Synopsis

Keywords: Gray Matter, Ex-Vivo Applications, cortical laminae, microstructure, magnetic susceptibility, human brain

Although recent high-resolution functional MRI studies have revealed laminar-specific cortical activity in the human brain, the underlying structural underpinning remains unclear. The present study collected submillimeter-resolution MR images from 10 ex-vivo human hemispheres. We computed the microstructural metrics and magnetic susceptibility for each sample at different cortical depths. We found that the cortical microstructure and magnetic susceptibility showed a depth-dependent pattern, which varied in different cortical regions. The cortical profiles were then correlated with cell density and myelin content obtained from histological staining. These findings may help to understand the structural basis of laminar brain function.

Introduction

The human neocortex is consisted of six cytoarchitectonic cortical layers, with different cell density, cell size and cell type, which are connected to different brain areas ^{1, 2}. Recently, laminar fMRI studies have demonstrated a close relationship between layer-specific activity and brain responses (e.g., feedforward and feedback) ³ and information flow (e.g., top-down and bottom-up signal) ⁴. However, the structural basis underlying the laminar-specific brain function is unclear, probably due to limited spatial resolution in in-vivo MRI measurement. This study acquired submillimeter-resolution MR images from ten ex-vivo human brains to investigate the changes of the microstructure and magnetic susceptibility with cortical depths, and estimate their association with the density and myelin content obtained from histology.

Methods

Data acquisition: 10 right hemispheres from 10 subjects (male:female = 9:1, age ranged from 48 to 89 years) were obtained according to the Standardized Operational Protocol for Human Brain Bank in China ⁵. All MRI scans were performed on a Siemens 7T MAGNETOM scanner with a 32 channel head coil. T2-weighted images were acquired with the following parameters: repetition time (TR) = 12510 ms; echo times (TE) = 24 ms; voxel size = 0.5 × 0.5 × 0.6 mm³; and 10 averages. Quantitative susceptibility mapping (QSM) was obtained using a 3D multi-gradient-echo (MGE) sequence with the following parameters: TR = 100 ms; TE = 4.0, 8.1, 12.2, 16.4, 20.5, 24.6, 28.8, 32.9, 37.1, 41.2, 45.2, and 49.3 ms; voxel size = 0.6 × 0.6 × 1 mm³; and 8 average. Diffusion MRI was acquired with a 3D diffusion-weighted steady state free precession (DW-SSFP) sequence with the following parameters: TR = 29 ms; TE = 21 ms; voxel size = 0.8 × 0.8 × 0.8 mm³; 20 images (b0) without diffusion weighting and 60 non-colinear diffusion directions at b-value of 6,000 s/ mm². After the MRI scans, four small cortical tissues were dissected from frontal, parietal, temporal and occipital lobes from one subject, which were stained with H&E for cell density and MBP for myelin measurement.
Data processing: As shown in Fig 1, we first segmented the grey matter cortex into six equidistance laminas in five slices from the T2-weighted image in the same spatial location for each subject using LAYNII toolbox ⁶. Then, we calculated FA, MD, AD and RD maps in the diffusion data after denoising and bias field correction in MRtrix3 (https://www.mrtrix.org/), and computed magnetic susceptibility maps using the FastQSM method ⁷ in Susceptibility Tensor Imaging Suite toolbox (http://people.duke.edu/~cl160/). Next, we registered these quantitative maps to T2-weighted space, and manual segmented the frontal, parietal, temporal, and occipital lobes to obtain layer-specific measurements in each lobe. In addition, we used color deconvolution and Otsu threshold methods to obtain cell and myelin density maps from H&E and MBP staining, respectively, which were also divided into six laminas. Finally, we manually matched MR images with the histological images, and examined their correlations across all laminas.

Results

From pial surface to white matter (WM), the diffusivity decreasd almostly linearly as the cortical depth increased and the FA showed a nonlinear increase in all subjects, and the depth-dependent profile differed among the four lobes (Fig.2 A-D). The signed QSM (both positive and negative) gradually changed from negative to positive values, in which the positive QSM increased and the negative QSM decreased with cortical depths (Fig.2 E-G).
The density of cell and myelin obtained from H&E and MBP displayed a depth-dependent increase from pial surface to WM in four cortical regions (Fig.3). After manually matching the MR and histological images (Fig. 4), MRI-histology correlation analysis demonstrated a positive correlation between QSM and myelin density and negative correltations between the diffusivities and cell density (Fig. 5).

Discussion and Conclusion

This study, for the first time, combined submilimeter-resolution MRI and histological staining to investigated the cortical lamina-specific microstrcture and magnetic suscetibility in ex-vivo human brains. We found that, from pial surface to WM, the diffusional anisotropy increased and the diffusivity decreased in the cortex, which were consistent with recent in-vivo findings ^{8, 9}, suggesting the deeper layer has more complex microstructure (corresponding to the richer cell and myelin identified from histology) to restrict the water diffusion. Moreover, QSM results indicated that the positive magnetic susceptibility increased and the negative magnetic susceptibility decreased with the depth, and finally completed change from diamagnetism at pial-surface to paramagnetism at deep-surface, which was in accordance with a recent R2*-based study ¹⁰. This finding also supports that the suferficial WM, close to the deepest cortical layer, has a paramagnetic contrast which is driven by iron ¹¹. MRI-histology correlations demonstrated that the depth-dependent changes of MRI measurement in cortical lamines were associated with the underlying cell/myelin compositions. These findings may be contributed to understanding the structural basis of laminar function.

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