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

Pierre Yger,Marcel Stimberg,Jens Duebel,Florian Jetter,Olivier Marre,Serge Picaud,Christophe Gardella,Elric Esposito,Stéphane Deny,Giulia Lb Spampinato,Baptiste Lefebvre,Guenther Zeck

doi:10.7554/elife.34518

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.

Highlights

As local circuits represent information using large populations of neurons throughout the brain (Buzsaki, 2010), technologies to record hundreds or thousands of them are essential
We found that our method was always able to estimate the pairwise correlation between the spike trains with no underestimation (Figure 3G)
We have shown that our method, based on density-based clustering and template matching, allows sorting spikes from large-scale extracellular recordings both in vitro and in vivo

Summary

Introduction

As local circuits represent information using large populations of neurons throughout the brain (Buzsaki, 2010), technologies to record hundreds or thousands of them are essential. Newly developed microelectrode arrays (MEA) have allowed recording of local voltage from hundreds to thousands of extracellular sites separated only by tens of microns (Berdondini et al, 2005; Fiscella et al, 2012; Lambacher et al, 2004), giving indirect access to large neural ensembles with a high spatial resolution. Thanks to this resolution, the spikes from a single neuron will be detected on several electrodes and produce extracellular waveforms with a characteristic spatio-temporal profile across the recording sites. For thousands of electrodes, this problem is still largely unresolved

Methods

Results

Conclusion