The Neurodata Without Borders ecosystem for neurophysiological data science.

FAIR data Neurophysiology archive data ecosystem data language data standard human mouse neuroscience rat

Journal

eLife
ISSN: 2050-084X
Titre abrégé: Elife
Pays: England
ID NLM: 101579614

Informations de publication

Date de publication:
04 10 2022
Historique:
received: 11 03 2022
accepted: 13 05 2022
entrez: 4 10 2022
pubmed: 5 10 2022
medline: 6 10 2022
Statut: epublish

Résumé

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB's impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness. The brain is an immensely complex organ which regulates many of the behaviors that animals need to survive. To understand how the brain works, scientists monitor and record brain activity under different conditions using a variety of experimental techniques. These neurophysiological studies are often conducted on multiple types of cells in the brain as well as a variety of species, ranging from mice to flies, or even frogs and worms. Such a range of approaches provides us with highly informative, complementary ‘views’ of the brain. However, to form a complete, coherent picture of how the brain works, scientists need to be able to integrate all the data from these different experiments. For this to happen effectively, neurophysiology data need to meet certain criteria: namely, they must be findable, accessible, interoperable, and re-usable (or FAIR for short). However, the sheer diversity of neurophysiology experiments impedes the ‘FAIR’-ness of the information obtained from them. To overcome this problem, researchers need a standardized way to communicate their experiments and share their results – in other words, a ‘standard language’ to describe neurophysiology data. Rübel, Tritt, Ly, Dichter, Ghosh et al. therefore set out to create such a language that was not only FAIR, but could also co-evolve with neurophysiology research. First, they produced a computer software program (called Neurodata Without Borders, or NWB for short) which generated and defined the different components of the new standard language. Then, other tools for data management were created to expand the NWB platform using the standardized language. This included data analysis and visualization methods, as well as an ‘archive’ to store and access data. Testing the new language and associated tools showed that they indeed allowed researchers to access, analyze, and share information from many different types of experiments, in organisms ranging from flies to humans. The NWB software is open-source, meaning that anyone can obtain a copy and make changes to it. Thus, NWB and its associated resources provide the basis for a collaborative, community-based system for sharing neurophysiology data. Rübel et al. hope that NWB will inspire similar developments across other fields of biology that share similar levels of complexity with neurophysiology.

Autres résumés

Type: plain-language-summary (eng)
The brain is an immensely complex organ which regulates many of the behaviors that animals need to survive. To understand how the brain works, scientists monitor and record brain activity under different conditions using a variety of experimental techniques. These neurophysiological studies are often conducted on multiple types of cells in the brain as well as a variety of species, ranging from mice to flies, or even frogs and worms. Such a range of approaches provides us with highly informative, complementary ‘views’ of the brain. However, to form a complete, coherent picture of how the brain works, scientists need to be able to integrate all the data from these different experiments. For this to happen effectively, neurophysiology data need to meet certain criteria: namely, they must be findable, accessible, interoperable, and re-usable (or FAIR for short). However, the sheer diversity of neurophysiology experiments impedes the ‘FAIR’-ness of the information obtained from them. To overcome this problem, researchers need a standardized way to communicate their experiments and share their results – in other words, a ‘standard language’ to describe neurophysiology data. Rübel, Tritt, Ly, Dichter, Ghosh et al. therefore set out to create such a language that was not only FAIR, but could also co-evolve with neurophysiology research. First, they produced a computer software program (called Neurodata Without Borders, or NWB for short) which generated and defined the different components of the new standard language. Then, other tools for data management were created to expand the NWB platform using the standardized language. This included data analysis and visualization methods, as well as an ‘archive’ to store and access data. Testing the new language and associated tools showed that they indeed allowed researchers to access, analyze, and share information from many different types of experiments, in organisms ranging from flies to humans. The NWB software is open-source, meaning that anyone can obtain a copy and make changes to it. Thus, NWB and its associated resources provide the basis for a collaborative, community-based system for sharing neurophysiology data. Rübel et al. hope that NWB will inspire similar developments across other fields of biology that share similar levels of complexity with neurophysiology.

Identifiants

pubmed: 36193886
doi: 10.7554/eLife.78362
pii: 78362
pmc: PMC9531949
doi:
pii:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NINDS NIH HHS
ID : U24 NS120057
Pays : United States
Organisme : NIMH NIH HHS
ID : R24 MH117295
Pays : United States
Organisme : NIMH NIH HHS
ID : R24 MH116922
Pays : United States
Organisme : NIMH NIH HHS
ID : RF1 MH120034
Pays : United States
Organisme : Howard Hughes Medical Institute
Pays : United States
Organisme : NINDS NIH HHS
ID : U19 NS104590
Pays : United States

Informations de copyright

© 2022, Rübel, Tritt, Ly et al.

Déclaration de conflit d'intérêts

OR, AT, RL, SG, PB, IS, LN, KS, LF, KB No competing interests declared, BD BD is the Founder and CEO of CatalystNeuro, a software consulting company that works with neurophysiology labs to build state-of-the-art data management workflows. Much of this work involves converting data from lab-specific formats to the NWB standard, and enhancing analysis and visualization tools to read and write NWB data. As such, Dr. Dichter has a personal financial state in the success of the NWB standard, LN LN is a software engineer at MBF Bioscience, a for-profit biotech company that develops microscopy software and hardware

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Auteurs

Oliver Rübel (O)

Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, United States.

Andrew Tritt (A)

Applied Mathematics and Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, United States.

Ryan Ly (R)

Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, United States.

Benjamin K Dichter (BK)

CatalystNeuro, Benicia, United States.

Satrajit Ghosh (S)

McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, United States.
Department of Otolaryngology - Head and Neck Surgery, Harvard Medical School, Boston, United States.

Lawrence Niu (L)

MBF Bioscience, Ashburn, United States.

Pamela Baker (P)

Allen Institute for Brain Science, Seattle, United States.

Ivan Soltesz (I)

Department of Neurosurgery, Stanford University, Stanford, United States.

Lydia Ng (L)

Allen Institute for Brain Science, Seattle, United States.

Karel Svoboda (K)

Allen Institute for Brain Science, Seattle, United States.
Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States.

Loren Frank (L)

Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States.
Kavli Institute for Fundamental Neuroscience, San Francisco, United States.
Departments of Physiology and Psychiatry University of California, San Francisco, San Francisco, United States.

Kristofer E Bouchard (KE)

Scientific Data Division, Lawrence Berkeley National Laboratory, Berkeley, United States.
Kavli Institute for Fundamental Neuroscience, San Francisco, United States.
Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, United States.
Helen Wills Neuroscience Institute and Redwood Center for Theoretical Neuroscience, University of California, Berkeley, Berkeley, United States.
Weill Neurohub, Berkeley, United States.

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