Phase-dependent stimulation response is shaped by the brain's transient collective dynamics.

Exogenous stimulation is a promising tool for investigating and altering cognitive processes in the brain, with potential clinical applications. Following experimental observations, we hypothesise that the effect of stimulation crucially depends on the endogenous dynamics of the brain. Our study explores how local and global dynamical properties, like the stimulation phase of regional oscillatory activity and the transient network states, modulate the effect of single pulse stimulation in a large-scale network. Our findings demonstrate that the effect of stimulation strongly depends on the interplay between stimulated phase, transient network state, and brain region. Importantly, we show that stimulation is not only state-dependent but can also induce global state switching. Lastly, predicting the effect of stimulation by using machine learning shows that state-aware measures can increase the performance by up to 40%. Our results suggest that a fine characterisation of the complex brain dynamics in experimental setups is essential for improving the reliability of exogenous stimulation.