Burst-to-Burst Variability in Respiratory Timing, Inspiratory-Phase Spectral Activity, and Inspiratory Neural Network Complexity in Urethane-Anesthetized C57BL/6 Mice in vivo

  • Hyun Hye Chun
  • Evan T. Spiegel
  • Irene C. Solomon
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 605)

Recent work from our laboratory has focused on identifying burst-to-burst variability in temporal and spectral characteristics for 5-minute time series segments of basal inspiratory motor discharges from urethane-anesthetized adult C57BL/6 mice. The current investigation, as the continuation of our previous studies, examined short- and long-term burst-to-burst variability in temporal and spectral components as well as in complexity, which reflects the central respiratory network dynamics. All measures were assessed by quantitative poincaré plot analyses and the determination of the coefficient of variation.


Breathing Frequency Spectral Activity Approximate Entropy Burst Data Plot Structure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Brennan, M., Palaniswamim, M. and Kamen, K. (2001) Do existing measure of poincare plots geometry reflect nonlinear features of heart rate variability? IEEE Trans. Biomed. Eng. 48(11), 1342–1347.CrossRefPubMedGoogle Scholar
  2. Gonsenhauser, I., Wilson, C.G., Han, F., Strohl, K.P, and Dick, T.E. (2004) Strain differences in murine ventilatory behavior persist after urethane anesthesia. J. Appl. Physiol. 97(3), 888–894.CrossRefPubMedGoogle Scholar
  3. O’Neal, M.H. 3rd, Spiegel, E.T., Chon, K.H, and Solomon, I.C. (2005) Time-frequency representation of inspiratory motor output in anesthetized C57BL/6 mice in vivo. J. Neurophysiol. 93(3), 1762–1775.CrossRefPubMedGoogle Scholar
  4. Pincus, S.M. and Goldberger, A.L. (1994) Physiological time-series analysis: what does regularity quantify? Am. J. Physio. 266, H1643–H1656.Google Scholar
  5. Pincus, S.M. (1991) Approximate entropy as a measure of system complexity. Proc. Natl. Acad. Sci. 88, 2297–2301.CrossRefPubMedGoogle Scholar
  6. Tulppo, M.P., Mäkikallio, T.H., Takala, T.E.S., Seppänen, T. and Huikuri, H.V. (1996) Quantitative beat-to-beat analysis of heart rate dynamics during exercise. Am. J. Physio. 271, H244–H252.Google Scholar

Copyright information

© Springer 2008

Authors and Affiliations

  • Hyun Hye Chun
  • Evan T. Spiegel
  • Irene C. Solomon

There are no affiliations available

Personalised recommendations