CRCNS: US-France Data Sharing Proposal: Lowering the barrier of entry to network neuroscience

CRCNS：美法数据共享提案：降低网络神经科学的准入门槛

• 批准号: 10262925
• 负责人: Danielle Smith Bassett
• 金额: $ 11.27万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-16 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10262925
• 关键词: Address; Aging; Behavior; Biophysics; Brain; Clinical; Cloud Computing; Cognition; Communities; Complex Analysis; Computer software; Data; Data Set; Development; Disease; Documentation; Ecosystem; Education; Elements; France; Funding; Generations; Graph; Growth; Health; Infrastructure; Instruction; Knowledge; Language; Lead; Libraries; Link; Literature; Mathematics; Methods; Modeling; Neurosciences; Neurosciences Research; Pathway Analysis; Play; Process; Reporting; Reproducibility; Research; Research Personnel; Resources; Role; Running; Science; Sociology; Source; Standardization; Structure; Study models; System; Techniques; Time; Training; Work; analysis pipeline; brain computer interface; cloud based; cognitive process; cyber infrastructure; data sharing; experience; innovation; insight; interest; machine learning method; network architecture; network models; neuroimaging; open data; prevent; relating to nervous system; statistics; support network; synergism; tool

The field of network neuroscience has developed powerful analysis tools for studying brain networks and holds promise for deepening our understanding of the role played by brain networks in health, disease, development, and cognition. Despite widespread interest, barriers exist that prevent these tools from having broader impact. These include (1) unstandardized practices for sharing and documenting software, (2) long delays from when a method is first introduced to when it becomes publicly available, and (3) gaps in theoretic knowledge and understanding leading to incorrect, delays due to mistakes, and errors in reported results. These barriers ultimately slow the rate of neuroscientific discovery and stall progress in applied domains. To overcome these challenges, we will use open science methods and cloud-computing, to increase the availability of network neuroscience tools. We will use the platform "brainlife.io" for sharing these tools, which will be packaged into self-contained, standardized, reproducible Apps, shared with and modified by a community of users, and integrated into existing brainlife.io analysis pipelines. Apps will also be accompanied by links to primary sources, in-depth tutorials, and documentation, and worked-through examples, highlighting their correct usage and offering solutions for mitigating possible pitfalls. In standardizing and packaging network neuroscience tools as Apps, this proposed research will engage a new generation of neuroscientists, providing them powerful new and leading to new discoveries. Second, the proposed research will contribute growing suite of modeling analysis that can be modified to suit specialized purposes. Finally, the Brainlife.io platform will serve as part of the infrastructure supporting neuroscience research. Altogether, these advances will lead to new opportunities in network neuroscience research and further stimulate its growth while increasing synergies with other domains in neuroscience.

网络神经科学领域已经开发出强大的分析工具来研究大脑网络和 有望加深我们对大脑网络在健康、疾病、 发展、认知。尽管人们广泛感兴趣，但仍然存在阻碍这些工具发挥作用的障碍。 更广泛的影响。其中包括 (1) 共享和记录软件的非标准化实践，(2) 长期的 从首次引入方法到公开可用的延迟，以及（3）理论差距 知识和理解导致不正确、错误导致的延误以及报告结果的错误。 这些障碍最终减缓了神经科学发现的速度并阻碍了应用领域的进展。 为了克服这些挑战，我们将使用开放科学方法和云计算来提高 网络神经科学工具的可用性。我们将使用“brainlife.io”平台来分享这些工具， 将被打包成独立的、标准化的、可复制的应用程序，与 用户社区，并集成到现有的 Brainlife.io 分析管道中。应用程序也将伴随 通过主要来源、深入教程和文档以及经过实践的示例的链接， 强调它们的正确用法并提供解决方案以减少可能的陷阱。 在将网络神经科学工具标准化和打包为应用程序时，这项拟议的研究将涉及 新一代神经科学家，为他们提供强大的新发现并带来新的发现。其次， 拟议的研究将贡献越来越多的建模分析套件，可以对其进行修改以适应专业化 目的。最后，Brainlife.io 平台将作为支持神经科学的基础设施的一部分 研究。总而言之，这些进步将为网络神经科学研究带来新的机遇 进一步刺激其发展，同时增加与神经科学其他领域的协同作用。

项目成果

Open science, communal culture, and women's participation in the movement to improve science.

开放科学、公共文化以及妇女参与提高科学水平的运动。

• 发表时间: 2020
• 影响因子: 11.1
• 作者: Murphy, Mary C;Mejia, Amanda F;Mejia, Jorge;Yan, Xiaoran;Cheryan, Sapna;Dasgupta, Nilanjana;Destin, Mesmin;Fryberg, Stephanie A;Garcia, Julie A;Haines, Elizabeth L;Harackiewicz, Judith M;Ledgerwood, Alison;Moss;Park, Lora E
• 通讯作者: Park, Lora E

The spread of COVID-19 increases with individual mobility and depends on political leaning.

COVID-19 的传播随着个人流动性的增加而增加，并取决于政治倾向。

• 发表时间: 2021-02-04
• 作者: Parker, Chris;Mejia, Jorge;Pestilli, Franco
• 通讯作者: Pestilli, Franco