Gyral-Sulcal-Net: An Integrated Network Representation of Brain Folding Patterns

TL;DR

This paper introduces Gyral-Sulcal-Net, a novel unified network model that captures detailed brain folding patterns, enhancing the understanding of brain organization and its relation to health and disease.

Contribution

The study presents a new integrated network model combining gyri and sulci patterns, with successful identification of three types of landmarks across diverse datasets.

Findings

GS-Net effectively represents cortical folding patterns

It integrates diverse anatomical landmarks into a unified network

The approach is validated across multiple age groups and conditions

Abstract

Our brain functions as a complex communication network, and studying it from a network perspective offers valuable insights into its organizational principles and links to cognitive functions and brain disorders. However, most current network studies typically use brain regions as nodes, often overlooking the intricate folding patterns of finer-scale anatomical landmarks within these regions. In this study, we introduce a novel approach to integrate the brain's two primary folding patterns - gyri and sulci - into a unified network termed the Gyral-Sulcal-Net (GS-Net), in which three different types of finer-scale landmarks have been successfully identified. We evaluated the proposed GS-Net across multiple datasets, comprising over 1,600 brains, spanning different age groups (from 34 gestational weeks to elderly adults) and cohorts (healthy brains and those with pathological conditions). The experimental results demonstrate that the GS-Net can effectively integrate and represent diverse cortical folding patterns from a network perspective. More importantly, this approach offers a promising way for integrating different folding patterns into a unified anatomical brain network, alongside structural and functional networks, providing a comprehensive framework for studying brain networks.