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dc.contributor.author
Dyer, Eva L.
dc.contributor.author
Studer, Christoph
dc.contributor.author
Robinson, Jacob T.
dc.contributor.author
Baraniuk, Richard G.
dc.date.accessioned
2020-12-14T12:15:37Z
dc.date.available
2020-12-08T10:30:03Z
dc.date.available
2020-12-14T12:15:37Z
dc.date.issued
2013
dc.identifier.isbn
978-1-4673-1969-0
en_US
dc.identifier.other
10.1109/NER.2013.6696004
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/455243.1
dc.identifier.uri
http://hdl.handle.net/20.500.11850/455243
dc.identifier.doi
10.3929/ethz-b-000455243
dc.description.abstract
In a variety of neural data analysis problems, “neural events” such as action potentials (APs) or post-synaptic potentials (PSPs), must be recovered from noisy and possibly corrupted measurements. For instance, in calcium imaging, an AP or group of APs generate a stereotyped calcium signal with a quick rise time and slow decay. In this work, we develop a general-purpose method for: (i) learning a template waveform that signifies the presence of a neural event and (ii) neural event recovery to determine the times at which such events occur. Our approach is based upon solving a sparse signal separation problem to separate the neural signal of interest from any noise and other corruptions that arise due to baseline drift, measurement noise, and breathing/motion artifacts. For both synthetic and real measured data, we demonstrate that our approach accurately learns the underlying template waveform and detects neural events, even in the presence of strong amounts of noise and corruption. The method's robustness, simplicity, and computational efficiency makes it amenable for use in the analysis of data arising in large-scale studies of both time-varying calcium imaging and whole-cell electrophysiology.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.rights.uri
http://rightsstatements.org/page/InC-NC/1.0/
dc.title
A Robust and Efficient Method to Recover Neural Events from Noisy and Corrupted Data
en_US
dc.type
Conference Paper
dc.rights.license
In Copyright - Non-Commercial Use Permitted
dc.date.published
2014-01-06
ethz.book.title
2013 6th International IEEE/EMBS Conference on Neural Engineering (NER)
en_US
ethz.pages.start
593
en_US
ethz.pages.end
596
en_US
ethz.size
4 p.
en_US
ethz.version.deposit
acceptedVersion
en_US
ethz.event
6th International IEEE EMBS Conference on Neural Engineering (NER 2013)
en_US
ethz.event.location
San Diego, CA, USA
en_US
ethz.event.date
November 6-8, 2013
en_US
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::09695 - Studer, Christoph / Studer, Christoph
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02140 - Dep. Inf.technologie und Elektrotechnik / Dep. of Inform.Technol. Electrical Eng.::02636 - Institut für Integrierte Systeme / Integrated Systems Laboratory::09695 - Studer, Christoph / Studer, Christoph
en_US
ethz.date.deposited
2020-12-08T10:30:13Z
ethz.source
FORM
ethz.eth
no
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2021-02-15T22:11:44Z
ethz.rosetta.lastUpdated
2021-02-15T22:11:44Z
ethz.rosetta.versionExported
true
ethz.rosetta.versionExported
true
ethz.COinS
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