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dc.contributor.authorRossant, Cyrille
dc.contributor.authorKadir, Shabnam N.
dc.contributor.authorGoodman, Dan F.M.
dc.contributor.authorSchulman, John
dc.contributor.authorHunter, Maximilian L.D.
dc.contributor.authorSaleem, Aman B.
dc.contributor.authorGrosmark, Andres
dc.contributor.authorBelluscio, Mariano
dc.contributor.authorDenfield, George H.
dc.contributor.authorEcker, Alexander S.
dc.contributor.authorTolias, Andreas S.
dc.contributor.authorSolomon, Samuel
dc.contributor.authorBuzski, György
dc.contributor.authorCarandini, Matteo
dc.contributor.authorHarris, Kenneth D.
dc.identifier.citationRossant , C , Kadir , S N , Goodman , D F M , Schulman , J , Hunter , M L D , Saleem , A B , Grosmark , A , Belluscio , M , Denfield , G H , Ecker , A S , Tolias , A S , Solomon , S , Buzski , G , Carandini , M & Harris , K D 2016 , ' Spike sorting for large, dense electrode arrays ' , Nature Neuroscience , vol. 19 , no. 4 , pp. 634-641 .
dc.identifier.otherPURE: 13613035
dc.identifier.otherPURE UUID: d07d75ee-9a39-44e9-be1e-16d47f38ca54
dc.identifier.otherScopus: 84961231245
dc.identifier.otherPubMed: 26974951
dc.identifier.otherORCID: /0000-0002-0103-9156/work/44180872
dc.description.abstractDevelopments 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%.en
dc.relation.ispartofNature Neuroscience
dc.titleSpike sorting for large, dense electrode arraysen
dc.contributor.institutionCentre of Data Innovation Research
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionBiocomputation Research Group
dc.description.statusPeer reviewed
rioxxterms.typeJournal Article/Review

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