A review of methods for spike sorting: the detection and classification ofneural action potentials

The detection of neural spike activity is a technical challenge that is a p rerequisite for studying many types of brain function. Measuring the activi ty of individual neurons accurately can be difficult due to large amounts o f background noise and the difficulty in distinguishing the action potentia ls of one neuron from those of others in the local area. This article revie ws algorithms and methods for detecting and classifying action potentials, a problem commonly referred to as spike sorting. The article first discusse s the challenges of measuring neural activity and the basic issues of signa l detection anti classification. It reviews and illustrates algorithms and techniques that have been applied to many of the problems in spike sorting and discusses the advantages and limitations of each and the applicability of these methods for different types of experimental demands. The article i s written both for the physiologist wanting to use simple methods that will improve experimental yield and minimize the selection biases of traditiona l techniques and for those who want to apply or extend more sophisticated a lgorithms to meet new experimental challenges.