Differential modulation of motor preparation by iTBS Over M1, SMA, and their combination

Background The movement-related cortical potential (MRCP) is generated primarily by the supplementary motor area (SMA) and primary motor cortex (M1). Brain computer interfaces (BCIs) leveraging the MRCP have emerged as a therapeutic option for supporting neurorehabilitation. Objectives This study aims to investigate whether intermittent theta burst stimulation (iTBS) applied to the primary motor cortex (M1), supplementary motor area (SMA), or both (M1 + SMA) enhances neural activity associated with endogenous motor preparation. Methods Fifteen participants performed a self-paced ballistic gripping task before and after receiving iTBS to M1, SMA, and M1 + SMA across three experiments. MRCPs were analyzed in four components: readiness potential (RP), negative slope (NS′), motor potential (MP), and peak negativity (PN). Signal-to-noise ratio (SNR) was calculated on individual MRCP trials. Artifacts were removed using independent component analysis, followed by manual inspection of trials to ensure only clear MRCPs were used in the repeated-measures statistical analysis. Results iTBS over M1 significantly enhanced the MP component. SMA stimulation reduced PN without affecting RP. Sequential M1 + SMA stimulation strongly facilitated the NS′ component and increased SNR. M1 stimulation effects peaked at 10 min post-stimulation, while SMA and sequential iTBS effects were strongest at 30 min. Conclusions Single- and multi-site iTBS modulated late-phase motor preparation, with early-phase activity remaining unchanged. M1 and sequential stimulation influenced different MRCP components, suggesting the former enhanced corticospinal output while sequential iTBS facilitated earlier cortical activity, perhaps through modulating connections between SMA and M1. Significance We show that iTBS can selectively enhance late-phase motor preparation, offering a promising avenue for both neurorehabilitation of individuals with motor impairments and performance optimization in athletic context. In improving quality of the MRCP signal, our findings can contribute to more reliable and responsive BCI designs.