Johns Hopkins University, Baltimore, MD, 12218, USA.
University of Texas at Austin, Austin, USA.
Sci Data. 2021 Mar 8;8(1):78. doi: 10.1038/s41597-021-00849-3.
Using brain atlases to localize regions of interest is a requirement for making neuroscientifically valid statistical inferences. These atlases, represented in volumetric or surface coordinate spaces, can describe brain topology from a variety of perspectives. Although many human brain atlases have circulated the field over the past fifty years, limited effort has been devoted to their standardization. Standardization can facilitate consistency and transparency with respect to orientation, resolution, labeling scheme, file storage format, and coordinate space designation. Our group has worked to consolidate an extensive selection of popular human brain atlases into a single, curated, open-source library, where they are stored following a standardized protocol with accompanying metadata, which can serve as the basis for future atlases. The repository containing the atlases, the specification, as well as relevant transformation functions is available in the neuroparc OSF registered repository or https://github.com/neurodata/neuroparc .
使用大脑图谱来定位感兴趣的区域是进行神经科学上有效统计推断的要求。这些图谱以体积或表面坐标空间表示,可以从多种角度描述大脑拓扑结构。尽管在过去的五十年中,已经有许多人类大脑图谱在该领域流传,但对它们的标准化却没有给予足够的重视。标准化可以促进方向、分辨率、标签方案、文件存储格式和坐标空间指定方面的一致性和透明度。我们的团队致力于将广泛的流行人类大脑图谱整合到一个单一的、经过精心整理的开源库中,按照标准化协议进行存储,并附有元数据,这些数据可以作为未来图谱的基础。包含图谱、规范以及相关转换函数的存储库可在 neuroparc OSF 注册存储库中找到,也可以在 https://github.com/neurodata/neuroparc 找到。