24] Signal processing techniques for channel current analysis based on hidden markov models

Abstract

Publisher Summary The patch-clamp technique can be used to record single-channel activity from a small patch of cell membrane. Although the noise from a small patch is much less than that from a whole-cell membrane, signals of interest are often obscured by the noise. Even if the signal frequently emerges from the noise, low-amplitude events such as small subconductance states can remain below the noise level and there may be little evidence of their presence. It is desirable therefore to have a method to measure and characterize not only relatively large ionic currents but also much smaller current fluctuations that are obscured by noise. Extracting the real signal from a limited set of imperfect measurements is a problem that commonly occurs in science, and techniques have been developed to overcome this difficulty. Following digitization, a single-channel record consists of a sequence of data points. Any movement between successive data points can be due to the signal of interest, extraneous noise, or both. The challenge is to remove the noise leaving the biological signal untouched. Some of the methods that have been used in this chapter to do this are linear filtering, nonlinear filtering, and transition detectors.