iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology

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Abstract

The Brain Imaging Data Structure (BIDS) is a community-driven specification for organizing neuroscience data and metadata with the aim to make datasets more transparent, reusable, and reproducible. Intracranial electroencephalography (iEEG) data offer a unique combination of high spatial and temporal resolution measurements of the living human brain. To improve internal (re)use and external sharing of these unique data, we present a specification for storing and sharing iEEG data: iEEG-BIDS.

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Most cited references 11

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Decoupling the cortical power spectrum reveals real-time representation of individual finger movements in humans.

K Miller, S Zanos, E E Fetz … (2009)

During active movement the electric potentials measured from the surface of the motor cortex exhibit consistent modulation, revealing two distinguishable processes in the power spectrum. At frequencies <40 Hz, narrow-band power decreases occur with movement over widely distributed cortical areas, while at higher frequencies there are spatially more focal power increases. These high-frequency changes have commonly been assumed to reflect synchronous rhythms, analogous to lower-frequency phenomena, but it has recently been proposed that they reflect a broad-band spectral change across the entire spectrum, which could be obscured by synchronous rhythms at low frequencies. In 10 human subjects performing a finger movement task, we demonstrate that a principal component type of decomposition can naively separate low-frequency narrow-band rhythms from an asynchronous, broad-spectral, change at all frequencies between 5 and 200 Hz. This broad-spectral change exhibited spatially discrete representation for individual fingers and reproduced the temporal movement trajectories of different individual fingers.

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THE BRAIN’S RECORD OF AUDITORY AND VISUAL EXPERIENCE

PHANOR PEROT, WILDER PENFIELD (1963)

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Big data from small data: data-sharing in the 'long tail' of neuroscience.

Adam R Ferguson, Jessica L. Nielson, Melissa H Cragin … (2014)

The launch of the US BRAIN and European Human Brain Projects coincides with growing international efforts toward transparency and increased access to publicly funded research in the neurosciences. The need for data-sharing standards and neuroinformatics infrastructure is more pressing than ever. However, 'big science' efforts are not the only drivers of data-sharing needs, as neuroscientists across the full spectrum of research grapple with the overwhelming volume of data being generated daily and a scientific environment that is increasingly focused on collaboration. In this commentary, we consider the issue of sharing of the richly diverse and heterogeneous small data sets produced by individual neuroscientists, so-called long-tail data. We consider the utility of these data, the diversity of repositories and options available for sharing such data, and emerging best practices. We provide use cases in which aggregating and mining diverse long-tail data convert numerous small data sources into big data for improved knowledge about neuroscience-related disorders.

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Author and article information

Contributors

Christopher Holdgraf: choldgraf@berkeley.edu

Dora Hermes: dorahermes@gmail.com

Journal

Journal ID (nlm-ta): Sci Data

Journal ID (iso-abbrev): Sci Data

Title: Scientific Data

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2052-4463

Publication date (Electronic): 25 June 2019

Publication date PMC-release: 25 June 2019

Publication date Collection: 2019

Volume: 6

Electronic Location Identifier: 102

Affiliations

[1 ]The Berkeley Institute for Data Science, Berkeley, USA

[2 ]ISNI 0000 0000 9859 7917, GRID grid.419526.d, Center for Adaptive Rationality, Max Planck Institute for Human Development, ; Berlin, Germany

[3 ]Feinstein Institute for Medical Research, Hofstra Northwell School of Medicine, New York, USA

[4 ]ISNI 0000 0001 2231 4551, GRID grid.184769.5, Biological Systems and Engineering Division, Lawrence Berkeley Lab, ; Berkeley, USA

[5 ]ISNI 0000 0004 1757 2822, GRID grid.4708.b, Università degli Studi di Milano, ; Milan, Italy

[6 ]GRID grid.450307.5, Universite Grenoble Alpes, ; Inserm, France

[7 ]ISNI 0000 0004 1936 8753, GRID grid.137628.9, NYU School of Medicine, ; New York, USA

[8 ]ISNI 0000000419368956, GRID grid.168010.e, Stanford University, ; Stanford, USA

[9 ]ISNI 0000 0001 2160 926X, GRID grid.39382.33, Baylor College of Medicine, ; Houston, Texas USA

[10 ]ISNI 0000 0004 1936 8753, GRID grid.137628.9, New York University, ; New York, USA

[11 ]Krembil Research Institute, Toronto, USA

[12 ]ISNI 0000 0004 1936 8091, GRID grid.15276.37, University of Florida, ; Gainesville, USA

[13 ]ISNI 0000 0004 1936 9924, GRID grid.89336.37, The University of Texas at Austin, ; Austin, USA

[14 ]ISNI 0000 0001 2171 9311, GRID grid.21107.35, Johns Hopkins University, ; Baltimore, USA

[15 ]ISNI 0000 0004 0386 9924, GRID grid.32224.35, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Med. School, ; Charlestown, USA

[16 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, University of California at Berkeley, ; Berkeley, USA

[17 ]Centre de Recherche en Neurosciences de Lyon, INSERM, Lyon, France

[18 ]ISNI 0000 0004 1936 8884, GRID grid.39381.30, Department of Clinical Neurological Sciences, Division of Neurosurgery, Western University, ; London, Canada

[19 ]ISNI 0000 0004 0459 167X, GRID grid.66875.3a, Mayo Clinic, ; Rochester, USA

[20 ]ISNI 0000 0004 0459 167X, GRID grid.66875.3a, Department of Neurosurgery, Mayo Clinic, ; Rochester, USA

[21 ]ISNI 0000000122986657, GRID grid.34477.33, University of Washington, ; Washington, USA

[22 ]ISNI 0000000122931605, GRID grid.5590.9, Radboud University, Donders Institute for Brain, Cognition and Behaviour, Karolinska Institutet, ; Nijmegen, The Netherlands

