Anatomical brain templates are commonly used as references in neurological MRI studies, for bringing data into a common space for group level statistics and coordinate reporting. Having a group representative template increases the accuracy of alignment, improves statistics and decreases distortions (as well as potential biases) in final coordinate reports. Given the inherent variability in brain morphology across age and geography, it is important to have templates that are as representative as possible for both age and population. In this study, we developed and validated a new set of T1w Indian brain templates (IBT) from a large number of subjects (total n=466) across different Indian states and acquired at multiple 3T MRI sites. A new tool in AFNI, make_template_dask.py, which uses the Dask python parallelization library, was created to efficiently make a template from a group of subjects. A total of five age-specific categories of IBTs [ages 6-11 yrs (C1), 12-18 yrs (C2), 19-25 yrs (C3), 26-40 yrs (C4), and 41-60 yrs (C5)], as well as maximum probability map (MPM) atlases for each template were generated; for each age group's template-atlas pair, there is both a population-average and a typical version. Validation experiments on an independent Indian structural and functional MRI dataset show the appropriateness of IBTs for spatial normalization of Indian brains. The results indicate significant structural differences when comparing the IBTs and MNI template, with these differences being maximal along the Anterior-Posterior and Inferior-Superior axes, but minimal Left-Right. For each age group, the MPM brain atlases provide reasonably good representation of the native-space volumes in the IBT space, except in a few regions with high inter-subject variability as indicated by high mean deformation value. These findings provide evidence to support the use of age and population-specific templates in human brain mapping studies. These templates, with corresponding atlases and tools, are publicly available on the NIMHANS and AFNI websites.

中文翻译：

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一系列五种特定于人群的印度脑模板和地图集，年龄在6至60岁之间

大脑解剖模板通常在神经MRI研究中用作参考，以将数据带入一个公共空间进行组级统计和协调报告。具有组代表模板可提高对齐精度，改善统计数据并减少最终坐标报告中的变形（以及潜在的偏差）。考虑到跨年龄和地域的大脑形态固有的可变性，重要的是要有对年龄和人群都具有代表性的模板。在这项研究中，我们开发并验证了一组来自印度不同州的大量受试者（总计n = 466）并在多个3T MRI站点获得的一组T1w印度脑模板（IBT）。AFNI中的新工具make_template_dask.py使用了Dask python并行化库，创建是为了有效地从一组主题中制作模板。IBT共有五种特定年龄段的类别：[6-11岁（C1），12-18岁（C2），19-25岁（C3），26-40岁（C4）和41-60岁（ C5）]，以及每个模板的最大概率图（MPM）地图集已生成；对于每个年龄组的模板图集对，既有人口平均值，又有典型版本。在独立的印度结构和功能MRI数据集上进行的验证实验表明，IBT适用于印度大脑的空间正常化。结果表明，在比较IBT和MNI模板时，存在明显的结构差异，这些差异在前后轴和上下轴上最大，而在左右方向上最小。对于每个年龄段，MPM脑图集提供了IBT空间中自然空间体积的合理良好表示，除了少数具有较高平均变形值指示的受试者间可变性的区域。这些发现提供了证据支持在人脑测绘研究中使用年龄和特定人群模板。这些模板以及相应的图集和工具可在NIMHANS和AFNI网站上公开获得。