Abstract: We study the spatiotemporal dynamics of activation in chains of inhibition-stabilized neural networks with nearest-neighbor coupling. We identify the regions of parameters where the network behavior is stable with respect to corrugation perturbations, allowing us to investigate the dynamical regimes associated with these regions. The neuronal excitation generated by local stimuli in such networks propagate across space and time, forming spatiotemporal waves that affect the excitation generated by the inputs separated spatially and temporally. These interactions form characteristic interference patterns manifested as intrinsic preferences of the network for specific spatial and temporal frequencies of luminance modulations in the stimulus, and for specific stimulus velocities. Notably, the interference leads to characteristic contextual ("lateral") interactions between the stimuli. Previously such interactions were attributed to distinct specialized mechanisms.