleep is closely related to the processes of observed changes in the BBB permeability.


Subject(s)
Blood-Brain Barrier/physiology , Brain/physiology , Sleep/physiology , Wakefulness/physiology , Animals , Electrocorticography , Male , Permeability , Rats , Rats, Wistar , Wavelet Analysis
3.
Sleep Breath ; 25(4): 2251-2258, 2021 12.
Article in English | MEDLINE | ID: mdl-33768413

ABSTRACT

PURPOSE: During the last decade, the reported prevalence of sleep-disordered breathing in adults has been rapidly increasing. Therefore, automatic methods of sleep assessment are of particular interest. In a framework of translational neuroscience, this study introduces a reliable automatic detection system of behavioral sleep in laboratory rats based on the signal recorded at the cortical surface without requiring electromyography. METHODS: Experimental data were obtained in 16 adult male WAG/Rij rats at the age of 9 months. Electrocorticographic signals (ECoG) were recorded in freely moving rats during the entire day (22.5 ± 2.2 h). Automatic wavelet-based assessment of behavioral sleep (BS) was proposed. The performance of this wavelet-based method was validated in a group of rats with genetic predisposition to absence epilepsy (n=16) based on visual analysis of their behavior in simultaneously recorded video. RESULTS: The accuracy of automatic sleep detection was 98% over a 24-h period. An automatic BS assessment method can be adjusted for detecting short arousals during sleep (microarousals) with various duration. CONCLUSIONS: These findings suggest that automatic wavelet-based assessment of behavioral sleep can be used for assessment of sleep quality. Current analysis indicates a temporal relationship between microarousals, sleep, and epileptic discharges in genetically prone subjects.


Subject(s)
Behavior, Animal/physiology , Cerebral Cortex/physiology , Electrocorticography/standards , Sleep/physiology , Animals , Electrocorticography/methods , Male , Rats , Sensitivity and Specificity , Wavelet Analysis
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