FreeSurfer

Cortical reconstruction and volumetric segmentation for all 134 images were performed with the FreeSurfer software suite, version 6.0.0.⁷ We selected the T1 image with the least motion artifact (in case there were several attempts due to visible motion during scan) and then applied the “recon-all” processing stream with default parameters. It begins with transformation to Talaraich space, intensity inhomogeneity correction, bias field correction (Sled et al., 1998), and skull-stripping (Ségonne et al., 2004). Thereafter, WM is separated from GM and other tissues and the volume within the created WM–GM boundary is filled. After this, the surface is tessellated and smoothed. After these preprocessing steps are completed, the surface is inflated (Fischl et al., 1999a) and registered to a spherical atlas. This method adapts to the folding pattern of each individual brain, utilizing consistent folding patterns such as the central sulcus and the sylvian fissure as landmarks, allowing for high localization accuracy (Fischl et al., 1999b). FreeSurfer uses probabilistic approach based on Markov random fields for automated labeling of brain regions. Cortical thickness is calculated as the average distance between the WM–GM boundary and the pial surface on the tessellated surface (Fischl and Dale, 2000). The cortical thickness measurement technique has been validated against post-mortem histological (Rosas et al., 2002) and manual measurements (Kuperberg et al., 2003; Salat, 2004).