Inferences about Molecular Mechanisms through Fluctuation Analysis

  • Charles F. Stevens


Membrane channels operate in an inherently probabilistic fashion because the world at a molecular level is chaotic. As a consequence of this molecular chaos, the number of open channels in an excitable cell’s membrane varies incessantly around an average value and produces random fluctuations in membrane conductance. The statistical characteristics of these fluctuations are not identical for all channel types, but rather reflects those same physical processes that give rise to variety in behaviors between species of channels. Thus, one sort of channel may produce small and rapid fluctuations, whereas another may yield large, slow noise. The essence of fluctuation analysis —the study of a system’s inherent noise—is this: channel noise reflects underlying molecular mechanisms, so we can learn about these mechanisms by studying conductance fluctuations. In some situations, fluctuation analysis is simply an alternative to studying the average response to a perturbation, but in other instances we can gain information not otherwise available. For example, different molecular mechanisms can exhibit identical average behavior, but produce fluctuations with distinct characteristics.


Spectral Density Covariance Function High Frequency Component Sampling Theorem Noise Sample 
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  1. Kenrick, G. W., 1929, The analysis of irregular motions with applications to the energy frequency spectrum of static and of telegraph signals, Phil. Mag., Series 7, Volume 7:176.Google Scholar
  2. Aseltine, J. A., 1958, “Transform Method in Linear System Analysis,” McGraw Hill, New York, pp. 1–293.Google Scholar
  3. Bailey, N. T. J., 1964, “The Elements of Stochastic Processes,” Wiley & Sons, New York, pp. 1–245.Google Scholar
  4. Gnedenko, B. V., 1962,”The Theory of Probability,” Chelsea Publishing Company, New York, pp. 1–523.Google Scholar
  5. Neher, E., and Stevens, C. F., 1977, Conductance fluctuations and ionic pores in membranes, Ann. B.ev. Biophys. Bioeng. 6:345.CrossRefGoogle Scholar
  6. Bendat, J. S., and Piersol, A. G., 1971, “Random Data: Analysis and Measurement Procedures,” Wiley-Interscience, New York, pp. 1–397.Google Scholar

Copyright information

© Plenum Press, New York 1984

Authors and Affiliations

  • Charles F. Stevens
    • 1
  1. 1.Section of Molecular NeurobiologyYale University School of MedicineNew HavenUSA

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