Combining Transcranial Magnetic Stimulation and Semantic Training to Promote Language Recovery in Aphasia: Evidence from Neural Circuit Remodeling and Machine Learning Prediction

Background : Aphasia is a frequent and debilitating outcome of stroke, often persisting into the chronic stage and significantly affecting communication ability. While transcranial magnetic stimulation (TMS) and semantic training have each demonstrated therapeutic benefits, their synergistic effects and underlying mechanisms remain to be fully elucidated. This study aimed to examine the efficacy of high-frequency TMS combined with semantic training in improving language function in patients with post-stroke aphasia, and to explore neural connectivity changes and predictive modeling of recovery outcomes. Results : The TMS plus semantic training group showed significantly greater improvement in WAB-AQ compared to both the sham and control groups. Resting-state fMRI revealed enhanced connectivity between the left IFG and posterior temporal-parietal regions post-intervention. Among the predictive models, linear regression achieved the best performance (R²= 0.47, RMSE = 3.96), followed closely by random forest (R²= 0.44, RMSE = 3.91), while SVM and XGBoost performed less optimally. Conclusions : Combined TMS and semantic therapy effectively enhances language recovery in chronic aphasia, likely through remodeling of left-hemispheric language circuits. Furthermore, regression-based models show promise in predicting treatment outcomes and may inform individualized rehabilitation strategies.