A software routine to reconstruct individual spike trains from
multi-neuron, single-channel extracellular recordings was designed.
Using a neural network algorithm that automatically clusters and sorts
the spikes, the only user input needed is the threshold level for
spike detection and the number of unit types present in the recording.
Adaptive features are included in the algorithm to allow for tracking
of spike trains during periods of amplitude variation and also to
identify noise spikes.  The routine will operate on-line during
extracellular studies of the cochlear nucleus in cats.