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Radboud Repository
Article . 2017
Data sources: Radboud Repository
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Journal of Neuroscience Methods
Article . 2017 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Automated selective disruption of slow wave sleep

Authors: Ooms, S.J.; Zempel, J.; Holtzman, D.M.; Ju, Y.;

Automated selective disruption of slow wave sleep

Abstract

Slow wave sleep (SWS) plays an important role in neurophysiologic restoration. Experimentally testing the effect of SWS disruption previously required highly time-intensive and subjective methods. Our goal was to develop an automated and objective protocol to reduce SWS without affecting sleep architecture.We developed a custom Matlab™ protocol to calculate electroencephalogram spectral power every 10s live during a polysomnogram, exclude artifact, and, if measurements met criteria for SWS, deliver increasingly louder tones through earphones. Middle-aged healthy volunteers (n=10) each underwent 2 polysomnograms, one with the SWS disruption protocol and one with sham condition.The SWS disruption protocol reduced SWS compared to sham condition, as measured by spectral power in the delta (0.5-4Hz) band, particularly in the 0.5-2Hz range (mean 20% decrease). A compensatory increase in the proportion of total spectral power in the theta (4-8Hz) and alpha (8-12Hz) bands was seen, but otherwise normal sleep features were preserved. N3 sleep decreased from 20±34 to 3±6min, otherwise there were no significant changes in total sleep time, sleep efficiency, or other macrostructural sleep characteristics.This novel SWS disruption protocol produces specific reductions in delta band power similar to existing methods, but has the advantage of being automated, such that SWS disruption can be performed easily in a highly standardized and operator-independent manner.This automated SWS disruption protocol effectively reduces SWS without impacting overall sleep architecture.

Country
Netherlands
Keywords

Automation, Laboratory, Time Factors, Polysomnography, Brain, Electroencephalography, Middle Aged, Pattern Recognition, Automated, Acoustic Stimulation, Radboudumc 1: Alzheimer`s disease DCMN: Donders Center for Medical Neuroscience, Humans, Sleep Deprivation, Artifacts, Sleep, Software, Aged

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    5
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Average
bronze