Cargando…

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

Neuroscientists 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 metho...

Descripción completa

Detalles Bibliográficos
Autores principales: Garcia, Samuel, Guarino, Domenico, Jaillet, Florent, Jennings, Todd, Pröpper, Robert, Rautenberg, Philipp L., Rodgers, Chris C., Sobolev, Andrey, Wachtler, Thomas, Yger, Pierre, Davison, Andrew P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3930095/
https://www.ncbi.nlm.nih.gov/pubmed/24600386
http://dx.doi.org/10.3389/fninf.2014.00010
_version_ 1782304497227268096
author Garcia, Samuel
Guarino, Domenico
Jaillet, Florent
Jennings, Todd
Pröpper, Robert
Rautenberg, Philipp L.
Rodgers, Chris C.
Sobolev, Andrey
Wachtler, Thomas
Yger, Pierre
Davison, Andrew P.
author_facet Garcia, Samuel
Guarino, Domenico
Jaillet, Florent
Jennings, Todd
Pröpper, Robert
Rautenberg, Philipp L.
Rodgers, Chris C.
Sobolev, Andrey
Wachtler, Thomas
Yger, Pierre
Davison, Andrew P.
author_sort Garcia, Samuel
collection PubMed
description Neuroscientists 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.
format Online
Article
Text
id pubmed-3930095
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-39300952014-03-05 Neo: an object model for handling electrophysiology data in multiple formats Garcia, Samuel Guarino, Domenico Jaillet, Florent Jennings, Todd Pröpper, Robert Rautenberg, Philipp L. Rodgers, Chris C. Sobolev, Andrey Wachtler, Thomas Yger, Pierre Davison, Andrew P. Front Neuroinform Neuroscience Neuroscientists 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. Frontiers Media S.A. 2014-02-20 /pmc/articles/PMC3930095/ /pubmed/24600386 http://dx.doi.org/10.3389/fninf.2014.00010 Text en Copyright © 2014 Garcia, Guarino, Jaillet, Jennings, Pröpper, Rautenberg, Rodgers, Sobolev, Wachtler, Yger and Davison. http://creativecommons.org/licenses/by/3.0/ 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.
spellingShingle Neuroscience
Garcia, Samuel
Guarino, Domenico
Jaillet, Florent
Jennings, Todd
Pröpper, Robert
Rautenberg, Philipp L.
Rodgers, Chris C.
Sobolev, Andrey
Wachtler, Thomas
Yger, Pierre
Davison, Andrew P.
Neo: an object model for handling electrophysiology data in multiple formats
title Neo: an object model for handling electrophysiology data in multiple formats
title_full Neo: an object model for handling electrophysiology data in multiple formats
title_fullStr Neo: an object model for handling electrophysiology data in multiple formats
title_full_unstemmed Neo: an object model for handling electrophysiology data in multiple formats
title_short Neo: an object model for handling electrophysiology data in multiple formats
title_sort neo: an object model for handling electrophysiology data in multiple formats
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3930095/
https://www.ncbi.nlm.nih.gov/pubmed/24600386
http://dx.doi.org/10.3389/fninf.2014.00010
work_keys_str_mv AT garciasamuel neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT guarinodomenico neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT jailletflorent neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT jenningstodd neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT propperrobert neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT rautenbergphilippl neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT rodgerschrisc neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT sobolevandrey neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT wachtlerthomas neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT ygerpierre neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats
AT davisonandrewp neoanobjectmodelforhandlingelectrophysiologydatainmultipleformats