OpenNeuro: An open archive for analysis and sharing of BRAIN Initiative data

OpenNeuro：用于分析和共享 BRAIN Initiative 数据的开放档案

• 批准号: 10451257
• 负责人: Russell A Poldrack
• 金额: $ 162.99万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10451257
• 关键词: Address; Adoption; Agreement; Architecture; Archives; BRAIN initiative; Brain; Brain imaging; Client; Collaborations; Computer software; Custom; Data; Data Set; Databases; Dedications; Development; Electroencephalography; Electromagnetics; Ensure; FAIR principles; Funding; Funding Agency; Goals; Grant; Growth; Health; Human; Informatics; Investments; Licensing; Link; Magnetic Resonance Imaging; Manuals; Measures; Metadata; Modality; Neurosciences; Neurosciences Research; Ontology; Performance; Policies; Positron-Emission Tomography; Process; Public Domains; Quality Control; Reporting; Reproducibility; Request for Proposals; Research; Research Personnel; Retrieval; Side; Site; Specific qualifier value; Standardization; Statistical Models; System; Testing; United States National Institutes of Health; Work; data archive; data integration; data management; data modeling; data reuse; data sharing; data structure; digital object identifier; distributed archives; flexibility; human subject; improved; neuroimaging; neurophysiology; open data; permissiveness; programs; repository; sharing platform; software development; success; usability; web site

Project Summary/Abstract The BRAIN Initiative is supporting a broad portfolio of neuroscience research aimed at revolutionizing our understanding of the brain. The sharing of data obtained from this research is critical both to leveraging this major public investment and to ensuring the rigor and reproducibility of NIH-funded research. We propose a renewal of support for the OpenNeuro data archive, which provides a platform for the storage, processing, and sharing of neuroimaging data collected as part of the BRAIN Initiative. OpenNeuro enables researchers to easily share a broad range of neuroscience data types, based on the Brain Imaging Data Structure standard for organizing datasets. The platform shares data openly and provides researchers with several avenues to access and reuse the data. In the renewal period we propose to continue supporting a high level of performance for the archive, and to extend the work done in the initial grant period. First, we will provide a specialized portal for BRAIN Initiative investigators, which will help more clearly link their research to funding sources, and to provide them with the ability to more flexibly select an appropriate data use agreement. We will also implement enhanced user profiles, linking shared datasets to standard researcher identities through the ORCID system. Second, we will enhance the ability to search for datasets by improving the ability for researchers to specify metadata that is linked to standard ontologies. Third, will improve the reusability of OpenNeuro datasets by providing support for the sharing of derivative data as well as statistical models, and by providing preprocessed data and quality control reports. Together, these improvements will sustain the success of the OpenNeuro archive and provide neuroscientists with increasingly usable data to address fundamental problems of brain function and health.

项目摘要/摘要 大脑计划正在支持广泛的神经科学研究组合，旨在彻底改变我们的 对大脑的理解。共享从这项研究中获得的数据对于利用这一点是至关重要的 主要的公共投资，并确保国家卫生研究院资助的研究的严密性和重复性。我们提出了一个 续订对OpenNeuro数据归档的支持，该归档为存储、处理和 共享作为大脑倡议的一部分收集的神经成像数据。OpenNeuro使研究人员能够轻松地 共享广泛的神经科学数据类型，基于的大脑成像数据结构标准 组织数据集。该平台公开共享数据，并为研究人员提供了多种访问途径 并重复使用这些数据。在续订期间，我们建议继续支持高水平的 此外，还要求建立一个档案库，并延长在最初批给期内完成的工作。首先，我们将为以下内容提供专门的门户 Brain Initiative调查人员，这将有助于更清楚地将他们的研究与资金来源联系起来，并提供 他们有能力更灵活地选择适当的数据使用协议。我们还将实施增强的 用户配置文件，通过ORCID系统将共享数据集与标准研究人员身份联系起来。第二，我们 将通过提高研究人员指定以下元数据的能力来增强搜索数据集的能力 链接到标准本体论。第三，将通过提供以下支持来提高OpenNeuro数据集的可重用性 分享衍生数据和统计模型，并通过提供经过预处理的数据和质量 控制报告。总之，这些改进将维持OpenNeuro档案的成功，并提供 神经科学家提供越来越有用的数据，以解决大脑功能和健康的根本问题。

项目成果

PET-BIDS, an extension to the brain imaging data structure for positron emission tomography.

