App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 6

Functional magnetic resonance spatio-temporal dual-stream brain network analysis method incorporating group prior information

Wu Yandi1
Wang Chen1
Wang Junze1
Liu Lei2
Zhang Limei1
1. School of Computer and Artificial Intelligence, Shandong Jianzhu University Shandong 250101, China
2. Shandong Provincial Mental Health Center Shandong 250014, China
DOI: 10.19734/j.issn.1001-3695.2025.10.0415

Abstract

Brain network analysis methods based on functional magnetic resonance imaging (fMRI) serve as a critical tool for diagnosing brain disorders. However, existing deep learning approaches predominantly focus on spatial structures while neglecting temporal dynamics and group-level prior information among subjects, resulting in insufficient exploration of temporal features and utilization of inter-subject similarity relationships. To address these limitations, we propose a Spatio-Temporal Dual-Stream Model (STDSM) incorporating group-level prior information: First, we establish a parallel spatio-temporal feature learning framework based on Graph Isomorphism Networks (GIN) and Mamba, which jointly capture the spatial and temporal characteristics of brain activity. Simultaneously, we incorporate group graph structures to embed prior similarity relationships among subjects, achieving representation optimization at the group level through neighborhood feature aggregation. Experiments on the public autism (ABIDE) and depression (REST-Meta-MDD) datasets demonstrate that STDSM exhibits outstanding disease prediction capabilities. By synergistically modeling spatio-temporal information and explicitly leveraging group priors, it effectively enhances the discriminative and generalization performance of brain disease prediction.

Foundation Support

国家自然科学基金面上项目(62176112,62476155)
山东省自然科学基金面上项目(ZR2024MF063)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.10.0415
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 6

Publish History

[2026-02-25] Accepted Paper

Cite This Article

吴燕棣, 王晨, 王俊泽, 等. 一种嵌入群体先验的功能磁共振时空双流脑网络分析方法 [J]. 计算机应用研究, 2026, 43 (6). (2026-02-25). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0415. (Wu Yandi, Wang Chen, Wang Junze, et al. Functional magnetic resonance spatio-temporal dual-stream brain network analysis method incorporating group prior information [J]. Application Research of Computers, 2026, 43 (6). (2026-02-25). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0415. )

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  • Application Research of Computers Monthly Journal
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    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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