[23 ]ISNI 0000000090126352, GRID grid.7692.a, Center for Image Sciences, University Medical Center Utrecht, ; Utrecht, The Netherlands

[24 ]ISNI 0000000090126352, GRID grid.7692.a, UMC Utrecht Brain Center, ; Utrecht, The Netherlands

[25 ]ISNI 0000 0000 9632 6718, GRID grid.19006.3e, David Geffen School of Medicine at UCLA, ; California, USA

[26 ]ISNI 0000 0004 1936 8008, GRID grid.170202.6, University of Oregon, ; Oregon, USA

[27 ]ISNI 0000 0004 0429 3736, GRID grid.462307.4, CHU Grenoble Alpes, GIN, ; Grenoble, France

[28 ]ISNI 0000 0001 2107 4242, GRID grid.266100.3, UC San Diego, ; San Diego, USA

[29 ]ISNI 0000 0004 5903 3632, GRID grid.499548.d, Alan Turing Institute, ; London, UK

[30 ]ISNI 0000 0001 2297 375X, GRID grid.8385.6, Institute for Neuroscience and Medicine (INM-1), Forschungszentrum Jülich GmbH, ; Jülich, Germany

[31 ]ISNI 0000 0004 0459 167X, GRID grid.66875.3a, Department of Physiology & Biomedical Engineering, Mayo Clinic, ; Rochester, USA

[32 ]ISNI 0000000121885934, GRID grid.5335.0, Department of Psychiatry, , University of Cambridge, ; Cambridge, UK

Author information

Stefan Appelhoff http://orcid.org/0000-0001-8002-0877

Sasha D’Ambrosio http://orcid.org/0000-0002-6600-6419

Orrin Devinsky http://orcid.org/0000-0003-0044-4632

Adeen Flinker http://orcid.org/0000-0003-1247-1283

Krzysztof J. Gorgolewski http://orcid.org/0000-0003-3321-7583

Iris Groen http://orcid.org/0000-0002-5536-6128

Liberty Hamilton http://orcid.org/0000-0003-0182-2500

Brian N. Lundstrom http://orcid.org/0000-0002-5310-5549

Robert Oostenveld http://orcid.org/0000-0002-1974-1293

Gio Piantoni http://orcid.org/0000-0002-5308-926X

Nick F. Ramsey http://orcid.org/0000-0002-7136-259X

Arjen Stolk http://orcid.org/0000-0003-3798-4923

Jonathan Winawer http://orcid.org/0000-0001-7475-5586

Lyuba Zehl http://orcid.org/0000-0002-5947-9939

Article

Publisher ID: 105

DOI: 10.1038/s41597-019-0105-7

PMC ID: 6592874

PubMed ID: 31239438

SO-VID: 8021b239-6e0f-4c5c-b099-85f911f21e2a

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 29 January 2019

Date accepted : 24 May 2019

Funding

Funded by: The Gordon and Betty Moore Foundation | GBMF3834 The Alfred P. Sloan Foundation | 2013-10-27

Funded by: Max Planck Institute for Human Development

Funded by: NYS ECRIP Fellowship

Funded by: NIH

Funded by: European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement no. 616268 F-TRACT; European Union&#x2019;s Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 785907 (Human Brain Project SGA2)

Funded by: U19-NS104590

Funded by: NIMH R01MH116914

Funded by: NIMH R24-MH114705-01

Funded by: National Institutes of Health

Funded by: Ontario Brain Institute

Funded by: NIH, NSF

Funded by: Sloan Research Fellowship, NIMH (MH111439-01)

Funded by: NINDS R37NS21135

Funded by: European Union&#x2019;s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 785907 (HBP SGA2)

Funded by: Canadian Institute of Health Research

Funded by: Wu Tsai Neurosciences Institute

Funded by: Mayo Clinic Foundation

Funded by: Van Wagenen Foundation

Funded by: NSF ERC EEC-1028725

Funded by: EU-H2020 Marie Curie &#x201C;ChildBrain&#x201D; Innovative Training Network grant no. 641652

Funded by: NIH, NIMH, BRAIN Initiative grant #: R01MH111417

Funded by: Human Brain Project SGA1 (No. 720270) and Human Brain Project SGA2 (No. 785907), SNSF - Sinergia CRSII3_160803/1 of the Swiss National Science Foundation

Funded by: NIH/NIMH R24MH114796

Funded by: Marie Sklodowska-Curie Global Fellowship from the European Union (658868)

Funded by: Sloan Research Fellowship (FG-2015-66057), the Whitehall Foundation (2017-12-73), and the National Science Foundation under grant BCS-1736028.

Funded by: Simons Foundation

Funded by: FundRef https://doi.org/10.13039/501100000266, RCUK | Engineering and Physical Sciences Research Council (EPSRC);

Award ID: EP/N510129/1

Award Recipient : Kirstie Whitaker

Funded by: European Union&#x2019;s Horizon 2020 Research and Innovation Programme 720270 (HBP SGA1) and 785907 (HBP SGA2)

Funded by: The Netherlands Organisation for Scientific Research | NWO, 016.VENI.178.048

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Keywords: software,cognitive neuroscience,data publication and archiving

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Keywords: software, cognitive neuroscience, data publication and archiving

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iEEG-BIDS, extending the Brain Imaging Data Structure specification to human intracranial electrophysiology

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Abstract

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NeuroImaging Methods

Most cited references 11

Decoupling the cortical power spectrum reveals real-time representation of individual finger movements in humans.

THE BRAIN’S RECORD OF AUDITORY AND VISUAL EXPERIENCE

Big data from small data: data-sharing in the 'long tail' of neuroscience.

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Cited by 57

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