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Using diffusion MRI to discriminate areas of cortical grey matter

Ganepola, T; Nagy, Z; Ghosh, A; Papadopoulo, T; Alexander, DC; Sereno, MI; (2017) Using diffusion MRI to discriminate areas of cortical grey matter. NeuroImage 10.1016/j.neuroimage.2017.12.046. (In press). Green open access

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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.

Type: Article
Title: Using diffusion MRI to discriminate areas of cortical grey matter
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuroimage.2017.12.046
Publisher version: http://dx.doi.org/10.1016/j.neuroimage.2017.12.046
Language: English
Additional information: © 2018 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Keywords: Architectonics, Cortex, Cortical surface, Grey matter, HARDI, Parcellation, Supervised leaning, dMRI
URI: http://discovery.ucl.ac.uk/id/eprint/10041295
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