Automatic detection, characterization, and discrimination of kinetically distinct spontaneous synaptic events

Rapid and reliable detection of randomly occurring small amplitude synaptic events resulting from activation of different classes of ligand-gated receptors is a difficult task. Here, we describe and characterize an amplitude threshold algorithm, written as an IGOR Pro procedure, which detects events as well as characterizes their amplitudes and kinetics. The program was developed to analyze recording traces that each contained both excitatory (glutamate-mediated) and inhibitory (GABA and glycine-mediated) events. By using differences in kinetics, the program could discriminate between the two different classes of events. In summary, the program has the following strengths: (1) it is generally applicable to circumstances in which different populations of elementary events occur concurrently, a drawback of methods that employ matched filtering techniques, (2) it is relatively insensitive to drifts in baseline, and (3) it generates user-accessible arrays of the timing, amplitude and kinetic parameters of the detected events, making customized statistical analysis of event characteristics easily executable.