Cluster failure or power failure? Evaluating sensitivity in cluster-level inference.

ABSTRACT: Pioneering work in human neuroscience has relied on the ability to map brain function using task-based fMRI, but the empirical validity of these inferential methods is still being characterized. A recent landmark study by Eklund and colleagues showed that popular multiple comparison corrections based on cluster extent suffer from unexpectedly low specificity (i.e., high false positive rate). Yet that study's focus on specificity, while important, is incomplete. The validity of a method depends also on its sensitivity (i.e., true positive rate or power), yet the sensitivity of cluster correction remains poorly understood. Here, we assessed the sensitivity of gold-standard nonparametric cluster correction by resampling real data from five tasks in the Human Connectome Project and comparing r

SUBMITTER: Noble S 

PROVIDER: S-EPMC8061745 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature