Unknown

Dataset Information

0

Scale-free and oscillatory spectral measures of sleep stages in humans.


ABSTRACT: Power spectra of sleep electroencephalograms (EEG) comprise two main components: a decaying power-law corresponding to the aperiodic neural background activity, and spectral peaks present due to neural oscillations. "Traditional" band-based spectral methods ignore this fundamental structure of the EEG spectra and thus are susceptible to misrepresenting the underlying phenomena. A fitting method that attempts to separate and parameterize the aperiodic and periodic spectral components called "fitting oscillations and one over f" (FOOOF) was applied to a set of annotated whole-night sleep EEG recordings of 251 subjects from a wide age range (4-69 years). Most of the extracted parameters exhibited sleep stage sensitivity; significant main effects and interactions of sleep stage, age, sex, and brain region were found. The spectral slope (describing the steepness of the aperiodic component) showed especially large and consistent variability between sleep stages (and low variability between subjects), making it a candidate indicator of sleep states. The limitations and arisen problems of the FOOOF method are also discussed, possible solutions for some of them are suggested.

SUBMITTER: Schneider B 

PROVIDER: S-EPMC9574340 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

altmetric image

Publications

Scale-free and oscillatory spectral measures of sleep stages in humans.

Schneider Bence B   Szalárdy Orsolya O   Ujma Péter P PP   Simor Péter P   Gombos Ferenc F   Kovács Ilona I   Dresler Martin M   Bódizs Róbert R  

Frontiers in neuroinformatics 20221003


Power spectra of sleep electroencephalograms (EEG) comprise two main components: a decaying power-law corresponding to the aperiodic neural background activity, and spectral peaks present due to neural oscillations. "Traditional" band-based spectral methods ignore this fundamental structure of the EEG spectra and thus are susceptible to misrepresenting the underlying phenomena. A fitting method that attempts to separate and parameterize the aperiodic and periodic spectral components called "fitt  ...[more]

Similar Datasets

| S-EPMC9626458 | biostudies-literature
| S-EPMC5704022 | biostudies-literature
| S-EPMC8119820 | biostudies-literature
| S-EPMC4164638 | biostudies-literature
| S-EPMC7607534 | biostudies-literature
| S-EPMC6687190 | biostudies-literature
| S-EPMC10830482 | biostudies-literature
| S-EPMC7773861 | biostudies-literature
| S-EPMC7573387 | biostudies-literature
| S-EPMC2964192 | biostudies-other