KSHAP MRI data

MRI images were acquired using a 3-Tesla MAGNETOM Trio 32 channel coil. Whole-brain T1-weighted images were reconstructed from 224 sagittal slices of 1 mm thickness using an MPRAGE sequence with the following parameters: TR = 2.3 s, TE = 2.3 ms, FOV = 256 × 256 mm2, and FA = 9°. The time between social network measurement and MRI acquisition was 16–21 months. Image preprocessing was carried out using tools implemented in Statistical Parametric Mapping software (SPM12; Wellcome Department of Imaging Neuroscience, London, UK) and executed in Matlab (MathWorks, Natick, Massachusetts). We used the New Segmentation algorithm implemented in SPM12 [43]. T1 images were bias-corrected and segmented into five tissue classes based on non-linearly registered tissue probability maps. The East Asian International Consortium for Brain Mapping template was used for local optimization affine regularization. In order to spatially normalize gray matter images into a standard space with enhanced accuracy of inter-subject registration [44,45], we used Diffeomorphic Anatomical Registration Exponentiated Lie algebra (DARTEL). A customized template was created from imported versions of the gray matter tissue images. Then, the deformation field was applied to previously segmented gray matter images to implement non-linear transformation into standardized Montreal Neurological Institute (MNI) space. During these non-linear transformations, the total volume of gray matter was preserved with modulated images. All images were smoothed using an 8-mm full-width at half-maximum Gaussian kernel