Advanced Graph Neural Networks for Structural and Functional Brain Networks

COEX 

Understanding the intricate organization of the human brain, both structurally and functionally, is a pivotal pursuit in neuroscience. In recent years, graph neural networks (GNNs) have emerged as powerful tools for modeling complex relationships in various domains, including neuroscience. This tutorial aims to provide a comprehensive overview of the fundamental concepts of GNNs and their application in the analysis of brain structural and functional connectivity.
The tutorial will commence with a thorough exploration of the basics of graph neural networks, elucidating their foundational principles and mechanisms. Participants will gain insights into how GNNs operate in capturing intricate patterns within networked data. Building upon this foundational knowledge, the tutorial will then delve into our recent advancements in the development of sophisticated graph neural networks tailored for the analysis of brain connectivity. Our cutting-edge graph neural networks facilitate the examination of connectivity at multiple levels of granularity within the brain. Participants will be introduced to techniques enabling the analysis of connectivity between individual brain regions, the exploration of structural and functional connectivity, and the examination of intricate relationships among clusters of brain regions.