Pulse waveform and current direction alter network-level TMS-induced functional connectivity: Evidence from TMS-EEG

Functional connectivity analyses of electroencephalographic (EEG) data during concurrent transcranial magnetic stimulation (TMS) can offer valuable insight into large-scale network dynamics. Still, the influence of TMS features on these measurements remains poorly understood. This study investigates the impact of key TMS parameters – pulse waveform and current direction – on the induced EEG functional connectivity of the motor system in the alpha and beta frequency bands. We analyzed data from 32 healthy participants retrieved from an open-access repository. Left primary motor cortex (M1) was stimulated at rest while varying TMS pulse waveform (monophasic, biphasic) and current direction (posterior-to-anterior – PA, anterior-to-posterior – AP). TMS-induced functional connectivity patterns were examined across experimental conditions to assess differences given by the distinct parameters used. In the alpha-band, TMS-induced left M1 connectivity was associated with a widespread network characterized by right-lateralized (i.e., contralateral to TMS site) communication to sensorimotor regions independent of stimulation features. Beta-band connectivity was more localized, with condition-dependent variations. Monophasic pulses led to stronger connectivity than biphasic pulses in the alpha band, with AP currents inducing the most significant modulation. In biphasic conditions, PA-AP stimulation produced the most substantial connectivity modulation in the alpha-band and the weakest in the beta-band, while AP-PA reversed this pattern. Our findings highlight that TMS parameters can significantly modulate M1 oscillatory dynamics. The selective activation of distinct functional networks could represent a vital source of variability in TMS applications, emphasizing the importance of carefully choosing TMS features and supporting the evidence that motor system interregional communication follows frequency-specific patterns.