Spike sorting for large, dense electrode arrays
2016 | journal article
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Cite this publication
Rossant, C., Kadir, S. N., Goodman, D. F. M., Schulman, J., Hunter, M. L. D., Saleem, A. B., Grosmark, A. ... Harris, K. D. (2016). Spike sorting for large, dense electrode arrays. Nature Neuroscience, 19(4), 634-641. doi: https://doi.org/10.1038/nn.4268
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Details
- Authors
- 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; Buzsaki, Gyorgy; Carandini, Matteo; Harris, Kenneth D.
- 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%.
- Issue Date
- 2016
- Journal
- Nature Neuroscience
- ISSN
- 1097-6256
- eISSN
- 1546-1726
- Language
- English