MulipleComparisons correction refers to the need to correct a significance level for the number of hypothesis tests performed. In brain mapping, the number of hypothesis tests is typically associated with the number of voxels or surface vertices and is therefore massive. Methods for MultipleComparisons correction include:

[ Bonferroni Correction]

[ False Discovery Rate]

[ Random Field Theory]

[ Permutation testing]