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Nat Neurosci. 2016 Apr;19(4):634-641. doi: 10.1038/nn.4268. Epub 2016 Mar 14.

Spike sorting for large, dense electrode arrays.

Author information

1
UCL Department of Neuroscience, Physiology and Pharmacology, London, UK.
2
UCL Institute of Neurology, London, UK.
3
Department of Electrical and Electronic Engineering, Imperial College, London, UK.
4
Department of Electrical Engineering and Computer Sciences, UC Berkeley, Berkeley, CA.
5
UCL Institute of Ophthalmology, London, UK.
6
NYU Neuroscience Institute, Langone Medical Center, New York, NY.
7
Department of Neuroscience, Baylor College of Medicine, Houston, TX.
8
UCL Institute of Behavioural Neuroscience, Department of Experimental Psychology, London, UK.
#
Contributed equally

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%.

PMID:
26974951
PMCID:
PMC4817237
DOI:
10.1038/nn.4268
[Indexed for MEDLINE]
Free PMC Article

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