  This paper deals with the problem of extracting the activity of individual
neurons from multi-electrode recordings. Important aspects of this work are: 1)
the sorting is done in two stages - a statistical model of the spikes from
different cells is built and only then are occurrences of these spikes in the
data detected by scanning through the original data, 2) the spike sorting is
done in the frequency domain, 3) strict statistical tests are applied to
determine if and how a spike should be classiffed, 4) the statistical model for
detecting overlaping spike events is proposed, 5) slow dynamics of spike shapes
are tracked during long experiments. Results from the application of these
techniques to data collected from the escape response system of the American
cockroach, Periplaneta americana, are presented.
