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

by Pierre Yger, Giulia LB Spampinato, Elric Esposito, Baptiste Lefebvre, Stéphane Deny, Christophe Gardella, Marcel Stimberg, Florian Jetter, Guenther Zeck, Serge Picaud, Jens Duebel, Olivier Marre
Abstract:
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.
Reference:
Pierre Yger, Giulia LB Spampinato, Elric Esposito, Baptiste Lefebvre, Stéphane Deny, Christophe Gardella, Marcel Stimberg, Florian Jetter, Guenther Zeck, Serge Picaud, Jens Duebel, Olivier Marre, 2018. A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo, eLife (David Kleinfeld, ed.), eLife Sciences Publications, Ltd, volume 7.
Bibtex Entry:
@article {Yger2018,
article_type = {journal},
title = {A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo},
author = {Yger, Pierre and Spampinato, Giulia LB and Esposito, Elric and Lefebvre, Baptiste and Deny, Stéphane and Gardella, Christophe and Stimberg, Marcel and Jetter, Florian and Zeck, Guenther and Picaud, Serge and Duebel, Jens and Marre, Olivier},
editor = {Kleinfeld, David},
volume = 7,
year = 2018,
month = {mar},
pub_date = {2018-03-20},
pages = {e34518},
citation = {eLife 2018;7:e34518},
doi = {10.7554/eLife.34518},
url = {https://elifesciences.org/download/aHR0cHM6Ly9jZG4uZWxpZmVzY2llbmNlcy5vcmcvYXJ0aWNsZXMvMzQ1MTgvZWxpZmUtMzQ1MTgtdjIucGRm/elife-34518-v2.pdf?_hash=OZQVzcieOLtyGVZUKHHV96BTmFkFRV3S1SznscwHcoo%3D},
abstract = {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.},
keywords = {electrophysiology, silicon probe, population recording, spike sorting, neural ensemble},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}