Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline
Neuroimaging Study Designs, Computational Analyses and Data Provenance Using the LONI Pipeline
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DOI：
10.1371/journal.pone.0013070
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发表时间：
2010-09-28
期刊：
影响因子：
3.7
通讯作者：
Toga, Arthur
中科院分区：
文献类型：
--
作者：
Dinov, Ivo;Lozev, Kamen;Toga, Arthur
现代计算神经科学使用不同的软件工具和多学科的专业知识来分析不同种类的大脑数据。收集有意义的数据、拟合特定模型以及发现合适的分析和可视化工具的经典问题，让位于一类新的计算挑战--管理大型和不一致的数据、计算资源的集成和互操作性以及数据来源。我们设计、实施并验证了一种新的范式，以应对神经成像领域的这些挑战。我们的解决方案基于LONI管道环境[3，4]，这是一个用于构建和执行复杂数据处理协议的图形化工作流环境。我们在LONI管道内开发了研究设计、数据库和可视化语言编程功能，使我们能够构建完整、精细和强大的图形工作流程，用于分析神经成像和其他数据。这些工作流程促进了数据和元数据、具体处理协议、结果验证以及不同调查人员和研究小组之间的研究复制的开放共享和交流。LONI管道的功能包括分布式网格基础设施、虚拟执行环境、高效集成、数据来源、新计算工具的验证和分发、自动数据格式转换以及直观的图形用户界面。我们使用基于国际脑成像联合会[5]和阿尔茨海默病神经成像倡议[6]的数据的大规模神经成像研究来演示新的LONI管道功能。有关LONI管道环境的用户指南、论坛、说明和下载，请访问http://pipeline.loni.ucla.edu.
Modern computational neuroscience employs diverse software tools and multidisciplinary expertise to analyze heterogeneous brain data. The classical problems of gathering meaningful data, fitting specific models, and discovering appropriate analysis and visualization tools give way to a new class of computational challenges-management of large and incongruous data, integration and interoperability of computational resources, and data provenance. We designed, implemented and validated a new paradigm for addressing these challenges in the neuroimaging field. Our solution is based on the LONI Pipeline environment [3,4], a graphical workflow environment for constructing and executing complex data processing protocols. We developed study-design, database and visual language programming functionalities within the LONI Pipeline that enable the construction of complete, elaborate and robust graphical workflows for analyzing neuroimaging and other data. These workflows facilitate open sharing and communication of data and metadata, concrete processing protocols, result validation, and study replication among different investigators and research groups. The LONI Pipeline features include distributed grid-enabled infrastructure, virtualized execution environment, efficient integration, data provenance, validation and distribution of new computational tools, automated data format conversion, and an intuitive graphical user interface. We demonstrate the new LONI Pipeline features using large scale neuroimaging studies based on data from the International Consortium for Brain Mapping [5] and the Alzheimer's Disease Neuroimaging Initiative [6]. User guides, forums, instructions and downloads of the LONI Pipeline environment are available at http://pipeline.loni.ucla.edu.