title: Assessing EEG sleep spindle propagation. Part 1: theory and proposed methodology.
abstract: BACKGROUND
  A convergence of studies has revealed sleep spindles to be associated with sleep-related cognitive processing and even with fundamental waking state capacities such as intelligence. However, some spindle characteristics, such as propagation direction and delay, may play a decisive role but are only infrequently investigated because of technical complexities.
  
  
  METHODS
  A new methodology for assessing sleep spindle propagation over the human scalp using noninvasive electroencephalography (EEG) is described. This approach is based on the alignment of time-frequency representations of spindle activity across recording channels.
  
  
  RESULTS
  This first of a two-part series concentrates on framing theoretical considerations related to EEG spindle propagation and on detailing the methodology. A short example application is provided that illustrates the repeatability of results obtained with the new propagation measure in a sample of 32 night recordings. A more comprehensive experimental investigation is presented in part two of the series.
  
  
  CONCLUSIONS
  Compared to existing methods, this approach is particularly well adapted for studying the propagation of sleep spindles because it estimates time delays rather than phase synchrony and it computes propagation properties for every individual spindle with windows adjusted to the specific spindle duration.
  
  
  CONCLUSIONS
  The proposed methodology is effective in tracking the propagation of spindles across the scalp and may thus help in elucidating the temporal aspects of sleep spindle dynamics, as well as other transient EEG and MEG events. A software implementation (the Spyndle Python package) is provided as open source software.
authors.affiliation: Dream and Nightmare Laboratory, Center for Advanced Research in Sleep Medicine, Hôpital du Sacré-Coeur de Montréal, 5400 boulevard Gouin Ouest Montréal, QC H4J 1C5, Canada. Electronic address: christian.oreilly@umontreal.ca.
authors.forename: Christian
authors.initials: C
authors.lastname: O'Reilly
authors.forename: Tore
authors.initials: T
authors.lastname: Nielsen
mesh_terms: D000328:Adult; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D017286:Polysomnography / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D012890:Sleep / Q000502:physiology*; D012894:Sleep Stages / Q000502:physiology; D012984:Software; D055815:Young Adult
keywords: Electroencephalography; S-transform; Signal propagation; Sleep spindle; Time delay; Time–frequency analysis