Increasing statistical power in functional MRI through permutation and multivariate statistics

Slotnick (2026) provides a large number of simulations to demonstrate that statistical power in fMRI can be improved by including the sample size N when calculating an appropriate cluster extent threshold for thresholding statistical maps. I argue that the problems acknowledged by Slotnick can instead be solved using threshold free cluster enhancement (TFCE) and a permutation test, which together apply a large number of cluster forming thresholds and implicitly model the sample size as well as the spatial autocorrelation. Furthermore, I briefly mention some other approaches for increasing statistical power in fMRI.