Macroscopic Models for Human Circadian Rhythms. Issue 6 (December 2019)

• Record Type: Journal Article
• Authors: Hannay, Kevin M.; Booth, Victoria; Forger, Daniel B.
• Is Part Of: Journal of biological rhythms. Volume 34:Issue 6(2019)
• Page Start: 658
• Page End: 671
• Publication Date: 2019-12
• Subjects: mathematical modeling -- circadian rhythms -- chronotype -- human -- phase response curve; Biological rhythms -- Periodicals; Circadian rhythms -- Periodicals; 571.77
• DOI: 10.1177/0748730419878298
• Languages: English
• ISSNs: 0748-7304

Abstract

Mathematical models have a long and influential history in the study of human circadian rhythms. Accurate predictive models for the human circadian light response have been used to study the impact of a host of light exposures on the circadian system. However, generally, these models do not account for the physiological basis of these rhythms. We illustrate a new paradigm for deriving models of the human circadian light response. Beginning from a high-dimensional model of the circadian neural network, we systematically derive low-dimensional models using an approach motivated by experimental measurements of circadian neurons. This systematic reduction allows for the variables and parameters of the derived model to be interpreted in a physiological context. We fit and validate the resulting models to a library of experimental measurements. Finally, we compare model predictions for experimental measurements of light levels and discuss the differences between our model's predictions and previous models. Our modeling paradigm allows for the integration of experimental measurements across the single-cell, tissue, and behavioral scales, thereby enabling the development of accurate low-dimensional models for human circadian rhythms.