title: Automated selective disruption of slow wave sleep.
abstract: BACKGROUND
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  This automated SWS disruption protocol effectively reduces SWS without impacting overall sleep architecture.
authors.affiliation: Department of Geriatric Medicine, Radboud University Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands; Radboud Alzheimer Centre, Radboud University Medical Centre, Nijmegen, The Netherlands. Electronic address: Sharon.Ooms@radboudumc.nl.
authors.forename: Sharon J
authors.initials: SJ
authors.lastname: Ooms
authors.affiliation: Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, Box 8111, St. Louis, MO 63110, USA. Electronic address: zempelj@neuro.wustl.edu.
authors.forename: John M
authors.initials: JM
authors.lastname: Zempel
authors.affiliation: Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, Box 8111, St. Louis, MO 63110, USA; The Charles F. and Joanne Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA. Electronic address: holtzman@neuro.wustl.edu.
authors.forename: David M
authors.initials: DM
authors.lastname: Holtzman
authors.affiliation: Department of Neurology, Washington University School of Medicine, 660 South Euclid Avenue, Box 8111, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA. Electronic address: juy@neuro.wustl.edu.
authors.forename: Yo-El S
authors.initials: YS
authors.lastname: Ju
mesh_terms: D000161:Acoustic Stimulation / Q000295:instrumentation / Q000379:methods*; D000368:Aged; D016477:Artifacts; D057205:Automation, Laboratory / Q000295:instrumentation / Q000379:methods*; D001921:Brain / Q000503:physiopathology; D004569:Electroencephalography / Q000295:instrumentation / Q000379:methods*; D006801:Humans; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods; D017286:Polysomnography / Q000295:instrumentation / Q000379:methods*; D012890:Sleep / Q000502:physiology; D012892:Sleep Deprivation / Q000209:etiology* / Q000503:physiopathology; D012984:Software; D013997:Time Factors
keywords: Electroencephalogram; Polysomnogram; Sleep; Slow wave sleep; Spectral power