Title
Highly scalable parallel processing of extracellular recordings of multielectrode arrays Highly scalable parallel processing of extracellular recordings of multielectrode arrays
Author
Faculty/Department
Faculty of Pharmaceutical, Biomedical and Veterinary Sciences . Biomedical Sciences
Publication type
conferenceObject
Publication
New york :Ieee ,
Source (journal)
MEDICINE AND BIOLOGY SOCIETY (EMBC)
IEEE Engineering in medicine and biology society conference proceedings
Source (book)
37th Annual International Conference of the IEEE Engineering in Medicine, and Biology Society (EMBC), AUG 25-29, 2015, Milan, ITALY
Volume/pages
(2015) , p. 4178-4181
ISSN
1557-170X
ISBN
978-1-4244-9270-1
ISI
000371717204115
Carrier
E
Target language
English (eng)
Affiliation
University of Antwerp
Abstract
Technological advances of Multielectrode Arrays (MEAs) used for multi-site, parallel electrophysiological recordings, lead to an ever increasing amount of raw data being generated. Arrays with hundreds up to a few thousands of electrodes are slowly seeing widespread use and the expectation is that more sophisticated arrays will become available in the near future. In order to process the large data volumes resulting from MEA recordings there is a pressing need for new software tools able to process many data channels in parallel. Here we present a new tool for processing MEA data recordings that makes use of new programming paradigms and recent technology developments to unleash the power of modern highly parallel hardware, such as multi-core CPUs with vector instruction sets or GPGPUs. Our tool builds on and complements existing MEA data analysis packages. It shows high scalability and can be used to speed up some performance critical pre-processing steps such as data filtering and spike detection, helping to make the analysis of larger data sets tractable.
E-info
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http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000371717204115&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848
https://repository.uantwerpen.be/docman/iruaauth/bda9a2/133217.pdf
Handle