A review on different algorithms and methods used for neural spike detection

Identification of neural spike activities has been a challenging task for a researcher which is a prerequisite for understanding various types of brain function. Computing the activities of each neuron with maximum accuracy can be a tricky task since the acquired signal form neurons have large amount of noise, therefore it becomes difficult for detection. This article reviews various algorithms and different techniques used for detection and classification of neural spike sorting. The article firstly shows the challenges faced for the measurement of neural activities and preliminary issues of signal detection and classification. Further this paper reviews and demonstrates algorithms and methods that have already been applied to various spike sorting problems. Also the advantages and limitations of each algorithm and methods along with its applicability have been discussed in this paper