Computational protocol: Linked alterations in gray and white matter morphology in adults with high-functioning autism spectrum disorder: A multimodal brain imaging study

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Protocol publication

[…] All T1-weighted images were preprocessed using FSL-VBM (; http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLVBM/), an optimized VBM protocol () carried out with FSL tools. First, each T1-weighted image was brain-extracted using the Brain Extraction Tool (BET), and then tissue-type segmentation was performed using FAST (). Next, the resulting images were aligned to the Montreal Neurological Institute (MNI) 152 standard space. The aligned images were averaged to create a study-specific template, to which native GM images were then non-linearly registered using FNIRT. The registered partial volume images were then modulated to correct for local expansion or contraction by dividing the Jacobian of the warp field. Finally, the modulated segmented images were spatially smoothed using an isotropic Gaussian kernel with a sigma of 4 mm (FWHM = 9.4 mm).As was the case with TBSS analysis, a permutation-based nonparametric testing with 5000 permutations was performed on the smoothed, modulated, and segmented GM volumes for between-group comparison. The result was corrected for multiple comparisons using TFCE (). Of note, age and total brain volume (TBV) (described below) were included as nuisance covariates. If any significant between-group differences were detected, associations between GM volume and autism scales (AQ and ADOS scores) were investigated for voxels showing significant alterations, while including age as a controlling variable.In addition, for each participant, brain tissue volumes normalized for head size were estimated with SIENAX (). Briefly, brain and skull images were first extracted from the original T1-weighted images; then, brain images were affine-registered to the MNI 152 standard space (; ). Finally, tissue-type segmentation with partial volume estimation was carried out in order to calculate the total volume of brain tissue (). [...] It turned out that two of the 90 composite components showed significant between-group differences (see ). In one of the components (component #13), we observed widespread GM alterations involving multiple brain regions critically implicated in the pathophysiology of ASD, such as the bilateral fusiform gyri, bilateral orbitofrontal cortices, and bilateral motor cortices. To elaborate the relationship between the spatial patterns in the GM and WM maps of that component, we delineated anatomical connections between some of the major clusters in the GM map using probabilistic tractography (). Among the many pairs of brain regions identified in the GM map of component #13, we reasoned that clear relationships with WM maps could be shown at least for the following three connections by tractography: (1) connection between the right fusiform gyrus and right anterior temporal pole, because these regions have been implicated in face perception () and are anatomically connected via the right inferior longitudinal fasciculus; (2) connection between the right anterior temporal pole and right orbitofrontal cortex, because these regions have been implicated in the integration of emotion with cognitive behavior () and are connected via the right uncinate fasciculus; and (3) connection between the left putamen and left pre- and post-central gyri, because these regions are involved in motor control () and are connected via the left corticospinal tract. Note that these three functions are significantly impaired in ASD and that these tracts have been reliably reconstructed in previous DTI tractography studies (e.g., ). Because the original GM map obtained by the linked ICA included large voxel clusters extending into multiple brain regions, the map was thresholded to yield distinct clusters for seed and target regions with moderate sizes (z < −6.0 for the right anterior temporal pole; z < −2.3 for the left putamen; z > 2.3 for the right orbitofrontal cortex; z > 6.0 for the right fusiform gyrus and left pre- and post-central gyri). The MNI coordinates and the number of voxels of seed and target regions are listed in .For each participant, probabilistic tractography was performed from all voxels in each seed mask using probtrackx2 implemented in FSL (). In order to discard streamlines that crossed to the contralateral hemisphere, an exclusion mask was generated on the standard space (MNI coordinate: x = 0). For each participant, a seed, target, and exclusion masks defined on the standard space were then transformed into a native DTI space. For each voxel within the seed mask, 5000 streamlines were sampled with a step length of 0.5 mm and a curvature threshold of 0.2. The streamlines were terminated when they reached to the target mask. Streamlines that did not pass or reach to the target mask within 2000 steps were discarded. By adding the exclusion mask, streamlines that crossed to the contralateral hemisphere were also discarded.To visualize the spatial distribution of the connection between each pair of seed and target regions, we created a tract representing the spatial overlap of the streamlines across all participants. For each participant, a tract obtained by probabilistic tractography was divided by the total number of successful streamlines and binarized by setting voxels having greater than 0.01 to 1 and the remaining voxels to 0. The binarized tract was transformed from a native DTI space into the standard space. The binarized tracts in the standard space were then summed across all participants and divided by the total number of participants (n = 92). We further binarized the normalized tract by setting voxels having greater than 0.1 to 1 and the remaining voxels to 0, to reconstruct a representative tract. Finally, we examined the spatial overlap between each reconstructed WM tract and the voxels in the FA map of component #13 by overlaying the two in a single figure. […]

Pipeline specifications

Software tools BET, Probtrackx
Applications Magnetic resonance imaging, Diffusion magnetic resonance imaging analysis
Organisms Homo sapiens
Diseases Brain Diseases