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What Does the Multi-peaked Respiratory Output Pattern Tell Us About the Respiratory Pattern Generating Neuronal Network?

  • Makio Ishiguro
  • Shigeharu Kawai
  • Yasumasa Okada
  • Yoshitaka Oku
  • Fumikazu Miwakeichi
  • Yoshiyasu Tamura
  • Amit Lal
Conference paper
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 669)

Abstract

The respiratory neuronal network activity can be optically recorded from the ventral medulla of the in vitro brainstem-spinal cord preparation using a voltage-sensitive dye. To assess the spatiotemporal dynamics of respiratory-related regions of the ventral medulla, we developed a novel non-linear response model called the sigmoid and transfer function model. It regards the respiratory motor activity recorded from the fourth cervical ventral root (C4VR) as the response to optical signals from pixels within respiratory-related regions. When the C4VR activity had less than three peaks, optical time series of a single suitably chosen pixel could precisely estimate the activity. However, it was difficult to find a single explanatory pixel for multi-peaked C4VR activity. In this paper, we show that the multi-input single-output (MISO) STF model that takes a few different pixels as inputs greatly improves the precision of the estimation. We interpret this result that multi-peaked respiratory output patterns are caused by “migration of recruited area”. Here the term “migration” denotes the phenomenon that the transition of respiratory-recruited subareas on the ventral medulla is observed within a single breath. In conclusion, the STF model is useful for analyzing spatiotemporal dynamics of optically recorded respiratory neuronal activities.

Keywords

Optical Signal Spatiotemporal Dynamic Single Breath Transfer Function Model Respiratory Neuron 
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.

Notes

Acknowledgments

This work was supported by the ISM Cooperative Research Program (2006-ISM-CRP-2029, 2007-ISM-CRP-2034), the 2006-2007 ISM Research Projects Grant and the Grant-in-Aid for Scientific Research (A) by the Ministry of Education, Science, Sports and Culture (19200021).

References

  1. Akaike, H. (1974) A new look at the statistical model identification. IEEE Trans. Automatic Control 19, 716–723.CrossRefGoogle Scholar
  2. Kawai, S., Oku, Y., Okada, Y., Miwakeichi, F., Ishiguro, M., and Tamura, Y. (2009) A novel statistical analysis of voltage-imaging data by structural time series modeling and its application to the respiratory neuronal network. Neurosci. Res. 63, 165–171.CrossRefPubMedGoogle Scholar
  3. Oku, Y., Masumiya, H., and Okada, Y. (2007) Postnatal developmental changes in activation profiles of the respiratory neuronal network in the rat ventral medulla. J. Physiol. 585, 175–186.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Makio Ishiguro
    • 1
    • 5
  • Shigeharu Kawai
    • 1
  • Yasumasa Okada
    • 2
  • Yoshitaka Oku
    • 3
  • Fumikazu Miwakeichi
    • 4
  • Yoshiyasu Tamura
    • 1
    • 5
  • Amit Lal
    • 1
    • 3
  1. 1.The Institute of Statistical MathematicsTokyoJapan
  2. 2.Department of MedicineKeio University, Tsukigase Rehabilitation CenterIzucityJapan
  3. 3.Department of PhysiologyHyogo College of MedicineHyogoJapan
  4. 4.Graduate School of EngineeringChiba UniversityChibaJapan
  5. 5.Graduate University for Advanced StudiesTokyoJapan

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