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Scaling Spike Detection and Sorting for Next-Generation Electrophysiology

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In Vitro Neuronal Networks

Part of the book series: Advances in Neurobiology ((NEUROBIOL,volume 22))

Abstract

Reliable spike detection and sorting, the process of assigning each detected spike to its originating neuron, are essential steps in the analysis of extracellular electrical recordings from neurons. The volume and complexity of the data from recently developed large-scale, high-density microelectrode arrays and probes, which allow recording from thousands of channels simultaneously, substantially complicate this task conceptually and computationally. This chapter provides a summary and discussion of recently developed methods to tackle these challenges and discusses the important aspect of algorithm validation, and assessment of detection and sorting quality.

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Author information

Authors and Affiliations

  1. Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, UK

    Matthias H. Hennig, Cole Hurwitz & Martino Sorbaro

  2. Computational Science and Technology, KTH Royal Institute of Technology, Stockholm, Sweden

    Martino Sorbaro

Authors
  1. Matthias H. Hennig
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  2. Cole Hurwitz
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  3. Martino Sorbaro
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Corresponding author

Correspondence to Matthias H. Hennig .

Editor information

Editors and Affiliations

  1. Rehab Technologies IIT-INAIL Joint Lab, Istituto Italiano di Tecnologia, Genova, Italy

    Michela Chiappalone

  2. Neuroscience and Brain Technologies, Istituto Italiano di Tecnologia, Genova, Italy

    Valentina Pasquale

  3. Department of Clinical Neurophysiology, University of Twente, Enschede, The Netherlands

    Monica Frega

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Hennig, M.H., Hurwitz, C., Sorbaro, M. (2019). Scaling Spike Detection and Sorting for Next-Generation Electrophysiology. In: Chiappalone, M., Pasquale, V., Frega, M. (eds) In Vitro Neuronal Networks. Advances in Neurobiology, vol 22. Springer, Cham. https://doi.org/10.1007/978-3-030-11135-9_7

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