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6 results for “cortical surfaces”
Voxel-level summary statistics of hippocampus shape, white matter microstructure, and cortical surface curvature in UK Biobank (n=33,324)
<p>This deposit hosts GWAS summary statistics of hippocampus shape (n=33,324), white matter microstructure (n=33,324), and cortical surface curvature (n=15,752) using UKB unrelated white subjects. The data was generated by using the highly efficient imaging genetics (<a href="https://github.com/Zhiwen-Owen-Jiang/heig">HEIG v1.1.0</a>) framework where only the triplets - summary statistics of low-dimensional representations (LDRs), the functional bases, and the variance-covariance matrix LDRs - are shared, which is sufficient to recover all voxel-variant pairs as well as to conduct voxel-level heritability and (cross-trait) genetic correlation analysis. Check the <a href="https://github.com/Zhiwen-Owen-Jiang/heig/wiki">tutorial</a> and the <a href="../records/13770930">example data</a> used in the tutorial. </p> <p>The shared data includes:</p> <p>1. Triplets for hippocampus shape measured by the radial distance from the medial model for each vertex. The original images contain 30,000 vertices while the shared data contains 49 LDRs. Left and right hemispheres were analyzed separately, each with 15,000 vertices.</p> <p>2. Triplets for 21 white matter tracts measured by fractional anisotropy. The original images contain 32,217 voxels and each tract contains 88 ~ 3503 voxels while the shared data contains 1,034 LDRs. Tracts were analyzed separately.</p> <p>3. Triplets for cortical surface curvature. The original images contain 59,412 vertices while the shared data contains 1,750 LDRs. The entire brain was analyzed as a whole.</p> <p>4. LD matrix and its inverse for 22 chromosomes including 460k genotyped SNPs. LD matrix and its inverse were estimated by using two separate datasets each containing 8.4k white unrelated subjects in UKB. Two regularization levels are provided: {85%, 80%} for heritability and genetic correlations within images and {75%, 70%} for cross-trait genetic correlations.</p> <p>5. LD matrix and its inverse for 22 chromosomes including 1.2 million imputed HapMap3 SNPs. LD matrix and its inverse were estimated by using two separate datasets each containing 42k white unrelated subjects in UKB. Two regularization levels are provided: {98%, 95%} for heritability and genetic correlations within images and {90%, 85%} for cross-trait genetic correlations.</p>
METHODS. Bovine ilia were used in the simulations because their histological structure (a fibrolamellar cortex overlying cancellous bone26) was found to match that of the Triceratops ilium. Bone sections 10 x 50 x 縠 3.0 cm with cortices ranging from 0.5 to 5.5 mm in depth (the range of initial cortical-thickness estimates based on gross morphology) were mounted on a servohydraulic mechanical loading frame (MTS Bionix, Minneapolis) and penetrated with an aluminium-bronze T. rex tooth replica. The replica was cast from an actual adult T. rex maxillary tooth, after casts made from some ofthe deeper bite marks revealed the size and shape of the teeth that had impacted the pelvis8 • The replica was penetrated into the ilia sections at 1 mm s-1 to a depth of 11.5 mm, equivalent to the maximum depth of the deepest ilium bite mark8 • Forces were measured with an MTS 25 N strain-gauge-based axial load cell accurate to 0.2%. The forces increased with increasing penetration depth even after the cortical layer had been perforated and the underlying cancellous bone was being crushed. The increase in force with penetration depth is attributed to a greater cortical surface area coming into contact with the semi-conical penetrator tooth as it descended through the ilia. in Bite-force estimation for Tyrannosaurus rex from tooth-marked bones
METHODS. Bovine ilia were used in the simulations because their histological structure (a fibrolamellar cortex overlying cancellous bone26) was found to match that of the Triceratops ilium. Bone sections 10 x 50 x 縠 3.0 cm with cortices ranging from 0.5 to 5.5 mm in depth (the range of initial cortical-thickness estimates based on gross morphology) were mounted on a servohydraulic mechanical loading frame (MTS Bionix, Minneapolis) and penetrated with an aluminium-bronze T. rex tooth replica. The replica was cast from an actual adult T. rex maxillary tooth, after casts made from some ofthe deeper bite marks revealed the size and shape of the teeth that had impacted the pelvis8 • The replica was penetrated into the ilia sections at 1 mm s-1 to a depth of 11.5 mm, equivalent to the maximum depth of the deepest ilium bite mark8 • Forces were measured with an MTS 25 N strain-gauge-based axial load cell accurate to 0.2%. The forces increased with increasing penetration depth even after the cortical layer had been perforated and the underlying cancellous bone was being crushed. The increase in force with penetration depth is attributed to a greater cortical surface area coming into contact with the semi-conical penetrator tooth as it descended through the ilia.
Template connectome harmonics for FreeSurfer template cortical surfaces using Gibbs Tractography Dataset
<p>The folder contains connectome harmonics for template surface meshes cvs_avg35_inMNI152, fsaverage45 and fsaverage5 from Freesurfer, using the Gibbs connectome tractography streamlines.<br> The connectome harmonics framework is integrated to the SCRIPTS pipeline, and the files present here use default parameters from Table 1 in Naze et al. 2020.</p> <p>Each .mat file include:<br> - graph Laplacian (L)<br> - connectome harmonics (H)<br> - connectome harmonics projected in the Desikan-Killiany atlas (H_DSK)<br> - local connectivity adjacency matrix (A_local)<br> - long-range connectivity adjacency matrix (A_ctx)<br> - vertices and faces of the cortical surface mesh (white matter - gray matter boundary)<br> - degree matrix (of combined adjacency matrices)<br> - eigenvalues of the eigendecomposition<br> - r, the ratio of local connections over all connections (local_vs_global_ratio)<br> - average (mu_cc) and standard deviation (sigma_cc) of the long-range connectome<br> - z_C, the weight threshold applied to the high resolution conectome to obtain its adjacency matrix (ta_zsc)</p> <p><br> Reference:<br> Naze S., Proix T., Atasoy S. & Kozloski J.R. (2020) Robustness of connectome harmonics to local gray matter and long-range white matter connectivity changes. <em>Neuroimage.</em></p>
Figure 2 from: Huntenburg J, Abraham A, Loula J, Liem F, Dadi K, Varoquaux G (2017) Loading and plotting of cortical surface representations in Nilearn. Research Ideas and Outcomes 3: e12342. https://doi.org/10.3897/rio.3.e12342
Figure 2 - Seed-based functional connectivity example. a Seed region in the posterior cingulate cortex (PCC). b Pearson product-moment correlation coefficient from the seed region time series to all other nodes. c The same map as in b, thresholded and plotted with a different colour scheme. d The same map as in b, plotted without sulcal depth information for shading.
Figure 1 from: Huntenburg J, Abraham A, Loula J, Liem F, Dadi K, Varoquaux G (2017) Loading and plotting of cortical surface representations in Nilearn. Research Ideas and Outcomes 3: e12342. https://doi.org/10.3897/rio.3.e12342
Figure 1 - Destrieux atlas plotted on the fsaverage5 surface template using the plot_surf_roi function. a Convoluted pial surface geometry of the left hemisphere. b Inflated pial surface geometry of the left hemisphere.
Data from: Cortical thickness, surface area and subcortical volume differentially contribute to cognitive heterogeneity in Parkinson's disease
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