The purpose of this application for a Research Career Development Award is to permit the Principal Investigator (PI) to devote a substantially greater portion of his time for research into the effects of sleep on the control of breathing. During the tenure of this proposes project, the PI will combine mathematical modeling and parameter estimation methodology with experiments on humans to obtain a better understanding of the dynamic mechanisms that lead to respiratory variability and recurrent apnea during sleep. The RCDA will free up sufficient time for him to conduct the proposed studies, as well as to obtain a firm grounding in the clinical and neurophysiological aspects of sleep through reading, increased interactions with experts in the field, and participation in colloquiums. The experience and training obtained through such an opportunity would be invaluable for his current and future development as in independent investigator in sleep physiology, particularly as it pertains to respiratory control. At the same time, the PI will be able to explore the applicability of new approaches derived from nonlinear dynamics, chaos theory and neural networks. The presence within the University of several experts in these new areas, as well as in the neurosciences, provides an ideal environment for the academic growth of the PI. The inclusion of two clinical colleagues, one in pulmonary medicine and the other in sleep disorders, as Co-Investigators in this project will significantly improve the PI's appreciation of the pathophysiological aspects of sleep. In the proposed project, experiments will be performed on both healthy subjects and patients with sleep apnea syndrome to determine the relative importance of chemoresponsiveness, sensitivity of arterial blood gas tensions to ventilatory changes (plant gain), respiratory phase-switching, sleep state changes and upper airway mechanics in mediating sleep-related breathing disorders. Simple noninvasive procedures combined with specially designed computational algorithms will be permit the tracking of chemoresponsiveness, plant gain, and arterial blood gases during sleep. Application of modeling also allows the estimation of the time-course for the 'wakefulness stimulus'. Analysis of the temporal relationships between these factors and changes in upper airway resistance will be used to extend an existing model of the interaction between sleep state and respiratory control.
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