@article {Rossant015198, author = {Cyrille Rossant and Shabnam Kadir and Dan F. M. Goodman and John Schulman and Mariano Belluscio and Gyorgy Buzsaki and Kenneth D. Harris}, title = {Spike sorting for large, dense electrode arrays}, elocation-id = {015198}, year = {2015}, doi = {10.1101/015198}, publisher = {Cold Spring Harbor Laboratory}, abstract = {Developments in microfabrication technology have enabled the production of neural electrode arrays with hundreds of closely-spaced recording sites, and electrodes with thousands of sites are currently under development. These probes will in principle allow the simultaneous recording of very large numbers of neurons. However, use of this technology requires the development of techniques for decoding the spike times of the recorded neurons, from the raw data captured from the probes. There currently exists no practical solution to this problem of {\textquotedblleft}spike sorting{\textquotedblright} for large, dense electrode arrays. Here, we present a set of novel tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from rat cortex, demonstrating error rates as low as 5\%.}, URL = {https://www.biorxiv.org/content/early/2015/02/16/015198}, eprint = {https://www.biorxiv.org/content/early/2015/02/16/015198.full.pdf}, journal = {bioRxiv} }