Effects of Sequential Dual-Target TMS on the Dynamic Characteristics of Brain Networks as Revealed by fNIRS

Abstract

Transcranial magnetic stimulation (TMS) modulates cortical excitability to promote neuroplasticity, but single-target TMS has limited effects on multi-region synergy. Sequential dual-target TMS may enhance brain network reorganization through temporal stimulation, though its mechanisms remain unclear. This study investigates the immediate effects of single- and dual-target TMS on brain functional networks in stroke patients using functional near-infrared spectroscopy (fNIRS) and dynamic functional connectivity (dFNC) analysis. Fifteen subacute stroke patients and fifteen healthy controls underwent three interventions: single-target SMA-rTMS, single-target LDLPFC-rTMS, and sequential dual-target stimulation (Dual-rTMS). fNIRS data were analyzed via dFNC to identify connectivity states (weak, moderate, strong) and evaluate time fraction, state transitions, global efficiency, and total signal power. Results revealed three dFNC states: State 1 (weak connectivity, 44.24%), State 2 (moderate, 39.44%), and State 3 (strong, 16.32%). Single-target TMS (especially SMA-rTMS) increased time fraction in State 1, indicating low-connectivity induction, while Dual-rTMS further prolonged State 1 and reduced inefficient transitions (e.g., State 1 → 2: p < 0.005). Stroke patients showed impaired transitions from State 2 → 3 (p = 0.024) versus controls. Time fraction in State 3 correlated positively with motor function scores (FMA-LE: r = 0.52, p = 0.045; BBS: r = 0.52, p = 0.047), while State 1 correlated negatively (FMA-LE: r = -0.52, p = 0.045). Sequential dual-target TMS optimizes network dynamics by sustaining low-energy states and suppressing maladaptive transitions, outperforming single-target approaches. dFNC temporal patterns may serve as biomarkers for post-stroke motor function, supporting sequential dual-target TMS as a promising rehabilitation tool.