Multi-scale EEG analysis identifies neural circuit signatures of iTBS responsiveness in major depressive disorder
EEG-based deep learning, combined with biophysically informed connectivity modeling, enables reliable prediction of iTBS outcomes in MDD. Subtype-specific disruptions in frontal-temporal coupling emerge as candidate biomarkers, offering mechanistic insight into neuromodulation response and a framework for personalized TMS interventions.
Authors
- Ziqi Sun
- Tiannan Shao
- Leilei Zheng (ORCID: https://orcid.org/0000-0003-1631-5683)
- Zheng Lin (ORCID: https://orcid.org/0009-0009-6711-4524)
- Qiutang Wang
- Jihan Fu
- Yuhang Han
Institutions
- Zhejiang Tongji Vocational College of Science and Technology (CN)
- Second Affiliated Hospital of Zhejiang University (CN)
Publication Details
- Journal
- NeuroImage
- Published
- 2026-01-06
- DOI
- https://doi.org/10.1016/j.neuroimage.2026.121697
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00