# Visualizing cortical laminar architecture in the living human brain using next-generation ultra-high-gradient diffusion MRI

## TL;DR

This study uses advanced MRI to visualize the layered structure of the human brain's cortex, revealing patterns of cell and nerve density that match historical tissue samples.

## Contribution

The paper introduces a non-invasive method using ultra-high-gradient diffusion MRI to map cortical laminar architecture in living humans.

## Key findings

- Intra-soma signal fraction peaks at ~55% cortical depth, matching histological patterns.
- Visual cortex has higher intra-soma signal than motor cortex in deeper layers.
- Intra-soma signal correlates with cortical curvature in a layer-specific manner.

## Abstract

Characterizing cortical laminar microstructure is essential for understanding human brain function. Leveraging the next-generation Connectome MRI scanner (maximum gradient strength = 500mT/m, slew rate = 600T/m/s), we characterized in vivo cortical laminar cytoarchitecture and myeloarchitecture through cortical depth-dependent analyses of soma and neurite density imaging (SANDI) metrics derived from diffusion MRI, enhanced by a super-resolution technique. SANDI revealed distinct laminar profiles: intra-soma signal fraction fis peaked at ~ 55% cortical depth, while intra-neurite signal fraction fin increased toward deeper layers, consistent with histological patterns. The visual cortex exhibited higher intra-soma signal fraction fis than the motor cortex, particularly in deeper layers. Moreover, intra-soma signal fraction fis correlated positively with cortical curvature in superficial layers and negatively in deeper layers, indicating layer-specific relationships between microstructure and cortical geometry. These findings demonstrate the feasibility of noninvasively mapping cortical laminar architecture, offering a potential surrogate for histology and enabling future studies of normative and pathological brain organization using commercially available high-performance gradient MRI systems.