NeuroQuery, comprehensive meta-analysis of human brain mapping
NeuroQuery, comprehensive meta-analysis of human brain mapping
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DOI：
10.7554/elife.53385
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发表时间：
2020-03-04
期刊：
影响因子：
7.7
通讯作者：
Varoquaux, Gael
中科院分区：
文献类型：
--
作者：
Dockes, Jerome;Poldrack, Russell A.;Varoquaux, Gael
要对大脑组织有一个全面的认识，需要收集有关截然不同的心理过程和机制的证据。人类神经科学概念和术语的多样性对跨科学文献关联脑成像结果提出了根本性挑战。现有的荟萃分析方法对与特定概念相关的出版物集进行统计测试。因此，大规模荟萃分析仅处理频繁出现的单个术语。我们提出了一种新的范式，侧重于预测而不是推理。我们的多变量模型可以根据描述实验、认知过程或疾病的文本来预测神经学观察的空间分布。这种方法可以处理任意长度的文本和对于标准荟萃分析来说太罕见的术语。我们捕获了 13,459 份神经影像出版物中 7547 个神经科学术语的关系和神经相关性。由此产生的元分析工具，neuroquery.org，可以根据已发表的大脑研究结果的综合观点来生成假设和数据分析先验。
Reaching a global view of brain organization requires assembling evidence on widely different mental processes and mechanisms. The variety of human neuroscience concepts and terminology poses a fundamental challenge to relating brain imaging results across the scientific literature. Existing meta-analysis methods perform statistical tests on sets of publications associated with a particular concept. Thus, large-scale meta-analyses only tackle single terms that occur frequently. We propose a new paradigm, focusing on prediction rather than inference. Our multivariate model predicts the spatial distribution of neurological observations, given text describing an experiment, cognitive process, or disease. This approach handles text of arbitrary length and terms that are too rare for standard meta-analysis. We capture the relationships and neural correlates of 7547 neuroscience terms across 13 459 neuroimaging publications. The resulting meta-analytic tool, neuroquery.org, can ground hypothesis generation and data-analysis priors on a comprehensive view of published findings on the brain.