4.5 Review

Sleep Neurophysiological Dynamics Through the Lens of Multitaper Spectral Analysis

期刊

PHYSIOLOGY
卷 32, 期 1, 页码 60-92

出版社

AMER PHYSIOLOGICAL SOC
DOI: 10.1152/physiol.00062.2015

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资金

  1. VA
  2. National Institutes of Health (NIH) [R21 NS-093000, R01 MH-039683, HL-095491]
  3. National Institute Of Neurological Disorders And Stroke [R01 NS-096177]
  4. NIH [DP2-OD006454]
  5. Department of Neurology, Massachusetts General Hospital
  6. Center for Integration of Medicine and Innovative Technology
  7. Milton Family Foundation
  8. MGH-MIT Grand Challenge
  9. Servier
  10. MC10, Inc.
  11. Insomnisolv, Inc.
  12. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [P01HL095491] Funding Source: NIH RePORTER
  13. NATIONAL INSTITUTE OF MENTAL HEALTH [R01MH039683] Funding Source: NIH RePORTER
  14. NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE [R01NS096177, R21NS093000] Funding Source: NIH RePORTER
  15. OFFICE OF THE DIRECTOR, NATIONAL INSTITUTES OF HEALTH [DP2OD006454] Funding Source: NIH RePORTER
  16. Veterans Affairs [I01BX001356] Funding Source: NIH RePORTER

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During sleep, cortical and subcortical structures within the brain engage in highly structured oscillatory dynamics that can be observed in the electroencephalogram (EEG). The ability to accurately describe changes in sleep state from these oscillations has thus been a major goal of sleep medicine. While numerous studies over the past 50 years have shown sleep to be a continuous, multifocal, dynamic process, long-standing clinical practice categorizes sleep EEG into discrete stages through visual inspection of 30-s epochs. By representing sleep as a coarsely discretized progression of stages, vital neurophysiological information on the dynamic interplay between sleep and arousal is lost. However, by using principled timefrequency spectral analysis methods, the rich dynamics of the sleep EEG are immediately visible-elegantly depicted and quantified at time scales ranging from a full night down to individual microevents. In this paper, we review the neurophysiology of sleep through this lens of dynamic spectral analysis. We begin by reviewing spectral estimation techniques traditionally used in sleep EEG analysis and introduce multitaper spectral analysis, a method that makes EEG spectral estimates clearer and more accurate than traditional approaches. Through the lens of the multitaper spectrogram, we review the oscillations and mechanisms underlying the traditional sleep stages. In doing so, we will demonstrate how multitaper spectral analysis makes the oscillatory structure of traditional sleep states instantaneously visible, closely paralleling the traditional hypnogram, but with a richness of information that suggests novel insights into the neural mechanisms of sleep, as well as novel clinical and research applications.

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