We will describe how an idealized form of synchronized firing in a network of integrate-and-fire neurons can be represented in terms of the Watts model for a network cascade. Both mean-field and tree-like (branching process) approximations are employed to characterize the probability that a particular statistical network model will sustain the idealized synchronous firing pattern. We describe some adaptations to these widely used analytical approximations that are indicated for this neuroscience application.