Digital Twin Brain Predicts rTMS Effects on Brain State Dynamics in Chronic Tinnitus

Abstract Predicting repetitive transcranial magnetic stimulation (rTMS) effects on whole-brain dynamics in clinical populations is crucial for developing personalized therapies and advancing precision medicine in brain disorders. This study provides the first proof-of-concept demonstrating that the Digital Twin Brain (DTB) can forecast rTMS effects on brain state dynamics in individuals with brain disorders (chronic tinnitus). First, we identified two aberrant brain states that predominantly overlapped with the somatomotor and default mode networks, respectively. Subsequently, we developed DTB for patients and derived regional responses for each brain region, revealing distinct roles of the parieto-occipital and frontal regions. Mechanistically, we examined the biological plausibility using tinnitus-specific risk genes and investigated the multi-scale neurobiological relevance. Clinically, we found that DTB can predict rTMS effects in an independent, longitudinal dataset (all r > 0.78). Particularly, the predictive capacity exhibits a state-specific nature. Overall, this work proposes a novel DTB-based framework for predicting rTMS effects in clinical populations and provides the first empirical evidence supporting its clinical utility. This approach may be generalizable to other brain disorders and neuromodulation techniques, promoting broader advancements in brain health.