Home / Publications / Articles in professional journals /

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

By raduchcsilla

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

Front. Neuroinform., 03 October 2022

DOI: 10.3389/fninf.2022.989262

Bence Schneider1,2*, Orsolya Szalárdy2,3, Péter P. Ujma2, Péter Simor4, Ferenc Gombos5,6, Ilona Kovács5, Martin Dresler7 and Róbert Bódizs2

  • 1Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
  • 2Institute of Behavioural Sciences, Semmelweis University Budapest, Budapest, Hungary
  • 3Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
  • 4Institute of Psychology, ELTE, Eötvös Loránd University, Budapest, Hungary
  • 5Department of General Psychology, Pázmány Péter Catholic University, Budapest, Hungary
  • 6MTA—PPKE Adolescent Development Research Group, Budapest, Hungary
  • 7Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands

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.