2D histology meets 3D topology: Cytoarchitectonic brain mapping with Graph Neural Networks

by   Christian Schiffer, et al.

Cytoarchitecture describes the spatial organization of neuronal cells in the brain, including their arrangement into layers and columns with respect to cell density, orientation, or presence of certain cell types. It allows to segregate the brain into cortical areas and subcortical nuclei, links structure with connectivity and function, and provides a microstructural reference for human brain atlases. Mapping boundaries between areas requires to scan histological sections at microscopic resolution. While recent high-throughput scanners allow to scan a complete human brain in the order of a year, it is practically impossible to delineate regions at the same pace using the established gold standard method. Researchers have recently addressed cytoarchitectonic mapping of cortical regions with deep neural networks, relying on image patches from individual 2D sections for classification. However, the 3D context, which is needed to disambiguate complex or obliquely cut brain regions, is not taken into account. In this work, we combine 2D histology with 3D topology by reformulating the mapping task as a node classification problem on an approximate 3D midsurface mesh through the isocortex. We extract deep features from cortical patches in 2D histological sections which are descriptive of cytoarchitecture, and assign them to the corresponding nodes on the 3D mesh to construct a large attributed graph. By solving the brain mapping problem on this graph using graph neural networks, we obtain significantly improved classification results. The proposed framework lends itself nicely to integration of additional neuroanatomical priors for mapping.



page 3

page 6


Convolutional Neural Networks for cytoarchitectonic brain mapping at large scale

Human brain atlases provide spatial reference systems for data character...

Contrastive Representation Learning for Whole Brain Cytoarchitectonic Mapping in Histological Human Brain Sections

Cytoarchitectonic maps provide microstructural reference parcellations o...

Parcellation of Visual Cortex on high-resolution histological Brain Sections using Convolutional Neural Networks

Microscopic analysis of histological sections is considered the "gold st...

Improving Cytoarchitectonic Segmentation of Human Brain Areas with Self-supervised Siamese Networks

Cytoarchitectonic parcellations of the human brain serve as anatomical r...

PRAGMA: Interactively Constructing Functional Brain Parcellations

A prominent goal of neuroimaging studies is mapping the human brain, in ...

Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain Connectivity

Brain image analysis has advanced substantially in recent years with the...

Investigating cognitive ability using action-based models of structural brain networks

Recent developments in network neuroscience have highlighted the importa...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.