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        Spike sorting for large, dense electrode arrays

        Author
        Rossant, Cyrille
        Kadir, Shabnam N.
        Goodman, Dan F.M.
        Schulman, John
        Hunter, Maximilian L.D.
        Saleem, Aman B.
        Grosmark, Andres
        Belluscio, Mariano
        Denfield, George H.
        Ecker, Alexander S.
        Tolias, Andreas S.
        Solomon, Samuel
        Buzski, György
        Carandini, Matteo
        Harris, Kenneth D.
        Attention
        2299/19952
        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 under development. These probes 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. Here we present a set of tools to solve this problem, implemented in a suite of practical, user-friendly, open-source software. We validate these methods on data from the cortex, hippocampus and thalamus of rat, mouse, macaque and marmoset, demonstrating error rates as low as 5%.
        Publication date
        2016-03-29
        Published in
        Nature Neuroscience
        Published version
        https://doi.org/10.1038/nn.4268
        Other links
        http://hdl.handle.net/2299/19952
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