Open AccessNeural Spike Sorting And Classification
Author(s) -
Zaid H. Berjis,
Ahmed Khorsheed Al-Sulaifanie
Publication year - 2020
Publication title -
maǧallaẗ ǧāmi'aẗ duhūk
Language(s) - English
Resource type - Journals
eISSN - 2521-4861
pISSN - 1812-7568
DOI - 10.26682/sjuod.2020.23.2.18
Subject(s) - spike sorting , spike (software development) , sorting , pattern recognition (psychology) , computer science , noise (video) , signal (programming language) , artificial intelligence , sorting algorithm , process (computing) , algorithm , image (mathematics) , software engineering , programming language , operating system
Spike sorting is the process of separating the extracellular recording of the brain signal into one unit activity. There are a number of proposed algorithms for this purpose, but there is still no acceptable solution. In this paper a spike sorting method has been proposed based on the Euclidean distance of the most effective features of spikes represented by principle components (PCs) of the detected and aligned spikes. The assessments of the method, based on signal-to-noise ratio (SNR) representing background noise, showed that the method performed spike sorting to a high level of accuracy.