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

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.

Data availability

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Pierre Yger

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  2. Giulia LB Spampinato

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Elric Esposito

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Baptiste Lefebvre

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  5. Stéphane Deny

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  6. Christophe Gardella

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3204-9012
  7. Marcel Stimberg

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2648-4790
  8. Florian Jetter

    Neurophysics group, The Natural and Medical Sciences Institute, Reutlingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  9. Guenther Zeck

    Neurophysics group, The Natural and Medical Sciences Institute, Reutlingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  10. Serge Picaud

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  11. Jens Duebel

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  12. Olivier Marre

    Physiology and Information Processing, Institut de la Vision - INSERM URMS 968, Paris, France
    For correspondence
    olivier.marre@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0090-6190

Funding

Agence Nationale de la Recherche (TRAJECTORY)

  • Olivier Marre

European Commission (ERC StG 309776)

  • Jens Duebel

National Institutes of Health (U01NS090501)

  • Olivier Marre

Foundation Fighting Blindness

  • Serge Picaud

Agence Nationale de la Recherche (ANR-14-CE13-0003)

  • Pierre Yger

Agence Nationale de la Recherche (ANR-10-LABX-65)

  • Serge Picaud

European Commission (FP7-604102)

  • Olivier Marre

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. David Kleinfeld, University of California, San Diego, United States

Ethics

Animal experimentation: Experiments were performed in accordance with institutional animal care standards, using protocol (#00847.02) of the Institut de la Vision (Agreement number A751202). The protocol was approved by the Charles Darwin ethic committee (CEEACD/N{degree sign}5)

Version history

  1. Received: December 20, 2017
  2. Accepted: March 19, 2018
  3. Accepted Manuscript published: March 20, 2018 (version 1)
  4. Version of Record published: April 9, 2018 (version 2)

Copyright

© 2018, Yger et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 13,949
    views
  • 1,703
    downloads
  • 256
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Pierre Yger
  2. Giulia LB Spampinato
  3. Elric Esposito
  4. Baptiste Lefebvre
  5. Stéphane Deny
  6. Christophe Gardella
  7. Marcel Stimberg
  8. Florian Jetter
  9. Guenther Zeck
  10. Serge Picaud
  11. Jens Duebel
  12. Olivier Marre
(2018)
A spike sorting toolbox for up to thousands of electrodes validated with ground truth recordings in vitro and in vivo
eLife 7:e34518.
https://doi.org/10.7554/eLife.34518

Share this article

https://doi.org/10.7554/eLife.34518

Further reading

    1. Neuroscience
    Daniel Hoops, Robert Kyne ... Cecilia Flores
    Short Report

    Dopamine axons are the only axons known to grow during adolescence. Here, using rodent models, we examined how two proteins, Netrin-1 and its receptor, UNC5C, guide dopamine axons toward the prefrontal cortex and shape behaviour. We demonstrate in mice (Mus musculus) that dopamine axons reach the cortex through a transient gradient of Netrin-1-expressing cells – disrupting this gradient reroutes axons away from their target. Using a seasonal model (Siberian hamsters; Phodopus sungorus) we find that mesocortical dopamine development can be regulated by a natural environmental cue (daylength) in a sexually dimorphic manner – delayed in males, but advanced in females. The timings of dopamine axon growth and UNC5C expression are always phase-locked. Adolescence is an ill-defined, transitional period; we pinpoint neurodevelopmental markers underlying this period.

    1. Neuroscience
    Baba Yogesh, Georg B Keller
    Research Article

    Acetylcholine is released in visual cortex by axonal projections from the basal forebrain. The signals conveyed by these projections and their computational significance are still unclear. Using two-photon calcium imaging in behaving mice, we show that basal forebrain cholinergic axons in the mouse visual cortex provide a binary locomotion state signal. In these axons, we found no evidence of responses to visual stimuli or visuomotor prediction errors. While optogenetic activation of cholinergic axons in visual cortex in isolation did not drive local neuronal activity, when paired with visuomotor stimuli, it resulted in layer-specific increases of neuronal activity. Responses in layer 5 neurons to both top-down and bottom-up inputs were increased in amplitude and decreased in latency, whereas those in layer 2/3 neurons remained unchanged. Using opto- and chemogenetic manipulations of cholinergic activity, we found acetylcholine to underlie the locomotion-associated decorrelation of activity between neurons in both layer 2/3 and layer 5. Our results suggest that acetylcholine augments the responsiveness of layer 5 neurons to inputs from outside of the local network, possibly enabling faster switching between internal representations during locomotion.