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Neuroimage. 2019 Jan 15;185:27-34. doi: 10.1016/j.neuroimage.2018.10.023. Epub 2018 Oct 9.

Depth-dependent intracortical myelin organization in the living human brain determined by in vivo ultra-high field magnetic resonance imaging.

Author information

1
Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands; Department of Cognitive Neuroscience, Radboudumc, Nijmegen, the Netherlands.
2
Translational and Molecular Imaging Institute Translational and Molecular Imaging Institute and Brain Imaging Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
3
Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
4
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
5
Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
6
Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Electronic address: sophia.frangou@mssm.edu.

Abstract

BACKGROUND:

Intracortical myelin is a key determinant of neuronal synchrony and plasticity that underpin optimal brain function. Magnetic resonance imaging (MRI) facilitates the examination of intracortical myelin but presents with methodological challenges. Here we describe a whole-brain approach for the in vivo investigation of intracortical myelin in the human brain using ultra-high field MRI.

METHODS:

Twenty-five healthy adults were imaged in a 7 Tesla MRI scanner using diffusion-weighted imaging and a T1-weighted sequence optimized for intracortical myelin contrast. Using an automated pipeline, T1 values were extracted at 20 depth-levels from each of 148 cortical regions. In each cortical region, T1 values were used to infer myelin concentration and to construct a non-linearity index as a measure the spatial distribution of myelin across the cortical ribbon. The relationship of myelin concentration and the non-linearity index with other neuroanatomical properties were investigated. Five patients with multiple sclerosis were also assessed using the same protocol as positive controls.

RESULTS:

Intracortical T1 values decreased between the outer brain surface and the gray-white matter boundary following a slope that showed a slight leveling between 50% and 75% of cortical depth. Higher-order regions in the prefrontal, cingulate and insular cortices, displayed higher non-linearity indices than sensorimotor regions. Across all regions, there was a positive association between T1 values and non-linearity indices (P < 10-5). Both T1 values (P < 10-5) and non-linearity indices (P < 10-15) were associated with cortical thickness. Higher myelin concentration but only in the deepest cortical levels was associated with increased subcortical fractional anisotropy (P = 0.05).

CONCLUSIONS:

We demonstrate the usefulness of an automatic, whole-brain method to perform depth-dependent examination of intracortical myelin organization. The extracted metrics, T1 values and the non-linearity index, have characteristic patterns across cortical regions, and are associated with thickness and underlying white matter microstructure.

KEYWORDS:

Cortical depth-levels; Myeloarchitecture; Neuroimaging; Ultra-high field

PMID:
30312809
PMCID:
PMC6289812
[Available on 2020-01-15]
DOI:
10.1016/j.neuroimage.2018.10.023
[Indexed for MEDLINE]
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