Investigation of Time-Frequency Characteristics of Nighttime EEG Signals in Various Brain Regions Depending on Chronotype

The paper reports the results of a partial-time analysis of EEG signals from healthy volunteers obtained during the recording of polysomnography with an expanded arrangement of electrodes (19 leads). An analysis of the characteristics of frequency patterns (their number, duration, and energy power) was carried out in 20 frequency ranges (from 1 to 40 Hz) in 5 areas of the brain (central, occipital, frontal, left, and right hemispheres). A comparison of the obtained characteristics was carried out according to the chronotypes of the respondents (“rhythmic” and “arrhythmic"). Based on the results of the study, it was possible to demonstrate chronobiological patterns of nocturnal EEG activity in healthy volunteers.

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Publication Details

Published
2024-09-19
DOI
https://doi.org/10.1109/dcna63495.2024.10718556
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

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article

Investigation of Time-Frequency Characteristics of Nighttime EEG Signals in Various Brain Regions Depending on Chronotype

Margarita A. Simonyan, Rodion Ukolov, Evgenia Drozhdeva, Yulia Zhuravleva
EEG and Brain-Computer Interfaces
article

Investigation of Time-Frequency Characteristics of Nighttime EEG Signals in Various Brain Regions Depending on Chronotype

Margarita A. Simonyan, Rodion Ukolov, Evgenia Drozhdeva, Yulia Zhuravleva
article en

Abstract

The paper reports the results of a partial-time analysis of EEG signals from healthy volunteers obtained during the recording of polysomnography with an expanded arrangement of electrodes (19 leads). An analysis of the characteristics of frequency patterns (their number, duration, and energy power) was carried out in 20 frequency ranges (from 1 to 40 Hz) in 5 areas of the brain (central, occipital, frontal, left, and right hemispheres). A comparison of the obtained characteristics was carried out according to the chronotypes of the respondents (“rhythmic” and “arrhythmic"). Based on the results of the study, it was possible to demonstrate chronobiological patterns of nocturnal EEG activity in healthy volunteers.

Saratov State University (RU), Saratov State Medical University (RU)
Russian Science Foundation
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EEG and Brain-Computer Interfaces
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