Diffusion data is acquired with two b-values (b=1000 and 2000 s/mm2) at 2mm spatial resolution, with multiband acceleration factor of 3 (three slices are acquired simultaneously instead of just one). For each diffusion-weighted shell, 50 distinct diffusion-encoding directions were acquired (covering 100 distinct directions over the two b-values). The diffusion preparation is a standard (“monopolar”) Stejskal-Tanner pulse sequence. This enables higher SNR due to a shorter echo time (TE=92ms) than a twice-refocused (“bipolar”) sequence at the expense of stronger eddy current distortions, which are removed using the Eddy tool67 (which also corrects for static field distortion and motion68 (link)).
Both diffusion tensor and NODDI models are fit voxel-wise, and IDPs of the various model outputs are extracted from a set of white matter tracts. Tensor fits utilize the b=1000 s/mm2 data, producing maps including fractional anisotropy, tensor mode and mean diffusivity. The NODDI16 (link) model is fit using the AMICO (Accelerated Microstructure Imaging via Convex Optimization) tool52 (link), with outputs including intra-cellular volume fraction (which is often interpreted to reflect neurite density) and orientation dispersion (a measure of within-voxel disorganization). For tractography, a parametric approach is first used to estimate fibre orientations. The generalised ball & stick model is fit to the multi-shell data, estimating up to 3 crossing fibre orientations per voxel.17 (link), 69 (link) Tractography is then performed in a probabilistic manner to estimate white matter pathways using the voxel-wise orientations.
Cross-subject alignment of white matter pathways is critical for extracting meaningful IDPs; here, two complementary approaches are used. The first used tract-based spatial statistics (TBSS18 (link), 70 (link)), in which a standard-space white matter skeleton is mapped to each subject using a high-dimensional warp, after which ROIs are defined as the intersection of the skeleton with standard-space masks for 48 tracts71 (link) (see the “JHU ICBM-DTI-81 white-matter labels atlas” described atfsl.fmrib.ox.ac.uk/fsl/fslwiki/Atlases for definitions of the tract regions and names). The second approach utilizes subject-specific probabilistic diffusion tractography run using standard-space protocols to identify identify 27 tracts18 (link); in this case, the output IDPs are weighted by the tractography output to emphasize values in regions that can most confidently be attributed to the tract of interest. Currently, no structural connectivity estimates from the diffusion tractography are provided as IDPs, but the probabilistic maps are available and future work will generate measures similar to those provided for resting-state fMRI.
Both diffusion tensor and NODDI models are fit voxel-wise, and IDPs of the various model outputs are extracted from a set of white matter tracts. Tensor fits utilize the b=1000 s/mm2 data, producing maps including fractional anisotropy, tensor mode and mean diffusivity. The NODDI16 (link) model is fit using the AMICO (Accelerated Microstructure Imaging via Convex Optimization) tool52 (link), with outputs including intra-cellular volume fraction (which is often interpreted to reflect neurite density) and orientation dispersion (a measure of within-voxel disorganization). For tractography, a parametric approach is first used to estimate fibre orientations. The generalised ball & stick model is fit to the multi-shell data, estimating up to 3 crossing fibre orientations per voxel.17 (link), 69 (link) Tractography is then performed in a probabilistic manner to estimate white matter pathways using the voxel-wise orientations.
Cross-subject alignment of white matter pathways is critical for extracting meaningful IDPs; here, two complementary approaches are used. The first used tract-based spatial statistics (TBSS18 (link), 70 (link)), in which a standard-space white matter skeleton is mapped to each subject using a high-dimensional warp, after which ROIs are defined as the intersection of the skeleton with standard-space masks for 48 tracts71 (link) (see the “JHU ICBM-DTI-81 white-matter labels atlas” described at
