A Model-Based Approach to Optimizing Ultradian Forced Desynchrony Protocols for Human Circadian Research

Stack, Nora; Barker, David H.; Carskadon, Mary A.; Behn, Cecilia Diniz

doi:10.1177/0748730417730488

Cited by 10 publications

(10 citation statements)

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“…One advantage of fitting light sensitivity parameters compared with tau is that they may be easier to obtain experimentally. Accurate assessment of an individual's circadian period requires desynchronization of the circadian system from the restactivity cycle, via a forced desynchrony protocol (Kleitman, 1963;Klerman et al, 1996;Stack et al, 2017), which is highly time and resource intensive. Current approaches to measuring circadian light sensitivity-either via phase shifting or melatonin suppression-also require extended lab visits.…”

Section: Discussionmentioning

confidence: 99%

The Role of Light Sensitivity and Intrinsic Circadian Period in Predicting Individual Circadian Timing

et al. 2020

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There is large interindividual variability in circadian timing, which is underestimated by mathematical models of the circadian clock. Interindividual differences in timing have traditionally been modeled by changing the intrinsic circadian period, but recent findings reveal an additional potential source of variability: large interindividual differences in light sensitivity. Using an established model of the human circadian clock with real-world light recordings, we investigated whether changes in light sensitivity parameters or intrinsic circadian period could capture variability in circadian timing between and within individuals. Healthy participants ( n = 12, aged 18-26 years) underwent continuous light monitoring for 3 weeks (Actiwatch Spectrum). Salivary dim-light melatonin onset (DLMO) was measured each week. Using the recorded light patterns, a sensitivity analysis for predicted DLMO times was performed, varying 3 model parameters within physiological ranges: (1) a parameter determining the steepness of the dose-response curve to light ( p), (2) a parameter determining the shape of the phase-response curve to light ( K), and (3) the intrinsic circadian period ( tau). These parameters were then fitted to obtain optimal predictions of the three DLMO times for each individual. The sensitivity analysis showed that the range of variation in the average predicted DLMO times across participants was 0.65 h for p, 4.28 h for K, and 3.26 h for tau. The default model predicted the DLMO times with a mean absolute error of 1.02 h, whereas fitting all 3 parameters reduced the mean absolute error to 0.28 h. Fitting the parameters independently, we found mean absolute errors of 0.83 h for p, 0.53 h for K, and 0.42 h for tau. Fitting p and K together reduced the mean absolute error to 0.44 h. Light sensitivity parameters captured similar variability in phase compared with intrinsic circadian period, indicating they are viable targets for individualizing circadian phase predictions. Future prospective work is needed that uses measures of light sensitivity to validate this approach.

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Section: Discussionmentioning

confidence: 99%

The Role of Light Sensitivity and Intrinsic Circadian Period in Predicting Individual Circadian Timing

et al. 2020

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“…Another approach to study the periodicity of human circadian rhythms is the forced desynchrony (FD) protocol (Minors and Waterhouse, 1981;Schmidt et al, 2007;Stack et al, 2017), pioneered by Kleitman (1987). This protocol exposes participants to a "day" that is significantly longer (e.g., 28, 40 h) or shorter (e.g., 20 h) than the 24-h day.…”

Section: Introductionmentioning

confidence: 99%

Living Without Temporal Cues: A Case Study

Bonmatí-Carrión

Revell

Cook³

et al. 2020

Front. Physiol.

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Isolation from external time cues allows endogenous circadian rhythmicity to be demonstrated. In this study, also filmed as a television documentary, we assessed rhythmic changes in a healthy man time isolated in a bunker for 9 days/nights. During this period the lighting conditions were varied between: (1) self-selected light/dark cycle, (2) constant dim light, and (3) light/dark cycle with early wake up. A range of variables was assessed and related to the sleep-wake cycle, psychomotor and physical performance and clock-time estimation. This case study using modern non-invasive monitoring techniques emphasizes how different physiological circadian rhythms persist in temporal isolation under constant dim light conditions with different waveforms, free-running with a period (τ) between 24 and 25 h. In addition, a significant correlation between time estimation and mid-sleep time, a proxy for circadian phase, was demonstrated.

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“…One example is the forced desynchrony (FD) protocol that causes desynchronization of the endogenous circadian rhythm from the rest-activity cycle by placing an individual in a non-entrainable light-dark (LD) cycle. Modeling using 20-30-hr cycles (Klerman et al, 1996) and ultradian cycles (e.g.,7 hr) (Stack, Barker, Carskadon, & Diniz Behn, 2017) has been performed. The models can be used to assess the influence of study design on the estimation of endogenous period in these FD protocols (Klerman et al, 1996;Stack et al, 2017).…”

Section: Effects Of Light On the Human Circadian Pacemakermentioning

confidence: 99%

Mathematical modeling of circadian rhythms

Asgari-Targhi

Klerman

2018

WIREs Mechanisms of Disease

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Circadian rhythms are endogenous~24-hr oscillations usually entrained to daily environmental cycles of light/dark. Many biological processes and physiological functions including mammalian body temperature, the cell cycle, sleep/wake cycles, neurobehavioral performance, and a wide range of diseases including metabolic, cardiovascular, and psychiatric disorders are impacted by these rhythms. Circadian clocks are present within individual cells and at tissue and organismal levels as emergent properties from the interaction of cellular oscillators. Mathematical models of circadian rhythms have been proposed to provide a better understanding of and to predict aspects of this complex physiological system. These models can be used to: (a) manipulate the system in silico with specificity that cannot be easily achieved using in vivo and in vitro experimental methods and at lower cost, (b) resolve apparently contradictory empirical results, (c) generate hypotheses, (d) design new experiments, and (e) to design interventions for altering circadian rhythms. Mathematical models differ in structure, the underlying assumptions, the number of parameters and variables, and constraints on variables. Models representing circadian rhythms at different physiologic scales and in different species are reviewed to promote understanding of these models and facilitate their use. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models K E Y W O R D S biological oscillators, circadian clock, circadian rhythms, dynamic systems, mathematical modeling, statistical modeling BOX 1 CIRCADIAN MODELINGCircadian clocks are present within individual cells, and communication among multiple cells gives rise to emergent properties at the tissue level. In mammals, both the master circadian clock in the suprachiasmatic nucleus and tissuelevel peripheral clocks have major effects at the organism level on numerous key physiological functions, including sleep/wake cycles, metabolism, cardiovascular function, reproduction, immune function, neurobehavioral performance, and mood. Misalignment between the master clock and peripheral clocks within an organism, or misalignment between an organism's clocks and its external environment, has adverse physiological consequences. When circadian interventions are needed to improve physiological function, a multiscale understanding of circadian rhythmicity therefore is essential to accurately manipulate this complex oscillatory system. Mathematical modeling is an essential tool to study and analyze complex physiological systems. It has been used to provide insight into the circadian system at multiple levels (i.e., organism, multi-cellular, cellular, molecular, genetic), to design new experiments, and to manipulate and control the components of the system in silico with specificity that

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A Model-Based Approach to Optimizing Ultradian Forced Desynchrony Protocols for Human Circadian Research

Cited by 10 publications

References 46 publications

The Role of Light Sensitivity and Intrinsic Circadian Period in Predicting Individual Circadian Timing

The Role of Light Sensitivity and Intrinsic Circadian Period in Predicting Individual Circadian Timing

Living Without Temporal Cues: A Case Study

Mathematical modeling of circadian rhythms

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