The reconstruction of individual spike trains from extracellular multineuron recordings using a neural network emulation program.

A method for the reconstruction of the individual spike trains from extracellular multineuron recordings is described. A neural network emulation program is trained to recognize a sample set of digitized spikes. The digitized spikes are fed into the neural network, and the network output is used to classify spikes in terms of the training set. The system runs on any PC and its speed makes is especially well suited for the analysis of large amounts of data.