Magnetom connectome 3 tesla scanner

The HCP data was collected at Washington University, St. Louis, using a customized Siemens Magnetom Connectome 3 Tesla scanner with a 100 mT/m maximum gradient strength and a 32-channel head coil. Details on the scanner, image acquisition, and reconstruction are provided elsewhere (Ugurbil et al., 2013 (link)) and found online at (https://www.humanconnectome.org/study/hcp-young-adult/document/1200-subjects-data-release). Diffusion data was collected using a single-shot, single refocusing spin-echo, echo-planar imaging sequence with 1.25 mm isotropic spatial resolution (TE/TR = 89.5/5520 ms, FOV = 210 × 180 mm). Three gradient tables of 90 diffusion-weighted directions and 6 b = 0 images each, were collected with right-to-left and left-to-right phase encoding polarities for each of the three diffusion weightings (b = 1000, 2000, and 3000 s/mm²). The diffusion data were then processed using the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) pipeline for structural and diffusion tensor imaging, including skeletonized voxel-wise FA values (Jahanshad et al., 2013 (link)).

Diffusion imaging data was collected at Washington University, St. Louis, using a customized Siemens Magnetom Connectome 3 Tesla scanner with a 100 mT/m maximum gradient strength and a 32 channel head coil. Details on the scanner, image acquisition and reconstruction reported elsewhere (Ugurbil et al., 2013 (link)) and are available online(https://www.humanconnectome.org/documentation/S500/HCP_S500_Release_Reference_Manual.pdf). Diffusion data were collected using a single-shot, single refocusing spin-echo, echo-planar imaging sequence with 1.25 mm isotropic spatial resolution (TE/TR=89.5/5520 ms, FOV=210×180 mm). Three gradient tables of 90 diffusion-weighted directions, and six b=0 images each, were collected with right-to-left and left-to-right phase encoding polarities for each of the three diffusion weightings (b=1000, 2000, and 3000 s/mm²). The total imaging time for collection of diffusion data was approximately one hour. Diffusion data were preprocessed using the HCP Diffusion pipeline (Glasser et al., 2013 (link); Sotiropoulos et al., 2013 (link)) that included: normalization of b0 image intensity across runs; correction for EPI susceptibility and eddy-current-induced distortions, gradient-nonlinearities, subject motion and application of a brain mask. FA maps were obtained by fitting diffusion tensor model using FSL-FDT toolkit (Behrens et al., 2003 (link)).