RT Journal Article
SR Electronic
T1 Fast and accurate spike sorting in <em>vitro</em> and <em>in vivo</em> for up to thousands of electrodes
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 067843
DO 10.1101/067843
A1 Pierre Yger
A1 Giulia L.B. Spampinato
A1 Elric Esposito
A1 Baptiste Lefebvre
A1 Stéphane Deny
A1 Christophe Gardella
A1 Marcel Stimberg
A1 Florian Jetter
A1 Guenther Zeck
A1 Serge Picaud
A1 Jens Duebel
A1 Olivier Marre
YR 2016
UL http://biorxiv.org/content/early/2016/08/04/067843.abstract
AB Understanding how assemblies of neurons encode information requires recording large populations of cells in the brain. In recent years, multi-electrode arrays and large silicon probes have been developed to record simultaneously from hundreds or thousands of electrodes packed with a high density. However, these new devices challenge the classical way to do spike sorting. Here we developed a new method to solve these issues, based on a highly automated algorithm to extract spikes from extracellular data, and show that this algorithm reached near optimal performance both in vitro and in vivo. The algorithm is composed of two main steps: 1) a “template-finding” phase to extract the cell templates, i.e. the pattern of activity evoked over many electrodes when one neuron fires an action potential; 2) a “template-matching” phase where the templates were matched to the raw data to find the location of the spikes. The manual intervention by the user was reduced to the minimal, and the time spent on manual curation did not scale with the number of electrodes. We tested our algorithm with large-scale data from in vitro and in vivo recordings, from 32 to 4225 electrodes. We performed simultaneous extracellular and patch recordings to obtain “ground truth” data, i.e. cases where the solution to the sorting problem is at least partially known. The performance of our algorithm was always close to the best expected performance. We thus provide a general solution to sort spikes from large-scale extracellular recordings.