标题： 脑扩散方向图的假发现率分析 显示英文标题

标题： False discovery rate analysis of brain diffusion direction maps

摘要： 扩散张量成像（DTI）是一种磁共振成像的新模式，它允许非侵入性地绘制大脑白质的图像。 从DTI测量中得出的一个特定图像是水分子主要扩散方向的图，这些方向是神经纤维方向的代理。 我们考虑一项研究，其中为两组受试者获取了扩散方向图。 分析的目的是找到大脑中对应扩散方向在两组之间存在差异的区域。 这是通过首先使用Watson模型对方向数据进行分析，在每个大脑位置计算差异的检验统计量来实现的。 随后通过控制错误发现率来选择有趣的区域。 通过基于整个大脑检验统计量的经验分布的经验零密度来获得更精确的零分布建模。 此外，通过对检验统计量图进行局部空间平均，显著提高了检验功效。 尽管重点是一项特定的研究和成像技术，但所提出的推断方法可以应用于具有连续潜在空间结构的其他大规模同时假设检验问题。 显示英文摘要

摘要： Diffusion tensor imaging (DTI) is a novel modality of magnetic resonance imaging that allows noninvasive mapping of the brain's white matter. A particular map derived from DTI measurements is a map of water principal diffusion directions, which are proxies for neural fiber directions. We consider a study in which diffusion direction maps were acquired for two groups of subjects. The objective of the analysis is to find regions of the brain in which the corresponding diffusion directions differ between the groups. This is attained by first computing a test statistic for the difference in direction at every brain location using a Watson model for directional data. Interesting locations are subsequently selected with control of the false discovery rate. More accurate modeling of the null distribution is obtained using an empirical null density based on the empirical distribution of the test statistics across the brain. Further, substantial improvements in power are achieved by local spatial averaging of the test statistic map. Although the focus is on one particular study and imaging technology, the proposed inference methods can be applied to other large scale simultaneous hypothesis testing problems with a continuous underlying spatial structure.