A Comprehensive Exploration of Unsupervised Classification in Spike Sorting: A Case Study on Macaque Monkey and Human Pancreatic Signals
Francisco Javier Iñiguez-Lomeli,
Edgar Eliseo Franco-Ortiz,
Ana Maria Silvia Gonzalez-Acosta
et al.
Abstract:Spike sorting, an indispensable process in the analysis of neural biosignals, aims to segregate individual action potentials from mixed recordings. This study delves into a comprehensive investigation of diverse unsupervised classification algorithms, some of which, to the best of our knowledge, have not previously been used for spike sorting. The methods encompass Principal Component Analysis (PCA), K-means, Self-Organizing Maps (SOMs), and hierarchical clustering. The research draws insights from both macaqu… Show more
Set email alert for when this publication receives citations?
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.