• DOI: 10.1038/s41597-022-01164-1
• 发表时间: 2022-03-02
• 期刊: Scientific data
• 影响因子: 9.8
• 作者: Norgaard M;Matheson GJ;Hansen HD;Thomas A;Searle G;Rizzo G;Veronese M;Giacomel A;Yaqub M;Tonietto M;Funck T;Gillman A;Boniface H;Routier A;Dalenberg JR;Betthauser T;Feingold F;Markiewicz CJ;Gorgolewski KJ;Blair RW;Appelhoff S;Gau R;Salo T;Niso G;Pernet C;Phillips C;Oostenveld R;Gallezot JD;Carson RE;Knudsen GM;Innis RB;Ganz M
• 通讯作者: Ganz M

A comparison of neuroelectrophysiology databases.

• DOI: 10.1038/s41597-023-02614-0
• 发表时间: 2023-10-19
• 期刊: Scientific data
• 影响因子: 9.8
• 作者: Subash P;Gray A;Boswell M;Cohen SL;Garner R;Salehi S;Fisher C;Hobel S;Ghosh S;Halchenko Y;Dichter B;Poldrack RA;Markiewicz C;Hermes D;Delorme A;Makeig S;Behan B;Sparks A;Arnott SR;Wang Z;Magnotti J;Beauchamp MS;Pouratian N;Toga AW;Duncan D
• 通讯作者: Duncan D

Benchmarking explanation methods for mental state decoding with deep learning models.

• DOI: 10.1016/j.neuroimage.2023.120109
• 发表时间: 2023-06
• 期刊: NEUROIMAGE
• 影响因子: 5.7
• 作者: Thomas, Armin W.;Re, Christopher;Poldrack, Russell A.
• 通讯作者: Poldrack, Russell A.

The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)

• DOI: 10.1162/imag_a_00103
• 发表时间: 2023-09
• 期刊: ArXiv
• 作者: R. Poldrack;Christopher J. Markiewicz;S. Appelhoff;Yoni K. Ashar;Tibor Auer;Sylvain Baillet;Shashank Bansal;Leandro Beltrachini;C. Bénar;G. Bertazzoli;Suyash Bhogawar;Ross W. Blair;M. Bortoletto;M. Boudreau;Teon L Brooks;V. Calhoun;F. Castelli;Patricia Clement;Alexander L Cohen;J. Cohen-Adad;Sasha D'Ambrosio;G. Hollander;M. D. L. iglesia-Vay'a;A. D. L. Vega;Arnaud Delorme;O. Devinsky;Dejan Draschkow;E. Duff;E. Dupre;Eric Earl;Oscar Esteban;Franklin W. Feingold;G. Flandin;Anthony Galassi;Giuseppe Gallitto;M. Ganz;Rémi Gau;J. Gholam;Sulagna Dia Ghosh;A. Giacomel;A. Gillman;P. Gleeson;Alexandre Gramfort;Samuel Guay;G. Guidali;Y. Halchenko;D. Handwerker;Nell Hardcastle;P. Herholz;Dora Hermes;C. Honey;R. Innis;Horea-Ioan Ioanas;Andrew Jahn;A. Karakuzu;D. Keator;Gregory Kiar;Bálint Kincses;A. Laird;Jonathan C. Lau;A. Lazari;Jon Haitz Legarreta;Adam Li;Xiangrui Li;B. Love;Hanzhang Lu;Camille Maumet;G. Mazzamuto;S. Meisler;Mark Mikkelsen;Henk‐Jan Mutsaerts;Thomas E. Nichols;A. Nikolaidis;G. Nilsonne;Guiomar Niso;M. Nørgaard;T. Okell;R. Oostenveld;Eduard Ort;Patrick J. Park;Mateusz Pawlik;C. Pernet;F. Pestilli;Jan Petr;Christophe Phillips;J B Poline;L. Pollonini;P. Raamana;Petra Ritter;Gaia Rizzo;Kay A. Robbins;A. Rockhill;Christine Rogers;A. Rokem;C. Rorden;A. Routier;J. M. Saborit-Torres;T. Salo;M. Schirner;Robert E. Smith;T. Spisák;Julia Sprenger;Nicole C. Swann;Martin Szinte;S. Takerkart;Bertrand Thirion;Adam G. Thomas;Sajjad Torabian;G. Varoquaux;Bradley Voytek;Julius Welzel;Martin Wilson;Tal Yarkoni;Krzysztof J. Gorgolewski

A data resource from concurrent intracranial stimulation and functional MRI of the human brain.

来自并发颅内刺激和人脑功能 MRI 的数据资源。

• DOI: 10.1038/s41597-020-00595-y
• 发表时间: 2020
• 期刊: Scientific data
• 影响因子: 9.8
• 作者: Thompson,WH;Nair,R;Oya,H;Esteban,O;Shine,JM;Petkov,CI;Poldrack,RA;Howard,M;Adolphs,R
• 通讯作者: Adolphs,R