Mathematical Modeling of Circadian/Performance Countermeasures

Metadata Updated: February 28, 2019

We developed and refined our current mathematical model of circadian rhythms to incorporate melatonin as a marker rhythm. We used an existing physiologically based mathematical model of the diurnal variations in plasma melatonin levels. The revised model can predict melatonin amplitude, markers of melatonin phase (melatonin synthesis onset (Synon) and synthesis offset (Synoff)), melatonin suppression by light, and salivary melatonin concentrations. Our model has been validated on several independent data sets. A manuscript of this work has been published. We incorporated wavelength sensitivity into our current mathematical model. We have revised the light input to our model from lux to an irradiance measure (microW/cm2) for both polychromatic and monochromatic light exposures. We have developed a two-channel photoreceptor model, in which one channel is driven by rod/cone input and the other channel is driven by a melanopsin input with peak sensitivity in the short wavelength range (~480nm). Our model can predict the response of the circadian pacemaker to 1-pulse light exposures of 460nm and 555nm at different irradiances to generate fluence-response curves of circadian phase-shifts to polychromatic light. This work has been presented at scientific meetings. A manuscript of this work is in preparation. We developed schedule assessment and countermeasure design software. We have developed a schedule/countermeasure design program that allows a user to interactively design a schedule and to automatically design a mathematically optimal countermeasure regime (intensity, duration, and placement). We have demonstrated this tool to NASA personnel. We have substantially redesigned the user interface for CPSS, the software implementation of our mathematical model, based on feedback from NASA users and operational requirements. We have shown that our methods can be used to design a variety of schedules and countermeasures relevant to NASA operations including shifting sleep wake (slam shifting), sleep deprivation, and non-24 hour schedules. This work has been presented at scientific meetings. A manuscript is in progress. We have begun to explore inter-individual differences in performance. (1) We have begun developing methodologies for determining how optimal model structure may differ by individual. The benefit of the framework is that models are easily understandable by non-mathematicians and that the probability distributions can be approximated by existing data. (2) We have conducted data analysis to quantify differences in model parameter values and we have correlated these model parameter differences with individual characteristics such as age, gender, morningness-eveningness, habitual bedrest duration, and habitual sleep/wake times. We have demonstrated the trait-like characteristics in the robustness of parameters associated with the homeostatic process under experimental light interventions. This work has been presented at scientific meetings.

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Public: This dataset is intended for public access and use. License: U.S. Government Work

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Metadata Created Date August 1, 2018
Metadata Updated Date February 28, 2019

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date August 1, 2018
Metadata Updated Date February 28, 2019
Publisher Space Technology Mission Directorate
Unique Identifier TECHPORT_23211
Maintainer Email
Public Access Level public
Bureau Code 026:00
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Harvest Object Id 506e0048-96c3-4bd0-a32b-e5b8da3d282f
Harvest Source Id 39e4ad2a-47ca-4507-8258-852babd0fd99
Harvest Source Title NASA Data.json
Data First Published 2008-08-01
Homepage URL
Data Last Modified 2018-07-19
Program Code 026:027
Source Datajson Identifier True
Source Hash b9998b304df30f7c71e11e32e4dfeb35000b40a9
Source Schema Version 1.1

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