Robustness of respiratory rhythm generation across dynamic regimes

• Published in: PLoS computational biology Vol. 15; no. 7; p. e1006860
• Main Authors: Rubin, Jonathan E, Smith, Jeffrey C
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.07.2019; Public Library of Science (PLoS)
• Subjects: Animals; Biology and Life Sciences; Central pattern generator; Computational neuroscience; Computer and Information Sciences; Computer simulation; Medicine and Health Sciences; Models, Neurological; Neurons; Neurons - physiology; Neurosciences; Observations; Ordinary differential equations; Physical Sciences; Physiological aspects; Respiration; Rhythm; System theory; Systems analysis; United States; United States > US; Pittsburgh Pennsylvania; Pennsylvania
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1006860

A central issue in the study of the neural generation of respiratory rhythms is the role of the intrinsic pacemaking capabilities that some respiratory neurons exhibit. The debate on this issue has occurred in parallel to investigations of interactions among respiratory network neurons and how these contribute to respiratory behavior. In this computational study, we demonstrate how these two issues are inextricably linked. We use simulations and dynamical systems analysis to show that once a conditional respiratory pacemaker, which can be tuned across oscillatory and non-oscillatory dynamic regimes in isolation, is embedded into a respiratory network, its dynamics become masked: the network exhibits similar dynamical properties regardless of the conditional pacemaker node's tuning, and that node's outputs are dominated by network influences. Furthermore, the outputs of the respiratory central pattern generator as a whole are invariant to these changes of dynamical properties, which ensures flexible and robust performance over a wide dynamic range.