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Contribution Details
| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Using diffusion MRI to discriminate areas of cortical grey matter |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | NeuroImage |
| Publisher | Elsevier |
| Geographical Reach | international |
| ISSN | 1053-8119 |
| Volume | 182 |
| Page Range | 456 - 468 |
| Date | 2018 |
| Abstract Text | Cortical area parcellation is a challenging problem that is often approached by combining structural imaging (e.g., quantitative T1, diffusion-based connectivity) with functional imaging (e.g., task activations, topological mapping, resting state correlations). Diffusion MRI (dMRI) has been widely adopted to analyse white matter microstructure, but scarcely used to distinguish grey matter regions because of the reduced anisotropy there. Nevertheless, differences in the texture of the cortical 'fabric' have long been mapped by histologists to distinguish cortical areas. Reliable area-specific contrast in the dMRI signal has previously been demonstrated in selected occipital and sensorimotor areas. We expand upon these findings by testing several diffusion-based feature sets in a series of classification tasks. Using Human Connectome Project (HCP) 3T datasets and a supervised learning approach, we demonstrate that diffusion MRI is sensitive to architectonic differences between a large number of different cortical areas defined in the HCP parcellation. By employing a surface-based cortical imaging pipeline, which defines diffusion features relative to local cortical surface orientation, we show that we can differentiate areas from their neighbours with higher accuracy than when using only fractional anisotropy or mean diffusivity. The results suggest that grey matter diffusion may provide a new, independent source of information for dividing up the cortex. |
| Free access at | PubMed ID |
| Digital Object Identifier | 10.1016/j.neuroimage.2017.12.046 |
| PubMed ID | 29274501 |
| Other Identification Number | merlin-id:15869 |
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| Keywords | Cortex, cortical surface, architectonics, grey matter, parcellation, HARDI, dMRI, supervised leaning |
| Additional Information | Open Access gemäss https://www.sciencedirect.com |