The use of multiple electrodes to record the activity of a neural populations is a technique that has shown promise in obtaining spike data from neural populations. This population data is clearly needed to further the study of how neurons code, process, learn, and retain information. Better understanding of neural population coding would have wide clinical benefits, for example, in the design of microelectronic devices such as cochlear and retinal implants. Currently, most researchers who collect multielectrode data are forced to also develop their own software to sort the recorded action potentials from each of the neurons recorded, determining the relative time-of-occurrence of each action potential, a process known as "spike-sorting." The long-term objective of this research program is to develop a MATLAB software toolbox for automated multichannel spike-sorting incorporating state-of-the-art algorithms using advanced signal processing techniques. The objective of the Phase I project is to develop prototype software using the MATLAB environment that expands existing work and incorporates new methods for spike sorting. This will be the first commercially available package that will allow the effective solution to a major problem facing neuroscientists: the discrimination and identification of spike superpositions. PROPOSED COMMERCIAL APPLICATION: There are many potential users of multichannel spike-sorting software who are already obtaining multichannel data. The number of researchers doing multi-channel studies has increased dramatically and will continue to increase as computer become faster and better multielectrodes are producted.