Promising experimental findings over the last two decades have sparked a strong interest in using electromagnetic brain stimulation in clinical practice to treat a variety of neurophysiological disorders, such as depression, Alzheimer’s and Parkinson. One strategy is to use periodic waveforms to engage brain oscillations - endogenous non-linear rhythms caused by the synchronous firing of neurons – to promote and hopefully upregulate neural communication. While relatively well characterized at the scale of individual cells, the effect of varying electromagnetic fields on populations and large-scale brain dynamics remains poorly understood. Here we have combined computational and mathematical approaches to understand how brain state fluctuations influence the response of the thalamo-cortical system to periodic stimulation. Specifically, we have examined how rest and task-engaged states – which correspond to different oscillatory regimes - shape the susceptibility of cortical populations to entrainment by exogenous signals. Our analysis shows that the different responses to stimulation observed experimentally in different brain states can be explained by a passage through a bifurcation combined with stochastic resonance - a mechanism by which irregular fluctuations amplify the response of a nonlinear system to weak signals. Indeed, our findings suggest that modulating brain oscillations is best achieved in states of low endogenous rhythmic activity and that irregular state-dependent fluctuations in thalamic inputs control endogenous oscillatory activity. Taken together, our results show that internal control over attractor states shapes the sensitivity of neural populations to stimulation.