Dynamic circadian modulation in a biomathematical model for the effects of sleep and sleep loss on waking neurobehavioral performance

Peter McCauley, Leonid V. Kalachev, Daniel J. Mollicone, Siobhan Banks, David F. Dinges, Hans P.A. Van Dongen

Research output: Contribution to journalArticlepeer-review

71 Scopus citations

Abstract

Recent experimental observations and theoretical advances have indicated that the homeostatic equilibrium for sleep/wake regulation-and thereby sensitivity to neurobehavioral impairment from sleep loss-is modulated by prior sleep/wake history. This phenomenon was predicted by a biomathematical model developed to explain changes in neurobehavioral performance across days in laboratory studies of total sleep deprivation and sustained sleep restriction. The present paper focuses on the dynamics of neurobehavioral performance within days in this biomathematical model of fatigue. Without increasing the number of model parameters, the model was updated by incorporating time-dependence in the amplitude of the circadian modulation of performance. The updated model was calibrated using a large dataset from three laboratory experiments on psychomotor vigilance test (PVT) performance, under conditions of sleep loss and circadian misalignment; and validated using another large dataset from three different laboratory experiments. The time-dependence of circadian amplitude resulted in improved goodness-of-fit in night shift schedules, nap sleep scenarios, and recovery from prior sleep loss. The updated model predicts that the homeostatic equilibrium for sleep/wake regulation-and thus sensitivity to sleep loss-depends not only on the duration but also on the circadian timing of prior sleep. This novel theoretical insight has important implications for predicting operator alertness during work schedules involving circadian misalignment such as night shift work.

Original languageEnglish
Pages (from-to)1987-1997
Number of pages11
JournalSleep
Volume36
Issue number12
DOIs
StatePublished - Dec 1 2013

Keywords

  • Alertness
  • Allostatic regulation
  • Dynamic circadian amplitude
  • Fatigue and performance models
  • Markov chain Monte Carlo (MCMC)
  • Model-based fatigue risk management
  • Nonlinear interaction
  • Sigmoidal dynamics
  • Sleep deprivation
  • Sleep homeostasis

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