title: Characterization of topographically specific sleep spindles in mice.
abstract: OBJECTIVE
  Sleep spindles in humans have been classified as slow anterior and fast posterior spindles; recent findings indicate that their profiles differ according to pharmacology, pathology, and function. However, little is known about the generation mechanisms within the thalamocortical system for different types of spindles. In this study, we aim to investigate the electrophysiological behaviors of the topographically distinctive spindles within the thalamocortical system by applying high-density EEG and simultaneous thalamic LFP recordings in mice.
  
  
  METHODS
  32-channel extracranial EEG and 2-channel thalamic LFP were recorded simultaneously in freely behaving mice to acquire spindles during spontaneous sleep.
  
  
  METHODS
  Hybrid F1 male mice of C57BL/6J and 129S4/svJae.
  
  
  RESULTS
  Spindle events in each channel were detected by spindle detection algorithm, and then a cluster analysis was applied to classify the topographically distinctive spindles. All sleep spindles were successfully classified into 3 groups: anterior, posterior, and global spindles. Each spindle type showed distinct thalamocortical activity patterns regarding the extent of similarity, phase synchrony, and time lags between cortical and thalamic areas during spindle oscillation. We also found that sleep slow waves were likely to associate with all types of sleep spindles, but also that the ongoing cortical decruitment/ recruitment dynamics before the onset of spindles and their relationship with spindle generation were also variable, depending on the spindle types.
  
  
  CONCLUSIONS
  Topographically specific sleep spindles show distinctive thalamocortical network behaviors.
authors.affiliation: Center for Neuroscience, Korea Institute of Science and Technology, Seoul, South Korea: Department of Neuroscience, University of Science and Technology, Daejon, South Korea.
authors.forename: Dongwook
authors.initials: D
authors.lastname: Kim
authors.affiliation: Center for Neuroscience, Korea Institute of Science and Technology, Seoul, South Korea.
authors.forename: Eunjin
authors.initials: E
authors.lastname: Hwang
authors.affiliation: Center for Neuroscience, Korea Institute of Science and Technology, Seoul, South Korea and Department of Neuroscience, University of Science and Technology, Daejon, South Korea.
authors.forename: Mina
authors.initials: M
authors.lastname: Lee
authors.affiliation: Korea Advanced Nano Fab Center, Gyeonggi-do, South Korea.
authors.forename: Hokun
authors.initials: H
authors.lastname: Sung
authors.affiliation: Center for Neuroscience, Korea Institute of Science and Technology, Seoul, South Korea: Department of Neuroscience, University of Science and Technology, Daejon, South Korea.
authors.forename: Jee Hyun
authors.initials: JH
authors.lastname: Choi
mesh_terms: D000465:Algorithms; D000818:Animals; D002540:Cerebral Cortex / Q000502:physiology; D016000:Cluster Analysis; D004569:Electroencephalography; D008297:Male; D051379:Mice; D008810:Mice, Inbred C57BL; D012890:Sleep / Q000502:physiology*; D013788:Thalamus / Q000502:physiology
keywords: high-density EEG; mouse; sleep slow waves; sleep spindles; thalamic LFP; thalamocortical networks; topography