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J Neurophysiol 100: 1770-1799, 2008. First published July 23, 2008; doi:10.1152/jn.90416.2008
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Reconfiguration of the Pontomedullary Respiratory Network: A Computational Modeling Study With Coordinated In Vivo Experiments

I. A. Rybak1, R. O'Connor2, A. Ross2, N. A. Shevtsova1, S. C. Nuding2, L. S. Segers2, R. Shannon2, T. E. Dick3, W. L. Dunin-Barkowski4,5, J. M. Orem5, I. C. Solomon6, K. F. Morris2 and B. G. Lindsey2

1Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, Pennsylvania; 2Department of Molecular Pharmacology and Physiology and Neuroscience Program, School of Biomedical Sciences, University of South Florida College of Medicine, Tampa, Florida; 3Departments of Medicine and Neurosciences, Case Western Reserve University, Cleveland, Ohio; 4Department of Neuro-Optical Systems, Scientific-Research Institute for System Analysis, Russian Academy of Sciences, Moscow, Russia; 5Department of Physiology, Texas Tech University Health Sciences Center, Lubbock, Texas; and 6Department of Physiology and Biophysics, State University of New York, Stony Brook, New York

Submitted 28 March 2008; accepted in final form 16 July 2008

A large body of data suggests that the pontine respiratory group (PRG) is involved in respiratory phase-switching and the reconfiguration of the brain stem respiratory network. However, connectivity between the PRG and ventral respiratory column (VRC) in computational models has been largely ad hoc. We developed a network model with PRG-VRC connectivity inferred from coordinated in vivo experiments. Neurons were modeled in the "integrate-and-fire" style; some neurons had pacemaker properties derived from the model of Breen et al. We recapitulated earlier modeling results, including reproduction of activity profiles of different respiratory neurons and motor outputs, and their changes under different conditions (vagotomy, pontine lesions, etc.). The model also reproduced characteristic changes in neuronal and motor patterns observed in vivo during fictive cough and during hypoxia in non-rapid eye movement sleep. Our simulations suggested possible mechanisms for respiratory pattern reorganization during these behaviors. The model predicted that network- and pacemaker-generated rhythms could be co-expressed during the transition from gasping to eupnea, producing a combined "burst-ramp" pattern of phrenic discharges. To test this prediction, phrenic activity and multiple single neuron spike trains were monitored in vagotomized, decerebrate, immobilized, thoracotomized, and artificially ventilated cats during hypoxia and recovery. In most experiments, phrenic discharge patterns during recovery from hypoxia were similar to those predicted by the model. We conclude that under certain conditions, e.g., during recovery from severe brain hypoxia, components of a distributed network activity present during eupnea can be co-expressed with gasp patterns generated by a distinct, functionally "simplified" mechanism.


Address for reprint requests and other correspondence: B. G. Lindsey, Dept. of Molecular Pharmacology and Physiology, School of Biomedical Sciences, College of Medicine, University of South Florida, 12901 Bruce B. Downs Blvd., Tampa, FL 33612 (E-mail: blindsey{at}health.usf.edu)




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