Adaptive Frequency‐Optimized Wavelet Networks for Early Detection of Subjective Cognitive Decline via Resting‐State fMRI
The FSAWT model offers a robust framework for early SCD detection by integrating frequency-specific and cross-frequency dynamics. While these findings highlight potential contributions to precision diagnostics and personalized interventions for neurodegenerative disorders, such applications remain to be established in future studies. Future applications may also explore multimodal neuroimaging and broader cognitive impairments.
Authors
- Yongjun Tan (ORCID: https://orcid.org/0000-0002-0765-108X)
- Zhongfeng Xie
- Mengling Tao (ORCID: https://orcid.org/0009-0007-1947-5208)
- Xiaowen Xu (ORCID: https://orcid.org/0000-0002-1373-4316)
- Peijun Wang (ORCID: https://orcid.org/0000-0002-1901-6569)
- Weikai Li (ORCID: https://orcid.org/0000-0002-5114-9660)
- Pei‐Ying Chen (ORCID: https://orcid.org/0000-0003-2288-3927)
- Yongsheng Xiang
- Yingying Liu
- Yupan Ding
- Xiereniguli Anayiti
Institutions
- Tongji University (CN)
- Tongji Hospital (CN)
- Artificial Intelligence in Medicine (Canada) (CA)
- Chongqing Jiaotong University (CN)
Publication Details
- Journal
- Brain and Behavior
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/brb3.71039
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Shanghai Municipal Health Commission
- National Natural Science Foundation of China
- Tongji University
- Natural Science Foundation of Chongqing
- Chongqing Municipal Education Commission
- Centre Scientifique et Technique du Bâtiment
- Shanghai Municipal Health and Family Planning Commission