C2: Data Science

项目摘要/摘要：核心2，数据科学 数据科学核心将促进和标准化所有研究项目的数据收集和分析 在U19项目中。特别是，我们将开发收集、组织和 分析行为、成像、电生理和神经操纵数据。为了更广泛的利益 我们将采用共享数据和元数据格式，并公开我们的管道， 可用，DataJoint作为科学数据管道的通用框架，而Neurodata没有 边界格式可共享大量原始数据。该平台将促进多个组织对数据集的协作分析。 研究人员在项目中，并使我们的分析可复制和可扩展的其他人。我们将使我们 代码和数据在易于查找的开放访问存储库中公开，例如BRAIN Initiative的分布式 Archives for神经生理学数据集成和Github.我们使用这些通用数据标准将使 数据的可互操作性和可重用性，从而确保我们的数据发布符合FAIR准则。 核心的第一个目标是为神经生理学和神经生理学提供标准化的计算管道。 行为数据我们已经有了收集虚拟现实行为数据的标准化数据管道 和神经元电生理记录的预处理。我们现建议 通过三项新举措，将这一努力扩展到合作产生的所有数据。首先，我们将构建一个 共享平台，可通过模块化、用户友好的Web应用程序访问，以支持虚拟现实和 操作性条件反射任务其次，我们将扩展我们的预处理管道，用于电生理学， 钙成像数据，以支持几个国家的最先进的分割算法。自动化 预处理、系统之间的数据传输以及人工策展步骤的标准化将使 分析更快、更容易，能够更有效、更可重复地处理神经生理数据。 第三，我们将开发基础设施，以支持行为期间的扰动，包括光遗传学， 药理学和物理操作。 核心的第二个目标是记录系统，培训用户，并传播我们的计算能力。 工具和工作流。这一努力将减轻研究人员的负担，通过促进 标准软件工具，增加标准化管道的采用，并促进他人对我们数据的重用。 为了促进培训和使用这些管道，我们将开发基于网络的综合工具， 全球访问和控制本地数据处理。这些工具的模块化特性将使它们 对更广泛的神经科学界有用并受欢迎。我们将提供持续的现场培训 向所有研究人员和技术人员提供培训，包括每年与外部顾问一起提供辅导。总之，这些方法 用于自动化和标准化数据处理，当与更广泛的社区共享时，将改善 神经科学领域数据的可重复性、可重用性和互操作性。

Project Summary/Abstract: Core 2, Data Science The Data Science Core will facilitate and standardize data collection and analysis for all research projects within this U19 program. In particular, we will develop processes and systems for collecting, organizing, and analyzing behavioral, imaging, electrophysiology, and neural manipulation data. To benefit the broader neuroscience community, we will adopt shared data and metadata formats and make our pipelines publicly available, with DataJoint as the common framework for scientific data pipelines and the Neurodata without Borders format to share large raw data. This platform will facilitate collaborative analysis of datasets by multiple researchers within the project, and make our analyses reproducible and extensible by others. We will make our code and data public in easy-to-find, open-access repositories, such as the BRAIN Initiative’s Distributed Archives for Neurophysiology Data Integration and Github. Our use of these common data standards will make the data interoperable and reusable, thus ensuring that our data publications adhere to FAIR guidelines. The core’s first aim will be to provide standardized computational pipelines for neurophysiological and behavioral data. We already have standardized data pipelines for collection of virtual-reality behavioral data and preprocessing of mesoscope imaging and Neuropixels electrophysiology recordings. We now propose to extend this effort to all data generated by the collaboration, via three new initiatives. First, we will construct a shared platform, accessed by modular, user-friendly web apps, to support virtual-reality and operant-conditioning tasks. Second, we will extend our preprocessing pipeline for electrophysiology and calcium imaging data to support several state-of-the-art segmentation algorithms. Automation of preprocessing, data transfer between systems, and standardization of manual curation steps will make analyses faster and easier, enabling more effective and reproducible processing of neurophysiological data. Third, we will develop infrastructure to support perturbations during behavior, including optogenetic, pharmacological, and physical manipulations. The core’s second aim will be to document the system, train users, and disseminate our computational tools and workflows. This effort will alleviate burdens on researchers, accelerate research by promoting standard software tools, increase adoption of standardized pipelines, and facilitate reuse of our data by others. To facilitate training and use of these pipelines, we will develop integrated web-based tools that allow world-wide access and control of local data processing. The modular nature of these tools will make them useful to and popular with the broader neuroscience community. We will provide continuous, in-person training to all researchers and technicians, including yearly tutorials with external consultants. Together, these methods for automating and standardizing data handling, when shared with the broader community, will improve the reproducibility, reusability, and interoperability of data across the field of neuroscience.