Fast and accurate spike sorting of high-channel count probes with KiloSort
- Submitting institution
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University of Hertfordshire
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 24439340
- Type
- E - Conference contribution
- DOI
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- Title of conference / published proceedings
- NIPS 2016
- First page
- 4455
- Volume
- -
- Issue
- -
- ISSN
- 1049-5258
- Open access status
- Technical exception
- Month of publication
- December
- Year of publication
- 2016
- URL
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https://proceedings.neurips.cc/paper/2016/file/1145a30ff80745b56fb0cecf65305017-Paper.pdf
- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
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4
- Research group(s)
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-
- Citation count
- -
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- KiloSort is now the main spike sorting algorithm worldwide for spike sorting electrophysiological data recorded on novel probes containing hundreds to thousands of channels, as evidenced by the worldwide popularity of the NeuroPixels course (UCL) (map from https://www.ucl.ac.uk/neuropixels/courses shows 108 labs paid form training in Kilosort, including Moser Lab). Further labs are encouraged to contact one of these trained labs due to huge demand. It was the first algorithm to substantially reduce the burden of manual curation of spikes which greatly aided experimentalists in their analysis of in-vivo recordings (Steinmetz et al, 2018, Current Opinion in Neurobiology).
- Author contribution statement
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- Non-English
- No
- English abstract
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