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This article is part of the supplement: Twenty First Annual Computational Neuroscience Meeting: CNS*2012

Open Access Poster presentation

A closed model for the respiratory system in mammals

Choongseok Park1*, Yaroslav Molkov2, Alona Ben-Tal3, Natalia Shevtsova4, Jeffrey Smith5, Ilya Rybak4 and Jonathan Rubin1

Author Affiliations

1 Department of Mathematics, University of Pittsburgh, Pittsburgh, PA15260, USA

2 Indiana University - Purdue University Indianapolis, Department of Mathematical Sciences, Indianapolis, IN 46202, USA

3 Institute of Information and Mathematical Sciences, Massey University, Auckland, New Zealand

4 Drexel University College of Medicine, Philadelphia, PA 19129, USA

5 Cellular and Systems Neurobiology Section, Laboratory of Neural Control, NINDS, Bethesda, MD 20892-3700, USA

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BMC Neuroscience 2012, 13(Suppl 1):P51  doi:10.1186/1471-2202-13-S1-P51

The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1471-2202/13/S1/P51


Published:16 July 2012

© 2012 Park et al; licensee BioMed Central Ltd.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Poster presentation

The interactions between rhythmogenic neuronal networks and physiological systems are crucial components in understanding how a system maintains homeostasis under diverse circumstances. Various aspects of such interactions should be addressed including how rhythms are generated in neuronal networks, how feedback signals interact with neuronal networks to regulate levels of important physiological quantities, and how changes in demands on the system can be handled in a way that restores homeostasis.

In this work, we explore these issues in the context of neuronal networks in the mammalian brainstem that generate the respiratory rhythm when isolated from the physiological systems that drive actual breathing [1]. These networks include neuronal components within the Bötzinger (BötC) and pre-Bötzinger (pre-BötC) complexes and the retrotrapezoid nucleus/parafacial respiratory group (RTN/pFRG). Experimental results on respiratory rhythm generation have suggested that neurons within the BötC and pre-BötC are responsible for the generation of primary respiratory rhythms, which are modulated by oscillations in the RTN/pFRG. Previous computational work has elucidated a possible set of mechanisms through which these brain stem neurons interact and produce a variety of experimental results [2].

Separate past work has developed a physiologically detailed yet tractable model of respiratory physiology [3]. This model is comprised of a very simplified version of a neuronal network oscillator that generates respiratory rhythms, an integrator that delivers respiratory output , and lung components responsible for air exchange. This earlier study considered reasonable ways to link the neuronal oscillator/integrator with these physiological components in a closed loop feedback system to achieve respiratory frequency and amplitude control.

In our work, we simulate and analyze a model that links the detailed neuronal rhythm generator with the physiological lung components. We consider the roles of mechanical and chemoreceptive feedback signals in maintaining stable respiratory rhythms and in responding to metabolic or environmental perturbations. In particular, we study the response to hypercapnia, or excessive carbon dioxide [4]. The idea is that excessive exposure to CO2 may lead to CO2 accumulation in the blood, which will recruit certain neuronal elements in the RTN/pFRG and alter the drive to core rhythmogenic elements. Changes in rhythmic output patterns activate certain muscles that alter breathing in a way that restores CO2 homeostasis. We analyze the roles of neurons’ intrinsic dynamic features, the architecture and strengths of synaptic connections among neurons, and the roles of particular feedback systems in achieving baseline rhythms and appropriate responses to perturbations.

Acknowledgements

This work is done in collaboration with Alona Ben-Tal, Ilya Rybak, Natalia Shevtsova, and Jeffrey Smith.

References

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