The difference in source localization of cortical oscillations between groups in each frequency band was assessed by voxel-by-voxel independent sample F-ratio-tests, based on eLORETA log-transformed current density power. In the resulting statistical three-dimensional images, cortical voxels showing significant differences were identified by a nonparametric approach (statistical nonparametric mapping or SnPM) via randomizations. This randomization strategy [55] determined the critical probability threshold values for the actually observed t-values with correction for multiple comparisons across all voxels and all frequencies. A total of 5000 permutations were used to determine the significance for each randomization test. The use of statistical nonparametric maps applied to LORETA images has been validated in several studies [56]–[58]. Although these statistical tests focused mainly on signal strength for single voxels (referred to as ‘single voxel statistics’), a second nonparametric analysis assessed the significance of activity based on its spatial extent, obtaining clusters of supra-threshold voxels (referred to as “cluster statistics”) [59]. The LORETA method does not need any “distributional assumptions” yielding an adjusted t-critical value that is effective for controlling Type I error [60].
