Abstract
The power of single-channel analysis techniques has rapidly expanded during the past few years, giving investigators increased ability to identify models and estimate parameters while reducing error and artifacts. At present, however, there is no single best method, as even the most advanced techniques have various limitations which depend on the experimental data and models being examined. Consequently, for the examined models and experimental data, the most critical part of single-channel analysis is to estimate errors and evaluate the ability of the methods used to discriminate among possible gating mechanisms. The magnitudes of the errors and the ability to identify models and estimate parameters depend on the models being examined as well as the experimental conditions and data. Consequently, the evaluation of the errors associated with each method needs to be repeated when the experimental data and examined models change.
