Behavior and Neurodata Core

行为和神经数据核心

• 批准号: 10630555
• 负责人: DAVID L SHEINBERG
• 金额: $ 73.78万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10630555
• 关键词: Acceleration; Area; Behavior; Behavioral; Brain; Businesses; Centers of Research Excellence; Central Nervous System; Clinical; Collaborations; Communities; Complex; Consultations; Data; Data Collection; Data Set; Data Sources; Database Management Systems; Dedications; Development; Devices; Diffusion; Diffusion Magnetic Resonance Imaging; Educational workshop; Electroencephalography; Ensure; Environment; Equipment; Fees; Functional Magnetic Resonance Imaging; Galvanic Skin Response; Goals; Head; High Performance Computing; Image; Individual; Information Dissemination; Infrastructure; Internet; Knowledge; Leadership; Magnetic Resonance Imaging; Maintenance; Methods; Modeling; Modernization; Names; Nervous System Physiology; Neurosciences; Neurosciences Research; Phase; Play; Procedures; Process; Protocols documentation; Research; Research Activity; Research Infrastructure; Research Personnel; Research Project Grants; Research Project Summaries; Research Support; Resource Sharing; Resources; Rest; Rhode Island; Rodent; Role; Running; Science; Specific qualifier value; Structure; System; Techniques; Technology; Testing; Training; Transcranial magnetic stimulation; Visualization; Work; analysis pipeline; analytical tool; behavioral phenotyping; brain research; community based research; community involvement; complex data; computer infrastructure; computerized data processing; computing resources; data acquisition; data analysis pipeline; data management; data quality; data repository; data sharing; design; experimental study; fabrication; forging; meetings; multimodal neuroimaging; neuroimaging; noninvasive brain stimulation; programs; quality assurance; research facility; success; tool; transcranial direct current stimulation; visual tracking

Project Summary The research projects that have been supported by the COBRE Center for Central Nervous System Function involve a wide range of complex neuroimaging and non-invasive brain stimulation methods used both individually and in multiple combinations. These methods include, but are not limited to, structural MRI, task- based and resting state functional MRI, diffusion imaging, transcranial magnetic stimulation, transcranial direct- current and alternating-current stimulation, galvanic skin response, electroencephalography, and eye tracking. The complexity of these techniques and the challenges of mastering the infrastructure required to effectively and efficiently deploy them can significantly impede research progress, especially in the case of relatively early stage investigators. The function of the the Phase 3 Behavior and Neurodata Core (BNC) is to provide ongoing expert support, training, assistance and advice to the Brown researchers in the practical aspects of data collection, data management and data processing related to these methods. The specific aims of the BNC are (1) to continue to provide support and assistance to past COBRE Project Leaders and their research teams and the broader research community, to promote and facilitate the acquisition of high quality research data; and (2) to expand the areas of support to include new initiatives, including support for part fabrication, video tracking, and behavioral task design. To meet these aims, the Core will coordinate the deployment and maintenance of shared research infrastructure to ensure that research equipment is functional and well documented. The Core will collect and evaluate quality assurance data to ensure that data collected are of high quality and to identify and correct problems at an early stage. The Core will provide researcher training, individually and in group settings, in order to promote the use of “best practices” when collecting data using a variety of methods. It will provide expert consultation to researchers so as to guide their choices regarding the complex and interacting acquisition parameters that must be specified for various acquisition techniques. BNC experts will aid in deploying and supporting new analytical tools and platforms to ensure that researchers have access to state-of-the-art methods and tools for processing their complex data sets. The BNC will create robust data processing pipelines for the analysis of neuroscience research data that leverage the existing and growing computational infrastructure available at Brown. The BNC will assist with data management to ensure that large research datasets are available when needed and protected. In coordination with the Center for Computation and Visualization, the BNC will provide training and support for the use of high-performance computing resources. By meeting these goals, the BNC will (1) accelerate the pace of neuroscience research, (2) establish supportive collaborative relationships among COBRE investigators throughout the local research community based on common solutions to shared challenges, and (3) ensure the availability and accessibility of high quality physical and computational research infrastructure to the broader brain science community.

项目摘要 由毛cer中心神经系统功能中心支持的研究项目 涉及多种复杂的神经影像学和非侵入性脑刺激方法的使用 单独和多种组合。这些方法包括但不限于结构性MRI，任务 - 基于和静止状态的功能性MRI，扩散成像，thrancranial磁刺激，thrancranial Direct- 电流和替代性刺激，电阵皮反应，脑电图和眼动追踪。 这些技术的复杂性以及有效掌握基础架构的挑战 并且有效部署它们可能会极大地阻碍研究的进展，尤其是在相对较早的情况下 舞台调查员。第三阶段行为和Neurodata核心（BNC）的功能是提供持续的 在数据的实际方面，专家支持，培训，协助和建议 收集，数据管理和数据处理与这些方法有关。 BNC的具体目标是 （1）继续为过去的毛毛项目负责人及其研究团队提供支持和帮助 以及更广泛的研究社区，以促进和促进获得高质量的研究数据； （2）扩大支持领域以包括新计划，包括对零件制造的支持，视频 跟踪和行为任务设计。为了满足这些目标，核心将协调部署和 维护共享的研究基础设施，以确保研究设备功能正常且良好 记录。核心将收集和评估质量保证数据，以确保收集的数据是 高质量并在早期识别和纠正问题。核心将提供研究人员培训， 单独和在小组设置中，为了促进使用“最佳实践”的使用 多种方法。它将向研究人员提供专家咨询，以指导他们的选择 必须为各种采集技术指定的复杂且相互作用的采集参数。 BNC 专家将帮助部署和支持新的分析工具和平台，以确保研究人员拥有 访问用于处理其复杂数据集的最新方法和工具。 BNC将创建强大的 用于分析神经科学研究数据的数据处理管道，该数据利用现有的和 越来越多的计算基础设施可在Brown提供。 BNC将协助数据管理以确保 需要在需要并受到保护的情况下提供大型研究数据集。与中心协调 计算和可视化，BNC将为使用高性能提供培训和支持 计算资源。通过实现这些目标，BNC将（1）加速神经科学研究的速度， （2）在整个本地研究中建立毛con研究者之间的支持性合作关系 社区基于共同挑战的共同解决方案，以及（3）确保可用性和可及性 为更广泛的脑科学社区提供的高质量物理和计算研究基础设施。