Large-scale Automated Synthesis of Functional Neuroimaging Data

描述(申请人提供)：人类神经成像文献的爆炸性增长导致了对正常和异常人类大脑功能的理解的重大进展，但也使得神经成像结果的汇总和合成变得越来越困难。该项目的目标是开发一个用于大规模合成人类功能神经成像研究的自动化软件平台。我们的工作直接建立在现有的软件平台(NeuroSynth)上，涉及的关键扩展和改进集中在(I)聚合、(Ii)编码、(Iii)合成和(Iv)共享功能神经成像数据。在AIM 1，我们将使用计算语言学和生物信息学数据挖掘技术来开发新的算法，从已发表的神经成像文章中自动提取激活焦点和关联元数据。在目标2中，我们将使用主题建模技术，如潜在的狄利克雷分析，并结合现有的认知本体，如认知地图集，以开发自动提取的神经成像数据的结构化表示。在目标3中，我们将通过实施研究小组最近开发的最先进的分层贝叶斯元分析方法来提高现有平台的元分析和分类能力。最后，在目标4中，我们将开发一个最先进的网络界面(：//urosynth.org)，支持在浏览器中实时访问目标1-3中产生的数据、结果和工具。实现这些目标将引入强大的新工具，用于以前所未有的规模组织和合成神经影像文献。这些工具将向任何有互联网连接的人免费和公开提供，使其能够快速有效地应用于广泛的临床和基础研究应用。

DESCRIPTION (provided by applicant): The explosive growth of the human neuroimaging literature has led to major advances in understanding of normal and abnormal human brain function, but has also made aggregation and synthesis of neuroimaging findings increasingly difficult. The goal of this project is to develop an automated software platform for large-scale synthesis of human functional neuroimaging studies. Our work builds directly on an existing software platform (NeuroSynth) and involves key extensions and improvements that focus on (i) aggregation, (ii) coding, (iii) synthesis, and (iv) sharing of functional neuroimaging data. In Aim 1, we will use computational linguistics and bioinformatics data mining techniques to develop new algorithms for automatically extracting activation foci and associated metadata from published neuroimaging articles. In Aim 2, we will use topic-modeling techniques such as Latent Dirichlet Analysis in combination with existing cognitive ontologies such as the Cognitive Atlas to develop structured representations of automatically extracted neuroimaging data. In Aim 3, we will improve the meta-analysis and classification capacities of our existing platform by implementing a state-of- the-art hierarchical Bayesian meta-analysis method recently developed by the research team. Finally, in Aim 4, we will develop a state-of-the-art web interface (://neurosynth.org) that supports real-time, in-browser access to the data, results, and tools produced in Aims 1 - 3. Realizing these objectives will introduce powerful new tools for organizing and synthesizing the neuroimaging literature on an unprecedented scale. These tools will be freely and publicly available to anyone with an internet connection, enabling rapid and efficient application to a broad range of clinical and basic research applications.