dorsal/arxiv
View SchemaGyral-Sulcal-Net: An Integrated Network Representation of Brain Folding Patterns
| Authors | Chao Cao, Tong Chen, Nan Zhao, Minheng Chen, Michael Qu, Zeyu Zhang, Xiao Shi, Xiang Li, Tianming Liu, Lu Zhang |
|---|---|
| Categories | |
| ArXiv ID | 2601.08818vv2 |
| URL | https://arxiv.org/abs/2601.08818 |
| License | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
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. (The GS-Net toolbox will be released soon.)
{
"annotation_id": "0bcd0d39-ffad-47a0-b129-0badcc87ba1a",
"date_created": "2026-02-17T05:53:16.187000Z",
"date_modified": "2026-02-17T05:53:16.187000Z",
"file_hash": "90e391221890bf61dea3d05029ef9b2edd8dda30db596f57f2196c136ff46991",
"private": false,
"record": {
"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\u0027s 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. (The GS-Net toolbox will be released soon.)",
"arxiv_id": "2601.08818",
"authors": [
"Chao Cao",
"Tong Chen",
"Nan Zhao",
"Minheng Chen",
"Michael Qu",
"Zeyu Zhang",
"Xiao Shi",
"Xiang Li",
"Tianming Liu",
"Lu Zhang"
],
"categories": [
"q-bio.NC"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"title": "Gyral-Sulcal-Net: An Integrated Network Representation of Brain Folding Patterns",
"url": "https://arxiv.org/abs/2601.08818",
"version": "v2"
},
"schema_id": "dorsal/arxiv",
"source": {
"execution_id": "0e9760c4-5273-450f-a127-46da7bdc639e",
"id": "arXiv Dataset",
"type": "Model",
"variant": "snapshot-2026-01-17",
"version": "0.1.0"
},
"user_id": 1000002
}