Published July 7, 2023 | Version v1
Journal article Open

A Meta-analysis of Quantitative Electroencephalography (EEG) in Insomnia Sleep Disorder

  • 1. Global Innervation LLC, Dallas, Texas, USA
  • 2. Neurocare.AI, Prosper, Texas, USA
  • 3. Department of Neuroscience, School of Behavioral & Brain Sciences, The University of Texas at Dallas, Richardson, Texas, USA
  • 4. Labouré College of Healthcare, Milton, Massachusetts, USA

Contributors

Project leader:

  • 1. Global Innervation LLC, Dallas, Texas, USA; School of Behavioral & Brain Sciences, The University of Texas at Dallas, Richardson, Texas, USA.
  • 2. Global Innervation LLC, Dallas, Texas, USA; Department of Neuroscience, School of Behavioral & Brain Sciences, The University of Texas at Dallas, Richardson, Texas, USA; Neurocare.AI, Prosper, Texas, USA; Labouré College of Healthcare, Milton, Massachusetts, USA.

Description

Electroencephalograms (EEG) can help detect sleep disorders, including insomnia and stress-related disorders. Analysis of sleep EEGs is essential for providing an objective and statistics-based assessment of EEG power spectra in patients with Insomnia Disorder (ID) using meta-analytic methods. It was characterized by increased high-frequency activity in the beta and/or gamma range and decreased activity in other frequency bands. The cause of these alterations was unknown, but cortical hyperarousal may be responsible. Benzodiazepine users exhibited increased sigma activity and decreased delta and theta activity overnight than did good sleepers, except for increased theta activity during wakefulness. This review of studies had several limitations, including inconsistent subdivisions of EEG spectral bands across studies, a small number of studies reporting data on EEG power during REM sleep, and a need for studies reporting results during daytime and sleep.

Files

v1n2 Paper 3. A Meta-analysis of Quantitative Electroencephalography (EEG) in Insomnia Sleep Disorder.pdf

Additional details

Dates

Available
2023-11-14