Valid Double-Dipping via Permutation-Based Closed Testing

Abstract

Functional Magnetic Resonance Imaging (fMRI) cluster analysis is widely popular for finding neural activation associated with some stimulus. However, it suffers from the spatial specificity paradox, and making follow-up inference inside clusters is not allowed. Valid double-dipping can be performed by closed testing, which determines lower confidence bounds for the number of active voxels, simultaneously over all regions. Moreover, a permutation framework adapts to the unknown

Publication
Preface XIX 1 Plenary Sessions, 776
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Angela Andreella
Assistant Professor at Ca’ Foscari University of Venice

My research interests include Multiple Testing problem and Procrustes technique, generally statistical methods in the Neuroscience field.