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%.
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Acknowledgements
We thank the 200+ members of the klustaviewas@groups.google.com 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.
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C.R., D.F.M.G., S.N.K. and J.S. wrote SpikeDetekt. K.D.H., S.N.K. and D.F.M.G. designed the masked EM algorithm and wrote KlustaKwik. C.R. and M.L.D.H. wrote KlustaViewa. C.R. wrote Galry. S.N.K. analyzed a lgorithm performance. Rat data were recorded by A.G., M.B. and G.B. Mouse data were recorded by A.B.S. and M.C. Marmoset data were recorded by S.S. The procedure for non-chronic laminar recordings with NeuroNexus Vector probes in awake, behaving macaques was developed by G.H.D., A.S.E. and A.S.T., who also collected the data. K.D.H., S.N.K. and C.R. wrote the manuscript with input from all authors.
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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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DOI: https://doi.org/10.1038/nn.4268
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