Literature DB >> 16147894

Comparison of amplitude recovery dynamics of two limit cycle oscillator models of the human circadian pacemaker.

Premananda Indic1, Daniel B Forger, Melissa A St Hilaire, Dennis A Dean, Emery N Brown, Richard E Kronauer, Elizabeth B Klerman, Megan E Jewett.   

Abstract

At an organism level, the mammalian circadian pacemaker is a two-dimensional system. For these two dimensions, phase (relative timing) and amplitude of the circadian pacemaker are commonly used. Both the phase and the amplitude (A) of the human circadian pacemaker can be observed within multiple physiological measures--including plasma cortisol, plasma melatonin, and core body temperature (CBT)--all of which are also used as markers of the circadian system. Although most previous work has concentrated on changes in phase of the circadian system, critically timed light exposure can significantly reduce the amplitude of the pacemaker. The rate at which the amplitude recovers to its equilibrium level after reduction can have physiological significance. Two mathematical models that describe the phase and amplitude dynamics of the pacemaker have been reported. These models are essentially equivalent in predictions of phase and in predictions of amplitude recovery for small changes from an equilibrium value (A = 1), but are markedly different in the prediction of recovery rates when A < 0.6. To determine which dynamic model best describes the amplitude recovery observed in experimental data; both models were fit to CBT data using a maximum likelihood procedure and compared using Akaike's Information Criterion (AIC). For all subjects, the model with the lower recovery rate provided a better fit to data in terms of AIC, supporting evidence that the amplitude recovery of the endogenous pacemaker is slow at low amplitudes. Experiments derived from model predictions are proposed to test the influence of low amplitude recovery on the physiological and neurobehavioral functions.

Entities:  

Keywords:  NASA Discipline Space Human Factors; Non-NASA Center

Mesh:

Year:  2005        PMID: 16147894      PMCID: PMC3797655          DOI: 10.1080/07420520500180371

Source DB:  PubMed          Journal:  Chronobiol Int        ISSN: 0742-0528            Impact factor:   2.877


  19 in total

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Authors:  M E Jewett; D B Forger; R E Kronauer
Journal:  J Biol Rhythms       Date:  1999-12       Impact factor: 3.182

2.  A simpler model of the human circadian pacemaker.

Authors:  D B Forger; M E Jewett; R E Kronauer
Journal:  J Biol Rhythms       Date:  1999-12       Impact factor: 3.182

3.  A statistical model of the human core-temperature circadian rhythm.

Authors:  E N Brown; Y Choe; H Luithardt; C A Czeisler
Journal:  Am J Physiol Endocrinol Metab       Date:  2000-09       Impact factor: 4.310

4.  Melatonin rhythm observed throughout a three-cycle bright-light stimulus designed to reset the human circadian pacemaker.

Authors:  T L Shanahan; R E Kronauer; J F Duffy; G H Williams; C A Czeisler
Journal:  J Biol Rhythms       Date:  1999-06       Impact factor: 3.182

5.  Bright light induction of strong (type 0) resetting of the human circadian pacemaker.

Authors:  C A Czeisler; R E Kronauer; J S Allan; J F Duffy; M E Jewett; E N Brown; J M Ronda
Journal:  Science       Date:  1989-06-16       Impact factor: 47.728

6.  The sleep and performance of shift workers.

Authors:  A J Tilley; R T Wilkinson; P S Warren; B Watson; M Drud
Journal:  Hum Factors       Date:  1982-12       Impact factor: 2.888

7.  Light-induced suppression of endogenous circadian amplitude in humans.

Authors:  M E Jewett; R E Kronauer; C A Czeisler
Journal:  Nature       Date:  1991-03-07       Impact factor: 49.962

8.  Dynamic resetting of the human circadian pacemaker by intermittent bright light.

Authors:  D W Rimmer; D B Boivin; T L Shanahan; R E Kronauer; J F Duffy; C A Czeisler
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2000-11       Impact factor: 3.619

9.  Association of sleep-wake habits in older people with changes in output of circadian pacemaker.

Authors:  C A Czeisler; M Dumont; J F Duffy; J D Steinberg; G S Richardson; E N Brown; R Sánchez; C D Ríos; J M Ronda
Journal:  Lancet       Date:  1992-10-17       Impact factor: 79.321

10.  Circadian regulation dominates homeostatic control of sleep length and prior wake length in humans.

Authors:  S H Strogatz; R E Kronauer; C A Czeisler
Journal:  Sleep       Date:  1986-06       Impact factor: 5.849

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  6 in total

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

Authors:  Peter McCauley; Leonid V Kalachev; Daniel J Mollicone; Siobhan Banks; David F Dinges; Hans P A Van Dongen
Journal:  Sleep       Date:  2013-12-01       Impact factor: 5.849

2.  Scaling behavior of human locomotor activity amplitude: association with bipolar disorder.

Authors:  Premananda Indic; Paola Salvatore; Carlo Maggini; Stefano Ghidini; Gabriella Ferraro; Ross J Baldessarini; Greg Murray
Journal:  PLoS One       Date:  2011-05-31       Impact factor: 3.240

3.  Suppressed cellular oscillations in after-hours mutant mice are associated with enhanced circadian phase-resetting.

Authors:  Clare Guilding; Fiona Scott; David A Bechtold; Timothy M Brown; Sven Wegner; Hugh D Piggins
Journal:  J Physiol       Date:  2012-12-03       Impact factor: 5.182

4.  Optimal schedules of light exposure for rapidly correcting circadian misalignment.

Authors:  Kirill Serkh; Daniel B Forger
Journal:  PLoS Comput Biol       Date:  2014-04-10       Impact factor: 4.475

5.  Entrainment of circadian rhythms to irregular light/dark cycles: a subterranean perspective.

Authors:  Danilo E F L Flôres; Milene G Jannetti; Veronica S Valentinuzzi; Gisele A Oda
Journal:  Sci Rep       Date:  2016-10-04       Impact factor: 4.379

6.  Macroscopic models for networks of coupled biological oscillators.

Authors:  Kevin M Hannay; Daniel B Forger; Victoria Booth
Journal:  Sci Adv       Date:  2018-08-03       Impact factor: 14.136

  6 in total

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