Spike Sorting Using a Cognitive Method Based on Fuzzy Concepts

A new spike sorting algorithm is proposed. This algorithm follows the human cognition process and classifies the spikes based on fuzzy concepts obtained from morphological features of spikes and fuzzy membership degrees to clustered spike classes formed at an initial stage of the classification. After learning classification rules through a training set, the spike sorting goes through an online format classification. The proposed method is then applied to both simulated and real data from chicken´s retina. The results are promising and suggest the utility of the proposed method.