Understanding the control of breathing is an important goal in integrative biology and medicine. Sleep disorders in newborns and adults that disrupt breathing have been implicated in the development of pulmonary and systemic hypertension and other disorders and risks. The goal of this collaborative project is to develop a unified model of the brainstem respiratory network and to identify potential sites where abnormalities can disrupt breathing and its control. Detailed biophysical and large-scale simulations will guide associated in vivo and in vitro neurophysiological and pharmacological experiments to test model-based hypotheses on sub-cellular, cellular, network and systems level mechanisms that transform the respiratory network during the transitions between eupnea and hyperventilation apnea, from eupnea to gasping, and during sleep and waking. Experimental feedback will be used to iteratively tune the model. The project has five aims: 1. Develop a comprehensive computational model of the ventrolateral medullary """"""""core"""""""" respiratory network and use it as a tool for interactive modeling/experimental studies on the neural control of breathing. 2. Evaluate interactions among the medullary central pattern generator (CPG), the pontine respiratory group, the nuclei of the solitary tract, and the raphe nuclei. 3. Elucidate mechanisms underlying network reconfiguration and the respiratory motor patterns associated with transient changes in chemical drive and gasping. 4. Identify inputs to the pontine-medullary respiratory network that can produce the respiratory motor patterns observed during the sleep-wake cycle and that can cause sleep apnea. These inputs or their absence are ultimately responsible for sleep disorders. 5. Test biophysical, cellular, and network mechanisms for a) rate and synchrony """"""""coding"""""""" and network stability. This project will bring together researchers from universities in five states. Members of the group have a common interest in the control of breathing, complementary areas of expertise, large and growing experimental databases, and long-standing collegial relationships. The project will be a catalyst for the development and sharing of advanced multi-array recording technologies and computational methods, modeling and simulation tools, and large data sets. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS046062-03
Application #
6797205
Study Section
Special Emphasis Panel (ZRG1-IFCN-5 (50))
Program Officer
Liu, Yuan
Project Start
2002-09-30
Project End
2007-08-31
Budget Start
2004-09-01
Budget End
2005-08-31
Support Year
3
Fiscal Year
2004
Total Cost
$423,684
Indirect Cost
Name
University of South Florida
Department
Physiology
Type
Schools of Medicine
DUNS #
069687242
City
Tampa
State
FL
Country
United States
Zip Code
33612
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Nuding, Sarah C; Segers, Lauren S; Baekey, David M et al. (2009) Pontine-ventral respiratory column interactions through raphe circuits detected using multi-array spike train recordings. J Neurophysiol 101:2943-60
Rybak, I A; O'Connor, R; Ross, A et al. (2008) Reconfiguration of the pontomedullary respiratory network: a computational modeling study with coordinated in vivo experiments. J Neurophysiol 100:1770-99
Dick, Thomas E; Shannon, Roger; Lindsey, Bruce G et al. (2008) Pontine respiratory-modulated activity before and after vagotomy in decerebrate cats. J Physiol 586:4265-82
Segers, Lauren S; Nuding, Sarah C; Dick, Thomas E et al. (2008) Functional connectivity in the pontomedullary respiratory network. J Neurophysiol 100:1749-69
Fraigne, Jimmy J; Dunin-Barkowski, Witali L; Orem, John M (2008) Effect of hypercapnia on sleep and breathing in unanesthetized cats. Sleep 31:1025-33
Lovering, Andrew T; Fraigne, Jimmy J; Dunin-Barkowski, Witali L et al. (2006) Medullary respiratory neural activity during hypoxia in NREM and REM sleep in the cat. J Neurophysiol 95:803-10
Lindsey, Bruce G; Gerstein, George L (2006) Two enhancements of the gravity algorithm for multiple spike train analysis. J Neurosci Methods 150:116-27

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