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Relating quantitative 7T MRI across cortical depths to cytoarchitectonics, gene expression and connectomics.

Authors :
McColgan, Peter
Helbling, Saskia
Vaculčiaková, Lenka
Pine, Kerrin
Wagstyl, Konrad
Attar, Fakhereh Movahedian
Edwards, Luke
Papoutsi, Marina
Wei, Yongbin
Van den Heuvel, Martijn Pieter
Tabrizi, Sarah J
Rees, Geraint
Weiskopf, Nikolaus
Source :
Human Brain Mapping. Oct2021, Vol. 42 Issue 15, p4996-5009. 14p.
Publication Year :
2021

Abstract

Ultra‐high field MRI across the depth of the cortex has the potential to provide anatomically precise biomarkers and mechanistic insights into neurodegenerative disease like Huntington's disease that show layer‐selective vulnerability. Here we compare multi‐parametric mapping (MPM) measures across cortical depths for a 7T 500 μm whole brain acquisition to (a) layer‐specific cell measures from the von Economo histology atlas, (b) layer‐specific gene expression, using the Allen Human Brain atlas and (c) white matter connections using high‐fidelity diffusion tractography, at a 1.3 mm isotropic voxel resolution, from a 300mT/m Connectom MRI system. We show that R2*, but not R1, across cortical depths is highly correlated with layer‐specific cell number and layer‐specific gene expression. R1‐ and R2*‐weighted connectivity strength of cortico‐striatal and intra‐hemispheric cortical white matter connections was highly correlated with grey matter R1 and R2* across cortical depths. Limitations of the layer‐specific relationships demonstrated are at least in part related to the high cross‐correlations of von Economo atlas cell counts and layer‐specific gene expression across cortical layers. These findings demonstrate the potential and limitations of combining 7T MPMs, gene expression and white matter connections to provide an anatomically precise framework for tracking neurodegenerative disease. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10659471
Volume :
42
Issue :
15
Database :
Academic Search Index
Journal :
Human Brain Mapping
Publication Type :
Academic Journal
Accession number :
152513516
Full Text :
https://doi.org/10.1002/hbm.25595