A mathematical model of ultradian sleep-wake regulation in rodents

Hao Wang, Farid Yaghouby, Sridhar Sunderam

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Rodent models are widely used for the experimental analysis of sleep. While this is motivated by similarities in brain circuitry and electrophysiological rhythms, unlike the circadian sleep-wake cycle in humans, rodent sleep is polyphasic, containing multiple bouts of sleep and wake minutes to hours in duration over the course of a day. Each sleep bout is punctuated by several brief arousals several seconds to minutes long. Physiologically motivated mathematical models replicate the shorter timescale of arousal within sleep, but not the longer one representing prolonged wakefulness. Here, we adapt a previously published 'flip-flop' model of human sleep to capture the ultradian alternation of sleep and wakefulness in mice on the longer timescale. The resulting model reproduces both the mean durations of alternating sleep and wake bouts as well as the circadian trends in their bout durations documented in our experiments on mice.

Original languageEnglish
Title of host publication2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Pages1656-1659
Number of pages4
ISBN (Electronic)9781457702204
DOIs
StatePublished - Oct 13 2016
Event38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States
Duration: Aug 16 2016Aug 20 2016

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2016-October
ISSN (Print)1557-170X

Conference

Conference38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Country/TerritoryUnited States
CityOrlando
Period8/16/168/20/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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