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Uncovering Physiologic Mechanisms of Circadian Rhythms and Sleep/Wake Regulation through Mathematical Modeling

Division of Sleep Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, Division of Applied Sciences, Harvard University, Cambridge, MA

Glenn Gunzelmann

Air Force Research Laboratory, Mesa, AZ

Hans P. A. Van Dongen

Sleep and Performance Research Center, Washington State University, Spokane, WA

Francis J. Doyle, III

Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA

Elizabeth B. Klerman

Division of Sleep Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, ebklerman{at}hms.harvard.edu

Mathematical models of neurobehavioral function are useful both for understanding the underlying physiology and for predicting the effects of rest-activity-work schedules and interventions on neurobehavioral function. In a symposium titled "Modeling Human Neurobehavioral Performance I: Uncovering Physiologic Mechanisms" at the 2006 Society for Industrial and Applied Mathematics/Society for Mathematical Biology (SIAM/SMB) Conference on the Life Sciences, different approaches to modeling the physiology of human circadian rhythms, sleep, and neurobehavioral performance and their usefulness in understanding the underlying physiology were examined. The topics included key elements of the physiology that should be included in mathematical models, a computational model developed within a cognitive architecture that has begun to include the effects of extended wake on information-processing mechanisms that influence neurobehavioral function, how to deal with interindividual differences in the prediction of neurobehavioral function, the applications of systems biology and control theory to the study of circadian rhythms, and comparisons of these methods in approaching the overarching questions of the underlying physiology and mathematical models of circadian rhythms and neurobehavioral function. A unifying theme was that it is important to have strong collaborative ties between experimental investigators and mathematical modelers, both for the design and conduct of experiments and for continued development of the models.

Key Words: mathematical modeling • circadian • sleep • neurobehavioral performance • cognitive architecture • systems biology

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