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Sleep. 2015 Jan 1;38(1):85-96. doi: 10.5665/sleep.4330.

Characterization of topographically specific sleep spindles in mice.

Author information

1
Center for Neuroscience, Korea Institute of Science and Technology, Seoul, South Korea: Department of Neuroscience, University of Science and Technology, Daejon, South Korea.
2
Center for Neuroscience, Korea Institute of Science and Technology, Seoul, South Korea.
3
Center for Neuroscience, Korea Institute of Science and Technology, Seoul, South Korea and Department of Neuroscience, University of Science and Technology, Daejon, South Korea.
4
Korea Advanced Nano Fab Center, Gyeonggi-do, South Korea.

Abstract

STUDY 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.

DESIGN:

32-channel extracranial EEG and 2-channel thalamic LFP were recorded simultaneously in freely behaving mice to acquire spindles during spontaneous sleep.

SUBJECTS:

Hybrid F1 male mice of C57BL/6J and 129S4/svJae.

MEASUREMENTS AND 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.

CONCLUSION:

Topographically specific sleep spindles show distinctive thalamocortical network behaviors.

KEYWORDS:

high-density EEG; mouse; sleep slow waves; sleep spindles; thalamic LFP; thalamocortical networks; topography

PMID:
25325451
PMCID:
PMC4262960
DOI:
10.5665/sleep.4330
[Indexed for MEDLINE]
Free PMC Article

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