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Hebbian Covariance Learning

A Nexus for Respiratory Variability, Memory, and Optimization?

  • Chapter
Advances in Modeling and Control of Ventilation

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 450))

Abstract

Respiration is a vital autonomic function that is characterized by an almost unwavering ability to maintain homeostatic blood gas and pH levels in the face of profound physiological and environmental challenges. This remarkable behavior has led many researchers to assume that respiratory control is a reflexogenic process whose sole purpose is simply to maintain nominal body gas and pH tones. While this model has born some insight into certain aspects of the respiratory system, it fails to account for more complex behaviors of the system that have been increasingly recognized.

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Author information

Authors and Affiliations

  1. Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts, 02139, USA

    Daniel L. Young & Chi-Sang Poon

  2. Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, 02139, USA

    Daniel L. Young

Authors
  1. Daniel L. Young
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  2. Chi-Sang Poon
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Corresponding author

Correspondence to Chi-Sang Poon .

Editor information

Editors and Affiliations

  1. University of Waterloo, Waterloo, Ontario, Canada

    Richard L. Hughson

  2. University of Western Ontario, London, Ontario, Canada

    David A. Cunningham

  3. University of Toronto, Toronto, Ontario, Canada

    James Duffin

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© 1998 Springer Science+Business Media New York

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Young, D.L., Poon, CS. (1998). Hebbian Covariance Learning. In: Hughson, R.L., Cunningham, D.A., Duffin, J. (eds) Advances in Modeling and Control of Ventilation. Advances in Experimental Medicine and Biology, vol 450. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-9077-1_14

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  • DOI: https://doi.org/10.1007/978-1-4757-9077-1_14

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4757-9079-5

  • Online ISBN: 978-1-4757-9077-1

  • eBook Packages: Springer Book Archive

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