Decoding Grey Matter - Meshes
收藏DataCite Commons2025-10-31 更新2026-02-09 收录
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https://research-data.cardiff.ac.uk/articles/dataset/Decoding_Grey_Matter_-_Meshes/30491159
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The following meshes are associated with the paper 'Decoding Gray Matter: large-scale analysis of brain cell morphometry to inform microstructural modeling of diffusion MR signals'Grey matter structure is a key focus in neuroscience, as cell morphology varies by type and can be affected by neurological conditions. Understanding these variations is essential for studying brain function and disease. Diffusion-weighted MRI (dMRI) is a powerful tool for examining cellular microstructure in vivo, but its accuracy depends on identifying which morphological features influence its measurements. Despite growing interest, no systematic report has defined key neural cell traits.We analysed more than 11,800 3D cellular reconstructions, obtained from Neuromorpho.org, across three species and nine cell types, establishing reference values for critical traits. To complement the statistical analysis, here we also provide high resolution 3D surface meshes representative of each cell type and species. For each cell type we provide 50 .ply meshes and the corresponding cellular skeleton saved as an .swc file. All meshes were meshed in blender using matlab scripts, which are publicly available on github. These meshes are fully compatible with Monte Carlo simulators, offering a valuable resource for the modelling community.
提供机构:
Cardiff University
创建时间:
2025-10-31



