病变-症状图谱研究可以深入了解大脑的哪些区域涉及认知的不同方面。这通常是通过对自然发生的脑损伤或病变（例如中风或脑肿瘤）的患者进行行为测试来完成的。这会产生高维观察数据，其中病变状态（存在/不存在）分布不均匀，一些体素在很少（或没有）受试者中具有病变。在这种情况下，大量单变量假设检验具有严重的功效异质性，其中许多检验事先已知几乎没有功效。多种测试方法的最新进展使研究人员能够根据辅助信息（例如，功率异质性信息）权衡假设。在本文中，我们建议使用 p 值加权进行基于体素的病变症状映射研究。使用病变状态和空间信息的分布创建权重，以通过一些常见方法估计每个假设检验的不同非零先验概率。我们提供了一个单调最小权重标准，它需要最小的先验功率信息。我们的方法是根据相关模拟数据和失语症研究来证明的，该研究调查了大脑的哪些区域与中风幸存者语言障碍的严重程度相关。结果表明，所提出的方法具有鲁棒的误差控制并且可以提高功率。此外，我们还展示了如何使用权重来识别由于缺乏功效而无法得出结论的区域。© 2024 作者。 Wiley‐VCH GmbH 出版的《生物识别杂志》。

Lesion-symptom mapping studies provide insight into what areas of the brain are involved in different aspects of cognition. This is commonly done via behavioral testing in patients with a naturally occurring brain injury or lesions (e.g., strokes or brain tumors). This results in high-dimensional observational data where lesion status (present/absent) is nonuniformly distributed, with some voxels having lesions in very few (or no) subjects. In this situation, mass univariate hypothesis tests have severe power heterogeneity where many tests are known a priori to have little to no power. Recent advancements in multiple testing methodologies allow researchers to weigh hypotheses according to side information (e.g., information on power heterogeneity). In this paper, we propose the use of p-value weighting for voxel-based lesion-symptom mapping studies. The weights are created using the distribution of lesion status and spatial information to estimate different non-null prior probabilities for each hypothesis test through some common approaches. We provide a monotone minimum weight criterion, which requires minimum a priori power information. Our methods are demonstrated on dependent simulated data and an aphasia study investigating which regions of the brain are associated with the severity of language impairment among stroke survivors. The results demonstrate that the proposed methods have robust error control and can increase power. Further, we showcase how weights can be used to identify regions that are inconclusive due to lack of power.© 2024 The Author(s). Biometrical Journal published by Wiley‐VCH GmbH.