Brain-computer interface training for multimodal functional recovery in patients with brain injury: a case series
Motor imagery-based BCI training may facilitate recovery across motor, language, and cognitive domains in patients with subacute brain injury. Functional gains were supported by neurophysiological and connectomics evidence of cross-network reorganization. These preliminary findings suggest that personalized BCI protocols could represent a promising avenue for multimodal neurorehabilitation.
Authors
- Jun‐Hao Wang (ORCID: https://orcid.org/0000-0001-9690-1484)
- Sun‐Wei Guo (ORCID: https://orcid.org/0000-0002-8511-7624)
- Gangli Zhang (ORCID: https://orcid.org/0000-0003-1335-4046)
- Peili Cao
- Javier Muñoz (ORCID: https://orcid.org/0000-0003-3288-3496)
- Fulong Zhang (ORCID: https://orcid.org/0000-0002-1211-3294)
- Brandon Lucke-Wold
- Xiang Zan
- Rui Cheng
Institutions
- Shanxi Medical University (CN)
- Xiamen University (CN)
- University of Florida (US)
- First Affiliated Hospital of Jinan University (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-09-24
- DOI
- https://doi.org/10.21037/qims-2025-1136
- Citations
- 1
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.43