The goal of this proposal is to develop a working framework for a multichannel data acquisition and stimulus presentation package for single-unit neurophysiology. In Phase I we will develop spike-sorting algorithms capable of discriminating action potentials from multiple neurons per each electrode, incorporating information across channels to improve the discrimination ability of the algorithm. Real-time discrimination would obviate the need for post-processing the data from high channel count systems, improving the ability to make experimental decisions during the course of the experiment. We will also develop a graphical display and interface designed to condense the inherently complex data sets that are acquired simultaneously from many single-units across many electrodes and stimulus parameters. The combination of stimulus control with multichannel acquisition will similarly improve data visualization.
The proposed project is to test the feasibility of developing a high channel count system for neurophysiology research. The commercial application of this product is most directly for the scientific research market in multichannel neurophysiology. It could be adapted for other clinical systems that require high channel counts, such as EEG systems.
