静息状态功能磁共振成像
神经影像学
计算机科学
功能磁共振成像
预处理器
人工智能
机器学习
心理学
神经科学
作者
Pierre Bellec,Carlton Chu,François Chouinard-Decorte,Yassine Benhajali,Daniel S. Margulies,R. Cameron Craddock
出处
期刊:NeuroImage
[Elsevier BV]
日期:2016-07-16
卷期号:144: 275-286
被引量:281
标识
DOI:10.1016/j.neuroimage.2016.06.034
摘要
In 2011, the “ADHD-200 Global Competition” was held with the aim of identifying biomarkers of attention-deficit/hyperactivity disorder from resting-state functional magnetic resonance imaging (rs-fMRI) and structural MRI (s-MRI) data collected on 973 individuals. Statisticians and computer scientists were potentially the most qualified for the machine learning aspect of the competition, but generally lacked the specialized skills to implement the necessary steps of data preparation for rs-fMRI. Realizing this barrier to entry, the Neuro Bureau prospectively collaborated with all competitors by preprocessing the data and sharing these results at the Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) (http://www.nitrc.org/frs/?group_id=383). This “ADHD-200 Preprocessed” release included multiple analytical pipelines to cater to different philosophies of data analysis. The processed derivatives included denoised and registered 4D fMRI volumes, regional time series extracted from brain parcellations, maps of 10 intrinsic connectivity networks, fractional amplitude of low frequency fluctuation, and regional homogeneity, along with grey matter density maps. The data was used by several teams who competed in the ADHD-200 Global Competition, including the winning entry by a group of biostaticians. To the best of our knowledge, the ADHD-200 Preprocessed release was the first large public resource of preprocessed resting-state fMRI and structural MRI data, and remains to this day the only resource featuring a battery of alternative processing paths.
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