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QSpike tools: a generic framework for parallel batch preprocessing of extracellular neuronal signals recorded by substrate microelectrode arrays.

  • Mahmud M Theoretical Neurobiology and Neuroengineering Lab, Department of Biomedical Sciences, University of Antwerp Wilrijk, Belgium ; Institute of Information Technology, Jahangirnagar University Savar, Bangladesh.
  • Pulizzi R Theoretical Neurobiology and Neuroengineering Lab, Department of Biomedical Sciences, University of Antwerp Wilrijk, Belgium.
  • Vasilaki E Theoretical Neurobiology and Neuroengineering Lab, Department of Biomedical Sciences, University of Antwerp Wilrijk, Belgium ; Department of Computer Science, University of Sheffield Sheffield, UK.
  • Giugliano M Theoretical Neurobiology and Neuroengineering Lab, Department of Biomedical Sciences, University of Antwerp Wilrijk, Belgium ; Department of Computer Science, University of Sheffield Sheffield, UK ; Brain Mind Institute, Swiss Federal Institute of Technology Lausanne Lausanne, Switzerland.
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  • 2014-03-29
Published in:
  • Frontiers in neuroinformatics. - 2014
MEAs
batch analysis
cellular electrophysiology
embarrassingly parallel signal-processing
extracellular
substrate arrays of microelectrodes
English Micro-Electrode Arrays (MEAs) have emerged as a mature technique to investigate brain (dys)functions in vivo and in in vitro animal models. Often referred to as "smart" Petri dishes, MEAs have demonstrated a great potential particularly for medium-throughput studies in vitro, both in academic and pharmaceutical industrial contexts. Enabling rapid comparison of ionic/pharmacological/genetic manipulations with control conditions, MEAs are employed to screen compounds by monitoring non-invasively the spontaneous and evoked neuronal electrical activity in longitudinal studies, with relatively inexpensive equipment. However, in order to acquire sufficient statistical significance, recordings last up to tens of minutes and generate large amount of raw data (e.g., 60 channels/MEA, 16 bits A/D conversion, 20 kHz sampling rate: approximately 8 GB/MEA,h uncompressed). Thus, when the experimental conditions to be tested are numerous, the availability of fast, standardized, and automated signal preprocessing becomes pivotal for any subsequent analysis and data archiving. To this aim, we developed an in-house cloud-computing system, named QSpike Tools, where CPU-intensive operations, required for preprocessing of each recorded channel (e.g., filtering, multi-unit activity detection, spike-sorting, etc.), are decomposed and batch-queued to a multi-core architecture or to a computers cluster. With the commercial availability of new and inexpensive high-density MEAs, we believe that disseminating QSpike Tools might facilitate its wide adoption and customization, and inspire the creation of community-supported cloud-computing facilities for MEAs users.
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  • English
Open access status
gold
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Persistent URL
https://folia.unifr.ch/global/documents/10311
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