MVPA排列方案:组级排列测试

J. Etzel
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引用次数: 26

摘要

排列检验被广泛用于fMRI MVPA(多变量模式分析)研究的显著性检验,但进行检验的精确方式各不相同,而且由于数据集结构复杂、自相关和分层,检验设计非常重要。以前,我们描述了单主题数据集的排列测试,建议采用“数据集明智”方案,其中示例在交叉验证之前重新标记。在这里,我们通过描述分组分析的排列方案来扩展这项工作:具有多个参与者的数据集。组级MVPA通常通过对受试者进行交叉验证或在受试者内部进行交叉验证来执行,每一种交叉验证都需要不同的排列测试策略,如下所示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MVPA Permutation Schemes: Permutation Testing for the Group Level
Permutation tests are widely used for significance testing in fMRI MVPA (multivariate pattern analysis) studies, but the precise way in which the tests are carried out varies, and test design is non-trivial because of complex, auto correlated, and stratified dataset structures. Previously, we described permutation tests for single-subject datasets, recommending adoption of "dataset-wise" schemes, in which examples are relabeled prior to cross-validation. Here, we extend that work by describing permutation schemes for group analyses: datasets with more than one participant. Group-level MVPA is most often performed with either cross-validation on the subjects or within-subjects cross-validation, each of which requires a different strategy for permutation testing, as illustrated here.
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