Gamma transcranial alternating current stimulation increases segregation in the sensorimotor network

Introduction: Transcranial alternating current stimulation (tACS) has emerged as a promising tool to modulate brain dynamics, especially in the context of motor recovery in clinical populations. Yet, its network-level effects on the sensorimotor (SM) functional organization have only been partially explored. In this study, we investigated whether gamma-frequency tACS can modulate functional connectivity and enhance segregation within the SM network, which is an index typically associated with better motor performance. Methods: In a within-subject, sham-controlled design, EEG was recorded before and after gamma tACS in 34 healthy subjects. Functional connectivity was quantified across three SM sub-networks, according to Yeo's parcelation, in five frequency bands, including delta, theta, alpha, beta, and gamma, using intra- and inter-network connectivity (IntraNC and InterNC, respectively) measures. ANCOVA tests were performed on IntraNC and InterNC values for each frequency band, to compare the sham and real condition at post p-stimulation hase. The connectivity values of the pre-stimulation phase were used as a covariate, to account for state-dependent effects. Results: = 0.029, FDR-corrected). Furthermore, we reported increased segregation post-tACS in specific SM sub-networks for alpha and beta frequency bands, primarily driven by enhanced IntraNC. No effects were observed in delta or theta frequency bands. Discussion: Albeit we did not find significant interactions of time and stimulation condition, additional analyses showed that gamma tACS might selectively modulate oscillatory dynamics within SM sub-networks, enhancing functional segregation in a frequency-specific manner. Given the roles of alpha/beta in sensorimotor integration and gamma in local processing, these effects might reflect more efficient neural communication. Our results support the potential of tACS as a neuromodulatory intervention to target dysfunctional network interactions in clinical populations.