Mahmud, M., Pulizzi, R., Vasilaki, E. orcid.org/0000-0003-3705-7070 et al. (1 more author) (2014) QSpike tools: a generic framework for parallel batch preprocessing of extracellular neuronal signals recorded by substrate microelectrode arrays. Frontiers in Neuroinformatics, 8. 26. ISSN 1662-5196
Abstract
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.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2014 Mahmud, Pulizzi, Vasilaki and Giugliano. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. http://creativecommons.org/licenses/by/3.0/ |
Keywords: | MEAs; batch analysis; cellular electrophysiology; embarrassingly parallel signal-processing; extracellular; substrate arrays of microelectrodes |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 10 May 2016 09:10 |
Last Modified: | 10 May 2016 09:15 |
Published Version: | http://dx.doi.org/10.3389/fninf.2014.00026 |
Status: | Published |
Publisher: | Frontiers Media |
Refereed: | Yes |
Identification Number: | 10.3389/fninf.2014.00026 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:89086 |