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IECE Transactions on Intelligent Systematics, 2024, Volume 1, Issue 2: 58-68

Free Access | Review Article | 23 September 2024
1 Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 637141, Singapore
2 Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 637141, Singapore
3 Department of Obstetrics and Gynecology, Jiangxi Fifth People’s Hospital, Nanchang 330002, China
* Corresponding author: Qian Hong, email: [email protected]
Received: 20 August 2024, Accepted: 14 September 2024, Published: 23 September 2024  

Abstract
The integration of graph neural networks (GNNs) with brain functional network analysis is an emerging field that combines neuroscience and machine learning to enhance our understanding of complex brain dynamics. We first briefly introduce the fundamentals of brain functional networks, followed by an overview of Graph Neural Network principles and architectures. The review then focuses on the applications of these networks and address current challenges in the field, such as the need for interpretable models and effective integration of multi-modal neuroimaging data. We also highlight the potential of GNNs in clinical perimenopausal areas such as perimenopausal depression research, demonstrating the broad applicability of this approach. The review concludes by outlining future research directions, including the development of more sophisticated architectures for large-scale, heterogeneous brain graphs, and the exploration of causal inference in brain networks. By synthesizing recent advances and identifying key research directions, this review aims to summarize the focal points of brain functional network analysis and GNNs, explore the potential of their integration, and provide a reference for advancing this interdisciplinary field.

Graphical Abstract
Modeling Brain Functional Networks Using Graph Neural Networks: A Review and Clinical Application

Keywords
Graph Neural Networks
Brain Functional Networks
Neuroimaging Analysis

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APA Style
Zhang, W. & Hong, Q. (2024). Modeling Brain Functional Networks Using Graph Neural Networks: A Review and Clinical Application. IECE Transactions on Intelligent Systematics, 1(2), 58–68. https://doi.org/10.62762/TIS.2024.680959

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