Practical analysis of single channel records

The aim of this chapter is to discuss the sorts of things that can be measured in an experimental record of single channel currents, and how to make the measurements. What is measured will depend on the aims of the experiment. In some cases, interest may centre mainly on the amplitudes of the currents. For example, this might be the case (a) when channel conductance and subconductance levels are used as a criterion for a particular channel subtype, or (b) when measurements are made in solutions of different ionic composition and different membrane potentials, in order to investigate the mechanism of ion permeation through open channels. In other cases the durations of the open and shut times may be of primary interest, as when we want to know the nature of individual channel activations by a transmitter (the unitary event usually consists of more than one opening), or when the kinetic mechanism of channel operation is of primary interest. The aims of a complete analysis are to measure (a) the amplitude(s) of the single channel currents, (b) the durations of shut periods, and the durations of sojourns at the various open channel current levels, and (c) the order in which the foregoing events occur. The amplitudes are, in the simplest cases at least, very nearly constant from one opening to the next. But, because we are looking at a single molecule, the durations of events and the order in which they occur are random variables; the information contained in them comes from measurements of their distributions (more strictly, their probability density functions see Chapter 7 for more details). Many measurements of individual durations have to be made in order to define these distributions properly. Single channel analysis must be one of the slowest known methods of generating an exponential curve from an experiment, because the averaging that normally results from having a large number of channels has not ‘already been done for us’. Furthermore the analysis is particularly important; not much can be inferred by simply looking at the raw data, because of its randomness. These measurements can be rather time consuming; this leads to the temptation to use automatic or semiautomatic methods of analysis in which distributions are produced by a computer program with little intervention by the experimenter. It is not usual in

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