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SHYBRID: A graphical tool for generating hybrid ground-truth spiking data for evaluating spike sorting performance

View ORCID ProfileJasper Wouters, Fabian Kloosterman, Alexander Bertrand
doi: https://doi.org/10.1101/734061
Jasper Wouters
KU Leuven, Electrical Engineering Dept. (ESAT), Stadius Center for Dynamical Systems, Signal Processing, and Data Analytics, Leuven, Belgium
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  • ORCID record for Jasper Wouters
  • For correspondence: jasper.wouters@esat.kuleuven.be
Fabian Kloosterman
Neuro-Electronics Research Flanders (NERF), Leuven, BelgiumKU Leuven, Brain & Cognition Research Unit, Leuven, BelgiumVIB, Leuven, Belgium
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Alexander Bertrand
KU Leuven, Electrical Engineering Dept. (ESAT), Stadius Center for Dynamical Systems, Signal Processing, and Data Analytics, Leuven, Belgium
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Abstract

Spike sorting is the process of retrieving the spike times of individual neurons that are present in an extracellular neural recording. Over the last decades, many spike sorting algorithms have been published. In an effort to guide a user towards a specific spike sorting algorithm, given a specific recording setting (i.e., brain region and recording device), we provide an open-source graphical tool for the generation of hybrid ground-truth data in Python. Hybrid ground-truth data is a data-driven modelling paradigm in which spikes from a single unit are moved to a different location on the recording probe, thereby generating a virtual unit of which the spike times are known. The tool enables a user to efficiently generate hybrid ground-truth datasets and make informed decisions between spike sorting algorithms, fine-tune the algorithm parameters towards the used recording setting, or get a deeper understanding of those algorithms.

Footnotes

  • This work was carried out at the ESAT Laboratory of KU Leuven, in the frame of KU Leuven Special Research Fund projects C14/16/057, and the Research Foundation Flanders (FWO) project FWO G0D7516N. This project has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No 802895). The scientific responsibility is assumed by its authors.

  • https://github.com/jwouters91/shybrid

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted August 13, 2019.
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SHYBRID: A graphical tool for generating hybrid ground-truth spiking data for evaluating spike sorting performance
Jasper Wouters, Fabian Kloosterman, Alexander Bertrand
bioRxiv 734061; doi: https://doi.org/10.1101/734061
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SHYBRID: A graphical tool for generating hybrid ground-truth spiking data for evaluating spike sorting performance
Jasper Wouters, Fabian Kloosterman, Alexander Bertrand
bioRxiv 734061; doi: https://doi.org/10.1101/734061

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