Among non-coding RNAs, microRNAs are pivotal post-transcriptional regulators of gene expression in higher eukaryotes. Through a titration-based mechanism of interaction with their target RNAs, microRNAs can mediate a weak but pervasive form of RNA cross-regulation, as different endogenous RNAs can be effectively coupled by competing for microRNA binding (a phenomenon now known as “crosstalk”). Mathematical modeling has been proven of great help in unraveling many features of these competing endogenous RNA (ceRNA) interactions. However, although many studies have been devoted to the steady-state properties of this indirect regulatory layer, little is known about how the information encoded in frequency, amplitude, duration, and other features of regulatory signals can affect the resulting ceRNA crosstalk picture and hence the overall patterns of gene expression. Here, we focus on such dynamical aspects, with a special emphasis on the encoding and decoding of time-dependent signals.