Sleep neurophysiological dynamics through the lens of multitaper spectral analysis

Michael J. Prerau, Ritchie E. Brown, Matt T. Bianchi, Jeffrey M. Ellenbogen, Patrick L. Purdon

Research output: Contribution to journalReview articlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)60-92
Number of pages33
JournalPhysiology
Volume32
Issue number1
DOIs
StatePublished - Jan 2017

ASJC Scopus subject areas

  • Physiology

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