 This paper studies the spread of oscillations in neural networks composed of excitatory and inhibitory neurons. The authors propose a model for the spread of these oscillations based on the structural connectivity of the network and the firing rates of the nodes. They then use this model to identify conditions under which the spread of oscillations can be controlled or optimized. Finally, they demonstrate their findings with numerical simulations. This article was authored by Ahmed Aliboy, Federico Kelly, Fabio Pascalletti, and others.