Literature DB >> 16895265

A taxonomic analysis of sleep stages.

Bettina Müller1, Wolf Dietrich Gäbelein, Hartmut Schulz.   

Abstract

STUDY
OBJECTIVES: To study the structure of human sleep at the level of sleep stages. We applied taxonomic statistics to detect significant configurations (types) of different physiologic variables and their relationship to sleep stages. DESIGN AND STATISTICS: Polygraphic sleep recordings from 32 subjects (normal sleepers as well as patients with insomnia, sleep apnea, or narcolepsy; n = 8 per group) were visually scored and submitted to a configural frequency analysis. The configural frequency analysis was computed with 3 continuous input variables: an electroencephalogram parameter, which represents the point of gravity of the EEG frequency distribution; the alpha slow-wave index, and the Rest Index, based on the presence or absence of phasic electromyographic activity. These variables were dichotomized for further analysis. The combination of 2 levels ( + or -) and 3 variables resulted in 2(3) patterns ( +++ to - - - ). The configural frequency analysis is a nonparametric X2-type multivariate statistic that identifies significant patterns or types.
RESULTS: Each sleep stage contained 3 or 4 types. For non-rapid eye movement sleep stages 2, 3, and 4, types overlapped, whereas there was no overlap of types between stages 1 and 2. Types of rapid eye movement sleep did not overlap with those from stages 2, 3, and 4 but did overlap with wake and stage 1 types. The majority of observed types were significant in all 4 groups of subjects.
CONCLUSIONS: Sleep stages appear to be less homogenous than rule-based sleep scoring would suggest. Types were either restricted to one stage or overlapped with neighboring stages.

Entities:  

Mesh:

Year:  2006        PMID: 16895265     DOI: 10.1093/sleep/29.7.967

Source DB:  PubMed          Journal:  Sleep        ISSN: 0161-8105            Impact factor:   5.849


  9 in total

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Review 2.  Rethinking sleep analysis.

Authors:  Hartmut Schulz
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4.  Template-based prediction of vigilance fluctuations in resting-state fMRI.

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Journal:  Neuroimage       Date:  2018-03-13       Impact factor: 6.556

5.  Examining initial sleep onset in primary insomnia: a case-control study using 4-second epochs.

Authors:  Douglas E Moul; Anne Germain; J David Cashmere; Michael Quigley; Jean M Miewald; Daniel J Buysse
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6.  The amplitude of the resting-state fMRI global signal is related to EEG vigilance measures.

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7.  Cellular and neurochemical basis of sleep stages in the thalamocortical network.

Authors:  Giri P Krishnan; Sylvain Chauvette; Isaac Shamie; Sara Soltani; Igor Timofeev; Sydney S Cash; Eric Halgren; Maxim Bazhenov
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8.  A novel unsupervised analysis of electrophysiological signals reveals new sleep substages in mice.

Authors:  Vasiliki-Maria Katsageorgiou; Diego Sona; Matteo Zanotto; Glenda Lassi; Celina Garcia-Garcia; Valter Tucci; Vittorio Murino
Journal:  PLoS Biol       Date:  2018-05-29       Impact factor: 8.029

9.  Development of Automated Sleep Stage Classification System Using Multivariate Projection-Based Fixed Boundary Empirical Wavelet Transform and Entropy Features Extracted from Multichannel EEG Signals.

Authors:  Rajesh Kumar Tripathy; Samit Kumar Ghosh; Pranjali Gajbhiye; U Rajendra Acharya
Journal:  Entropy (Basel)       Date:  2020-10-09       Impact factor: 2.524

  9 in total

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