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Collegiate athlete brain data for white matter mapping and network neuroscience
Scientific Data ( IF 5.8 ) Pub Date : 2021-02-11 , DOI: 10.1038/s41597-021-00823-z
Bradley Caron 1, 2 , Ricardo Stuck 1 , Brent McPherson 3 , Daniel Bullock 1, 3 , Lindsey Kitchell 3, 4, 5 , Joshua Faskowitz 1, 3 , Derek Kellar 3 , Hu Cheng 1, 3 , Sharlene Newman 1, 3, 6 , Nicholas Port 1, 2, 3, 4 , Franco Pestilli 1, 2, 3, 4, 7, 8, 9
Affiliation  

We describe a dataset of processed data with associated reproducible preprocessing pipeline collected from two collegiate athlete groups and one non-athlete group. The dataset shares minimally processed diffusion-weighted magnetic resonance imaging (dMRI) data, three models of the diffusion signal in the voxel, full-brain tractograms, segmentation of the major white matter tracts as well as structural connectivity matrices. There is currently a paucity of similar datasets openly shared. Furthermore, major challenges are associated with collecting this type of data. The data and derivatives shared here can be used as a reference to study the effects of long-term exposure to collegiate athletics, such as the effects of repetitive head impacts. We use advanced anatomical and dMRI data processing methods publicly available as reproducible web services at brainlife.io.



中文翻译:


用于白质绘图和网络神经科学的大学运动员大脑数据



我们描述了一个处理数据的数据集,以及从两个大学运动员组和一个非运动员组收集的相关可重复预处理管道。该数据集共享经过最低限度处理的扩散加权磁共振成像 (dMRI) 数据、体素中扩散信号的三种模型、全脑束图、主要白质束的分割以及结构连接矩阵。目前公开共享的类似数据集很少。此外,收集此类数据还面临着重大挑战。这里分享的数据和导数可以作为研究长期接触大学体育运动的影响的参考,例如重复头部撞击的影响。我们使用先进的解剖和 dMRI 数据处理方法,这些方法在 Brainlife.io 上作为可重复的网络服务公开提供。

更新日期:2021-02-11
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