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Elife. 2018 Mar 20;7. pii: e34518. doi: 10.7554/eLife.34518.

A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo.

Author information

Institut de la Vision, INSERM UMRS 968, UPMC UM 80, Paris, France.
Laboratoire de Physique Statistique, CNRS, ENS, UPMC, 75005, Paris, France.
NMI, Neurophysics Group, Reutlingen, Germany.
Contributed equally


In recent years, multielectrode arrays and large silicon probes have been developed to record simultaneously between hundreds and thousands of electrodes packed with a high density. However, they require novel methods to extract the spiking activity of large ensembles of neurons. Here, we developed a new toolbox to sort spikes from these large-scale extracellular data. To validate our method, we performed simultaneous extracellular and loose patch recordings in rodents to obtain 'ground truth' data, where the solution to this sorting problem is known for one cell. The performance of our algorithm was always close to the best expected performance, over a broad range of signal-to-noise ratios, in vitro and in vivo. The algorithm is entirely parallelized and has been successfully tested on recordings with up to 4225 electrodes. Our toolbox thus offers a generic solution to sort accurately spikes for up to thousands of electrodes.


electrophysiology; mouse; neural ensemble; neuroscience; population recording; rat; silicon probe; spike sorting

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