The Cluster Depth Tests: Toward Point-Wise Strong Control of the Family-Wise Error Rate in Massively Univariate Tests with Application to M/EEG

TL;DR

The paper introduces the cluster depth tests, a new method for massively univariate tests in M/EEG data that controls the family-wise error rate at the point level, enabling precise localization of effects.

Contribution

It presents a novel multiple comparison procedure that maintains FWER control while allowing point-wise interpretation, improving upon traditional cluster mass tests.

Findings

Achieves high power in simulations with physiologically plausible effects.

Guarantees FWER control at the point level.

Enables precise temporal localization of effects in EEG data.

Abstract

The cluster mass test has been widely used for massively univariate tests in M/EEG, fMRI and, recently, pupillometry analysis. It is a powerful method for detecting effects while controlling weakly the family-wise error rate (FWER), although its correct interpretation can only be performed at the cluster level without any point-wise conclusion. It implies that the discoveries of a cluster mass test cannot be precisely localized in time or in space. We propose a new multiple comparison procedure, the cluster depth tests, that both controls the FWER while allowing an interpretation at the time point level. The simulation study shows that the cluster depth tests achieve large power and guarantee the FWER even in the presence of physiologically plausible effects. By having an interpretation at the time point/voxel level, the cluster depth tests make it possible to take full advantage of the high temporal resolution of EEG recording to precisely time the appearance of an effect.