A novel graph neural network framework for resting-state functional MRI spatiotemporal dynamics analysis

Tao Wang, Zenghui Ding, Zheng Chang, Xianjun Yang, Yanyan Chen, Meng Li, Shu Xu and Yu Wang

Physica A: Statistical Mechanics and its Applications, 2025, vol. 669, issue C

Abstract: Graph neural networks (GNNs) are essential for studying brain functional connectivity and neural network activity, but the high dimensionality and complexity of resting-state functional magnetic resonance imaging (rs-fMRI), coupled with its spatiotemporal dynamic characteristics, pose challenges for traditional GNNs in spatiotemporal dynamic analysis.

Keywords: rs-fMRI; Static spatial graph; Dynamic temporal graph; Spatiotemporal dynamics analysis; Graph neural network (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:669:y:2025:i:c:s0378437125002341

DOI: 10.1016/j.physa.2025.130582

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