Personalized high-intensity temporal interference stimulation decouples cerebellar networks to enhance implicit learning

Abstract Objective Despite the central role of deep brain structures such as the striatum in motor learning, existing noninvasive stimulation methods are hindered by limited depth and precision. Temporal interference (TI) stimulation presents the potential for precise, individualized modulation of deep regions. However, how TI stimulation influences deep brain activity and large-scale network reorganization to facilitate motor learning is still unclear. Therefore, this study aimed to clarify these mechanisms by investigating how personalized, high-intensity TI targeting the striatum modulates neural activity and enhances motor learning. Methods Twenty-six healthy right-handed male participants were enrolled in a randomized, double-blind, sham-controlled crossover study. Each participant received both TI and sham stimulation targeting the right striatum (10 mA, Δf = 20 Hz) through an individualized electrode montage. Resting-state functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and serial reaction time (SRT) task performance were assessed before and after each intervention. Neural analyses included static and dynamic fractional amplitude of low-frequency fluctuation (fALFF) in the target region, structural connectivity (SC)–functional connectivity (FC) coupling and topological metrics across six major brain networks, as well as brain-behavior correlations related to learning performance. Results (1) Target region activity: TI stimulation significantly increased both static and dynamic fALFF in the right striatum (Cohen’s d = 0.49, p = 0.016; Cohen’s d = 0.39, p = 0.035). (2) Brain network reorganization: Compared with the Sham group, the TI group exhibited significantly reduced SC-FC coupling in the cerebellar network (CN) (t = – 2.279, Cohen’s d = -0.82, p = 0.027, FDR corrected). TI stimulation significantly enhanced nodal degree in the cerebellar network (CN) and nodal efficiency the cingulo-opercular network (CON) (FDR corrected with Bonferroni correction, p < 0.0083) following the stimulation. Behavioral performance: The TI stimulation significantly improved performance in second implicit learning (SIL) after stimulation (Cohen’s d = 0.47, p = 0.043). Brain-behavior correlation: Changes in SC-FC coupling in the CN were significantly negatively correlated with improvement in SIL (r = – 0.372, p = 0.040). Conclusion Personalized high-intensity TI of the striatum enhances deep target activity and promotes selective network reorganization, particularly by reducing SC-FC coupling and strengthening intra-network connectivity in the CN. These network-level modulations underlie improved implicit learning performance, highlighting the potential of TI neuromodulation as a precise and effective approach for promoting motor learning by targeting deep nuclei and large-scale brain networks. Trial registration number ChiCTR2500098699.