Spike sorting by a minimax reduced feature set based on finite differences.

Spikes are classified according to their finite differences in various orders. The fundamental idea that makes it work is that finite differences can extract and isolate features from spikes. This method showed better sorting quality and involved less labor than the methods of principal component analysis, original reduced feature set, and wavelet-based spike classifiers.