Language-related functional connectivity in post-stroke aphasia: preliminary findings from a graph-theoretical and interpretable machine learning study
Our findings suggest that the high-level group relies on a synergistic interaction between the ventral stream (toITG) and the dorsal stream (pSMG). The shift toward increased local specialization, particularly the compensatory recruitment of the right pSMG, highlights a critical neural modularity strategy for functional recovery. These results suggest the feasibility of integrating graph metrics with interpretable machine learning, offering preliminary insights that could support the development of objective tools for monitoring aphasia rehabilitation.
Authors
- Christof Karmonik (ORCID: https://orcid.org/0000-0002-6695-9535)
- Abo Masahiro
- Ngoc Thanh Hoang
- Niluka Dilhani
- Thishuli Walpola
- Atsushi Senoo
Institutions
- Jikei University School of Medicine (JP)
- Houston Methodist (US)
- Cornell University (US)
- Hue University (VN)
- Methodist Hospital (US)
- Tokyo Metropolitan University (JP)
Publication Details
- Journal
- International Journal of Neuroscience
- Published
- 2026-03-13
- DOI
- https://doi.org/10.1080/00207454.2026.2644508
- Primary Topic
- Neurobiology of Language and Bilingualism
- Type
- article
- Field-Weighted Citation Impact
- 0.00