Image data analysis was performed within the CerebroMatic toolbox which employs a multivariate adaptive regression spline approach as available within the ARESLab toolbox . The data analysis settings were left at the defaults described in . Due to their dominating influence, we used age and gender , , , as well as field strength  and data quality  as predictors. The latter was here described by the cat12 overall image quality measure, a combined parameter with contributions from spatial resolution, image noise, and image inhomogeneity . Processing each iteration required about 12 hours per tissue class on a current PC workstation. The resulting regression parameters can now be used to generate a set of six increasingly crisp tissue maps (see Fig. 2, Fig. 4 for an illustration of the tissue maps, and Fig. 3, Fig. 5 for an illustration of their respective differences), matched to the demographic and technical details of a population under study, with regard to age (in the range of 13–900 months [1–75 years]), gender (male or female), and field strength (1.5 or 3 T). Tissue quality will automatically be set to “best”. These tissue maps can then serve as appropriately matched targets for spatial normalization within the DARTEL/SHOOT framework even for smaller studies, or studies of “unusual” populations.Fig. 2Top row: Illustration of the conventionally generated DARTEL GM templates, from the whole dataset (n=1919). Bottom row: Illustration of synthetically-generated DARTEL GM templates, generated by the CerebroMatic toolbox based on the here-presented regression parameter set (settings: age=330 months, field strength=3 T, gender=male, data quality=best).Fig. 2Fig. 3Top row: difference image of the conventionally generated and the synthetic DARTEL GM templates (cf. Fig. 2), showing voxels where the intensity difference exceeds 5% (in red) or −5% (in blue). Note overall only minor and decreasing differences. Bottom row: boxplot of all voxelwise differences, with the mean voxelwise intensity difference listed at the bottom (in %).Fig. 3Fig. 4Top row: Illustration of the conventionally generated DARTEL WM templates, from the whole dataset (n=1919). Bottom row: Illustration of synthetically-generated DARTEL WM templates, generated by the CerebroMatic toolbox based on the here-presented regression parameter set (settings: age=330 months, field strength=3 T, gender=male, data quality=best).Fig. 4Fig. 5Top row: difference image of the conventionally generated and the synthetic DARTEL WM templates (cf. Fig. 4), showing voxels where the intensity difference exceeds 5% (in red) or −5% (in blue). Note overall only very minor and decreasing differences. Bottom row: boxplot of all voxelwise differences, with the mean voxelwise intensity difference listed at the bottom (in %).Fig. 5