Yale University School of Medicine, Department of Psychiatry, USA.
University of Pennsylvania Perelman School of Medicine, Department of Biostatistics, Epidemiology, and Informatics, USA.
Neuroimage. 2018 Sep;178:540-551. doi: 10.1016/j.neuroimage.2018.05.070. Epub 2018 Jun 1.
A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data.
在许多神经影像学研究中，一个关键问题是对脑图谱进行比较。然而，对于如何检验专注于两个或多个脑图谱之间的重叠或空间对应关系的假设，目前仍不清楚。这个“对应问题”影响了例如基于任务的功能激活模式、静息态网络或模块与神经解剖学标志物之间的比较的解释。迄今为止，这个问题在方法学方法和统计严谨性方面存在显著的可变性。在本文中，我们使用空间置换框架来解决对应问题，通过对皮质表面的球体表示进行随机旋转来生成重叠的零模型，我们还为这种方法提供了理论统计学基础。我们使用这种方法来推导出与功能神经解剖基质相关的认知功能的聚类。此外，使用公开可用的数据，我们正式证明了基于任务的功能活动图、静息态 fMRI 网络和基于脑回的解剖标志物之间的对应关系。我们提供了一个开源代码来实现用于基于表面的皮质分析的两个常用工具（https://www.github.com/spin-test）中的方法。这种空间置换方法是对广泛使用的皮质图谱比较方法的一个有益的改进，从而为整合各种神经影像学数据开辟了新的可能性。
