Neo: an object model for handling electrophysiology data in multiple formats

dc.contributor.authorGarcia, Samuel
dc.contributor.authorGuarino, Domenico
dc.contributor.authorJaillet, Florent
dc.contributor.authorJennings, Todd
dc.contributor.authorPröpper, Robert
dc.contributor.authorRautenberg, Philipp L.
dc.contributor.authorRodgers, Chris C.
dc.contributor.authorSobolev, Andrey
dc.contributor.authorWachtler, Thomas
dc.contributor.authorYger, Pierre
dc.contributor.authorDavison, Andrew P.
dc.date.accessioned2019-11-01T12:28:39Z
dc.date.available2019-11-01T12:28:39Z
dc.date.issued2014-02-20
dc.date.updated2019-09-29T20:49:32Z
dc.description.abstractNeuroscientists use many different software tools to acquire, analyze and visualize electrophysiological signals. However, incompatible data models and file formats make it difficult to exchange data between these tools. This reduces scientific productivity, renders potentially useful analysis methods inaccessible and impedes collaboration between labs. A common representation of the core data would improve interoperability and facilitate data-sharing. To that end, we propose here a language-independent object model, named “Neo,” suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. As a concrete instantiation of this object model we have developed an open source implementation in the Python programming language. In addition to representing electrophysiology data in memory for the purposes of analysis and visualization, the Python implementation provides a set of input/output (IO) modules for reading/writing the data from/to a variety of commonly used file formats. Support is included for formats produced by most of the major manufacturers of electrophysiology recording equipment and also for more generic formats such as MATLAB. Data representation and data analysis are conceptually separate: it is easier to write robust analysis code if it is focused on analysis and relies on an underlying package to handle data representation. For that reason, and also to be as lightweight as possible, the Neo object model and the associated Python package are deliberately limited to representation of data, with no functions for data analysis or visualization. Software for neurophysiology data analysis and visualization built on top of Neo automatically gains the benefits of interoperability, easier data sharing and automatic format conversion; there is already a burgeoning ecosystem of such tools. We intend that Neo should become the standard basis for Python tools in neurophysiology.en
dc.description.sponsorshipEC/FP7/269921/EU/Brain-inspired multiscale computation in neuromorphic hybrid systems/BrainScaleSen
dc.description.sponsorshipDFG, 103586207, GRK 1589: Verarbeitung sensorischer Informationen in neuronalen Systemenen
dc.description.sponsorshipBMBF, 01GQ1302, Nationaler Neuroinformatik Knotenen
dc.identifier.eissn1662-5196
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/10234
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-9195
dc.language.isoenen
dc.rights.urihttps://creativecommons.org/licenses/by/3.0/en
dc.subject.ddc004 Datenverarbeitung; Informatikde
dc.subject.ddc610 Medizin und Gesundheitde
dc.subject.otherelectrophysiologyen
dc.subject.otherinteroperabilityen
dc.subject.otherPythonen
dc.subject.othersoftwareen
dc.subject.otherfile formatsen
dc.titleNeo: an object model for handling electrophysiology data in multiple formatsen
dc.typeArticleen
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber10en
dcterms.bibliographicCitation.doi10.3389/fninf.2014.00010en
dcterms.bibliographicCitation.journaltitleFrontiers in Neuroinformaticsen
dcterms.bibliographicCitation.originalpublishernameFrontiers Media S.A.en
dcterms.bibliographicCitation.originalpublisherplaceLausanneen
dcterms.bibliographicCitation.volume8en
tub.accessrights.dnbfreeen
tub.affiliationFak. 4 Elektrotechnik und Informatik::Inst. Softwaretechnik und Theoretische Informatik::FG Neuronale Informationsverarbeitungde
tub.affiliation.facultyFak. 4 Elektrotechnik und Informatikde
tub.affiliation.groupFG Neuronale Informationsverarbeitungde
tub.affiliation.instituteInst. Softwaretechnik und Theoretische Informatikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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