Influence of sample size and analytic approach on stability and interpretation of brain-behavior correlations in task-related fMRI data.
Influence of sample size and analytic approach on stability and interpretation of brain-behavior correlations in task-related fMRI data.
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DOI：
10.1002/hbm.25217
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发表时间：
2021-01
影响因子：
4.8
通讯作者：
Kennedy KM
中科院分区：
文献类型：
--
作者：
Grady CL;Rieck JR;Nichol D;Rodrigue KM;Kennedy KM
由于样本量小，统计能力有限是功能磁共振成像研究中的一个问题。迄今为止，大多数研究都是研究样本量对任务相关激活的影响，很少关注样本量对脑行为相关性的影响，特别是在实际的实验fMRI数据中。我们使用两个大型数据集（一个工作记忆任务，N = 171，一个关系处理任务，N = 865）和单变量和多变量体素相关性方法来解决这个问题。我们创建了不同大小的子样本，并计算了每个体素上与任务相关的活动与任务性能之间的相关性。在这两个数据集中，随着样本量的增加，大脑-行为相关性的程度降低，而空间地图的相似性增加。多变量技术确定了更广泛的相关区域和更多的空间地图相似性，这表明在大脑行为相关性的稳定性方面，多变量方法将比单变量方法提供一致的优势。此外，多变量分析表明，大约80或更多参与者的样本量将需要在这些数据集中稳定地估计相关程度。重要的是，在任何给定的实验中，许多其他因素可能会影响评估这种相关性的样本量的选择，包括感兴趣的认知任务和每个参与者收集的数据量。我们的研究结果在两个独立的数据集中提供了新的实验证据，证明在20-30名参与者的fMRI研究中常用的样本量不太可能足以获得可重复的脑-行为相关性，无论采用何种分析方法。由于样本量小，统计能力有限是功能磁共振成像研究中的一个问题。迄今为止，大多数研究都是研究样本量对任务相关激活的影响，很少关注样本量对脑行为相关性的影响，特别是在实际的实验fMRI数据中。我们的研究结果在两个独立的数据集中提供了新的实验证据，证明在20-30名参与者的fMRI研究中通常使用的样本量非常不可能足以获得可重复的脑-行为相关性，无论使用单变量还是多变量方法。
Limited statistical power due to small sample sizes is a problem in fMRI research. Most of the work to date has examined the impact of sample size on task‐related activation, with less attention paid to the influence of sample size on brain‐behavior correlations, especially in actual experimental fMRI data. We addressed this issue using two large data sets (a working memory task, N = 171, and a relational processing task, N = 865) and both univariate and multivariate approaches to voxel‐wise correlations. We created subsamples of different sizes and calculated correlations between task‐related activity at each voxel and task performance. Across both data sets the magnitude of the brain‐behavior correlations decreased and similarity across spatial maps increased with larger sample sizes. The multivariate technique identified more extensive correlated areas and more similarity across spatial maps, suggesting that a multivariate approach would provide a consistent advantage over univariate approaches in the stability of brain‐behavior correlations. In addition, the multivariate analyses showed that a sample size of roughly 80 or more participants would be needed for stable estimates of correlation magnitude in these data sets. Importantly, a number of additional factors would likely influence the choice of sample size for assessing such correlations in any given experiment, including the cognitive task of interest and the amount of data collected per participant. Our results provide novel experimental evidence in two independent data sets that the sample size commonly used in fMRI studies of 20–30 participants is very unlikely to be sufficient for obtaining reproducible brain‐behavior correlations, regardless of analytic approach. Limited statistical power due to small sample sizes is a problem in fMRI research. Most of the work to date has examined the impact of sample size on task‐related activation, with less attention paid to the influence of sample size on brain‐behavior correlations, especially in actual experimental fMRI data. Our results provide novel experimental evidence in two independent data sets that the sample size commonly used in fMRI studies of 20–30 participants is very unlikely to be sufficient for obtaining reproducible brain‐behavior correlations, regardless of whether a univariate or multivariate approach is used.
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