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Preventing errors when estimating single channel properties from the analysis of current fluctuations

S D Silberberg1, K L Magleby

  • 1Department of Physiology and Biophysics R-430, University of Miami School of Medicine, Florida 33101-6430.

Biophysical Journal
|October 1, 1993
PubMed
Summary

Flaws in fluctuation analysis can skew ion channel property estimates. Proper filtering and analysis duration, alongside specific methods like Butterworth filtering, minimize errors in channel number and open time calculations.

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Area of Science:

  • Biophysics
  • Computational Neuroscience
  • Ion Channel Physiology

Background:

  • Estimating ion channel properties like conductance, number, and mean open time relies on analyzing membrane current fluctuations.
  • Potential errors in fluctuation analysis can compromise the accuracy of these single-channel property estimations.

Purpose of the Study:

  • To investigate and quantify errors in single-channel property estimation arising from fluctuation analysis.
  • To identify optimal parameters for filtering and data segment length to minimize these errors.

Main Methods:

  • Simulated ensemble currents to estimate single channel properties.
  • Utilized nonstationary fluctuation analysis for channel number (N) and amplitude (i) estimation.
  • Employed covariance and spectral analysis for mean open time estimation.

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  • Evaluated the impact of excessive filtering and brief current segment analysis.

    • Main Results:

    • Excessive filtering and short analysis segments led to underestimation of channel amplitude (i) and overestimation of channel number (N).
    • Errors were reduced to <2% by setting filter cut-off frequency >5x inverse of mean channel open time and analyzing segments >=80x mean open time.
    • Butterworth filtering showed up to 10% less error than Bessel filtering for estimating i and N under excessive filtering.
    • Mean open time estimates were less sensitive to filtering; extrapolation of covariance decay time (tau obs) plots provided accurate estimates at higher open probabilities.

    Conclusions:

    • Optimized filtering and analysis duration are crucial for accurate ion channel property estimation via fluctuation analysis.
    • Butterworth and Bessel filtering exhibit differential performance depending on the analysis method (covariance vs. spectral) and the parameter being estimated.
    • A method for estimating mean open time using covariance decay time extrapolation is effective across varying open probabilities.