Interdisciplinary MRI/MRS Laboratory, Department of Electrical Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 106, Taiwan.
Neuroinformatics. 2011 Mar;9(1):21-38. doi: 10.1007/s12021-010-9083-9.
Associating fMRI image datasets with the available literature is crucial for the analysis and interpretation of fMRI data. Here, we present a human brain function mapping knowledge-base system (BrainKnowledge) that associates fMRI data analysis and literature search functions. BrainKnowledge not only contains indexed literature, but also provides the ability to compare experimental data with those derived from the literature. BrainKnowledge provides three major functions: (1) to search for brain activation models by selecting a particular brain function; (2) to query functions by brain structure; (3) to compare the fMRI data with data extracted from the literature. All these functions are based on our literature extraction and mining module developed earlier (Hsiao, Chen, Chen. Journal of Biomedical Informatics 42, 912-922, 2009), which automatically downloads and extracts information from a vast amount of fMRI literature and generates co-occurrence models and brain association patterns to illustrate the relevance of brain structures and functions. BrainKnowledge currently provides three co-occurrence models: (1) a structure-to-function co-occurrence model; (2) a function-to-structure co-occurrence model; and (3) a brain structure co-occurrence model. Each model has been generated from over 15,000 extracted Medline abstracts. In this study, we illustrate the capabilities of BrainKnowledge and provide an application example with the studies of affect. BrainKnowledge, which combines fMRI experimental results with Medline abstracts, may be of great assistance to scientists not only by freeing up resources and valuable time, but also by providing a powerful tool that collects and organizes over ten thousand abstracts into readily usable and relevant sources of information for researchers.
将 fMRI 图像数据集与现有文献相关联对于 fMRI 数据的分析和解释至关重要。在这里，我们提出了一个人脑功能映射知识库系统（BrainKnowledge），它将 fMRI 数据分析和文献搜索功能关联起来。BrainKnowledge 不仅包含索引文献，还提供了将实验数据与文献中得出的数据进行比较的功能。BrainKnowledge 提供了三个主要功能：（1）通过选择特定的脑功能来搜索脑激活模型；（2）通过脑结构查询功能；（3）将 fMRI 数据与从文献中提取的数据进行比较。所有这些功能都是基于我们之前开发的文献提取和挖掘模块（Hsiao、Chen、Chen，《生物医学信息学期刊》42，912-922，2009 年），该模块自动从大量 fMRI 文献中下载和提取信息，并生成共现模型和脑关联模式，以说明脑结构和功能的相关性。BrainKnowledge 目前提供了三种共现模型：（1）结构-功能共现模型；（2）功能-结构共现模型；（3）脑结构共现模型。每个模型都是从超过 15000 篇提取的 Medline 摘要中生成的。在这项研究中，我们展示了 BrainKnowledge 的功能，并提供了一个情感研究的应用示例。BrainKnowledge 将 fMRI 实验结果与 Medline 摘要相结合，不仅可以为科学家节省资源和宝贵的时间，还可以为他们提供一个强大的工具，将超过一万篇摘要收集和组织成易于使用的、相关的信息源，为研究人员提供帮助。
