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%.
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We thank the 200+ members of the firstname.lastname@example.org mailing list for their feedback, bug reports and suggestions. This work was supported by EPSRC (K015141, I005102, K.D.H.) and the Wellcome Trust (95668, 95669, 100154, K.D.H., M.C.). M.C. is supported by the GlaxoSmithKline/Fight for Sight chair in Visual Neuroscience.
The authors declare no competing financial interests.
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Rossant, C., Kadir, S., Goodman, D. et al. Spike sorting for large, dense electrode arrays. Nat Neurosci 19, 634–641 (2016). https://doi.org/10.1038/nn.4268
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