Imperial College London

Dr Dan Goodman

Faculty of EngineeringDepartment of Electrical and Electronic Engineering




+44 (0)20 7594 6264d.goodman Website




1001Electrical EngineeringSouth Kensington Campus






BibTex format

author = {Rossant, C and Kadir, SN and Goodman, DF and Schulman, J and Hunter, ML and Saleem, AB and Grosmark, A and Belluscio, M and Denfield, GH and Ecker, AS and Tolias, AS and Solomon, S and Buzsáki, G and Carandini, M and Harris, KD},
doi = {10.1038/nn.4268},
journal = {Nature Neuroscience},
pages = {634--641},
title = {Spike sorting for large, dense electrode arrays},
url = {},
volume = {19},
year = {2016}

RIS format (EndNote, RefMan)

AB - 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%.
AU - Rossant,C
AU - Kadir,SN
AU - Goodman,DF
AU - Schulman,J
AU - Hunter,ML
AU - Saleem,AB
AU - Grosmark,A
AU - Belluscio,M
AU - Denfield,GH
AU - Ecker,AS
AU - Tolias,AS
AU - Solomon,S
AU - Buzsáki,G
AU - Carandini,M
AU - Harris,KD
DO - 10.1038/nn.4268
EP - 641
PY - 2016///
SN - 1546-1726
SP - 634
TI - Spike sorting for large, dense electrode arrays
T2 - Nature Neuroscience
UR -
UR -
UR -
VL - 19
ER -