Abstract
Our ultimate goal is to study the mechanisms of cross-level integration and synergy of network and intrinsic neuronal properties, and the role of this integration in the behavior of biological neural networks and systems. In the present work, we have selected a relatively simple mammalian system, which produces the respiratory rhythm and pattern, as an example for investigation of the above issues.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
D. W. Richter and D. Ballantyne, D. A three phase theory about the basic respiratory pattern generator. In: M. Schlafke, H. Koepchen, and W. See (Eds.) Central Neurone Environment, Berlin: Springer, 1983, pp. 164–174.
D. Richter et. al., How is the respiratory rhythm generated? A model. Nests Pln:siol. Sri. I (1986) 109–112.
J. Champagnat and D. W. Richter, The roles of K+ conductance in expiratory pattern generation in anaesthetized cats. J. Phvsiol. Lund. 479 (1994) 127–138.
O. Pierrefiche et al.,Calcium-dependent conductances control neurones involved in termination of inspiration in cats. New - usci. Letters,184 (1995)101–104.
D. W. Richter et al.,Calcium currents and calcium-dependent potassium currents in mammalian medullary respiratory neurons. J. Phvsiol. 470 (1993) 23–33.
S. M. Botros and E. N. Bruce, Neural network implementation of the three-phase model of respiratory rhythm generation. Biol. Ci’bern. 63 (1990)143–153.
J. A. Duffin, A model of respiratory rhythm generation. Neuroreport 2 (1991) 623–626.
J. A. Duffin et al., Breathing rhythm generation: focus on the rostral ventrolateral medulla. News in Physiol. Sciences. 10 (1995) 133–140.
S. Geman and M. Miller, Computer simulation ofbrainstem respiratory activity. J. Appl. Phvsiol. 41 (1976) 931–938.
A. Gottschalk et al. Computational aspects of the respiratory pattern generator. Neural Comput. 6 (1994) 56–68.
M. D. Ogilvie et al., A network model of respiratory rhythmogenesis. Am. J. Phvsiol. 263 (1992) R962 - R975.
J. E. Rubio, A new mathematical model of the respiratory center. Bull. Made. Biophrs. 34 (1972) 486–481.
J. Champagnat el al., Voltage-dependent currents in neurons of the nuclei of the solitary tract of rat brain-stem slices. PJlügers Arch. 406 (1986) 372–379.
M. S. Dekin and P. A. Getting, In vitro characterization of neurons in the ventral part of the nucleus tractus solitarius. II. Ionic basis for repetitive firing patterns. J. Neurophvsiol. 58 (1987) 215–229.
J. R. Huguenard and D. A. McCormick, Vclamp and Cclamp. A Computational Simulation of Single Thalamic Relay and Cortical Pyramidal Neurons. Neural Simulation Instruction Manual, 1991.
D. W. Richter. Rhythmogenesis of respiratory movements. In: D. Jordan (Ed.) Central Control of Autonomic Nervous System. Harwood Academic, 1996 (in press).
F. Kreuter et al.. Morphological and electrical description of medullary respiratory neurons of the cat. L’fingers Arch. 372 (1977) 7–16. 1977.
M. I. Cohen, Neurogenesis of respiratory rhythm in the mammal. Phvsiol. Rev. 59 (1979) 1105–1173.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1997 Springer Science+Business Media New York
About this chapter
Cite this chapter
Rybak, I.A., Paton, J.F.R., Schwaber, J.S. (1997). Synergism of Cellular and Network Mechanisms in Respiratory Pattern Generation. In: Bower, J.M. (eds) Computational Neuroscience. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9800-5_76
Download citation
DOI: https://doi.org/10.1007/978-1-4757-9800-5_76
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4757-9802-9
Online ISBN: 978-1-4757-9800-5
eBook Packages: Springer Book Archive