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Characterization of the Bout Durations of Sleep and Wakefulness: New Metrics for Summarizing Sleep, Journal of Neuroscience Methods


Study objectives:Develop a new statistical approach to describe the microarchitecture of wakefulness and sleep in mice; (b) evaluate differences among inbred strains in this microarchitecture; (c) compare results when data are scored in 4-s versus 10-s epochs. Design Studies in male mice of four inbred strains: AJ, C57BL/6, DBA and PWD. EEG/EMG were recorded for 24 hand scored independently in 4-s and 10-s epochs. Measurements and results: Distribution of bout durations of wakefulness, NREM and REM sleep in mice has two distinctcomponents, i.e., short and longer bouts. This is described as a spike (short bouts) and slab (longer bouts) distribution, a particular type of mixturemodel. The distribution in any state depends on the state the mouse is transitioning from and can be characterized by three parameters: the number of such bouts conditional on the previous state, the size of the spike, and the average length of the slab. While conventional statistics such as time spent in state, average bout duration, andnumberof boutsshow some differences between inbred strains, this new statistical approach reveals more major differences. The major difference between strains is their ability to sustain long bouts of NREM sleep or wakefulness. Scoring mouse sleep/wake in 4-s epochs offered little new information when using conventional metrics but did when evaluating the microarchitecture based on this new approach. Conclusions : Standard statistical approaches do not adequately characterize the microarchitecture of mouse behavioral state. Approaches based on a spike-and-slab provide a quantitative description.




Blake McShane, R. J. Galante, S. Jensen, N. Naidoo, Pack A.I., A. J. Wyner

Date Published



McShane, Blake, R. J. Galante, S. Jensen, N. Naidoo, Pack A.I., and A. J. Wyner. 2010. Characterization of the Bout Durations of Sleep and Wakefulness: New Metrics for Summarizing Sleep. Journal of Neuroscience Methods.(2): 321-333.


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