Spike sorting for large, dense electrode arrays
- Submitting institution
-
University of Hertfordshire
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 13613163
- Type
- D - Journal article
- DOI
-
10.1038/nn.4268
- Title of journal
- Nature Neuroscience
- Article number
- -
- First page
- 634
- Volume
- 19
- Issue
- 4
- ISSN
- 1097-6256
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
14
- Research group(s)
-
-
- Citation count
- 246
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Reports development of an open-course software package, Phy, incorporating new algorithms designed to tackle an urgent technical challenge in the field of spike sorting in electrophysiology brought on by the NeuroPixels probes which are revolutionising neuroscience. This was developed with continual input and feedback from over 320 scientists in 50 labs worldwide. The package enabled scalable and user-friendly analysis of how hundreds of simultaneously recorded neurons contribute or generate complex animal behaviour and intelligence. It underpinned the analysis in many groundbreaking studies on brain development e.g. (Quadrato et al. 2017, Nature) and brain disease e.g. (Iaccarino et al. 2016, Nature).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -