We have previously shown that random channel and synaptic noise improve the ability of a biologically realistic, GENESIS-based computational model of the Hermissenda eye to encode light intensity. In this paper we explore mechanisms for noise-induced improvement by examining contextual spike-timing relationships among neurons in the photoreceptor network. In other systems, synaptically connected pairs of spiking cells can develop phase-locked spike-timing relationships at particular, well-defined frequencies. Consequently, domains of stability (DOS) emerge in which an increase in the frequency of inhibitory post-synaptic potentials can paradoxically increase, rather than decrease, the firing rate of the post-synaptic cell. We have extended this analysis to examine DOS as a function of noise amplitude in the exclusively inhibitory Hermissenda photoreceptor network. In noise-free simulations, DOS emerge at particular firing frequencies of type-B and type-A photoreceptors, thus producing a nonmonotonic relationship between their firing rates and light intensity. By contrast, in the noise-added conditions, an increase in noise amplitude leads to an increase in the variance of the inter-spike interval (ISI) distribution for a given cell; in turn, this blocks the emergence of phase locking and DOS. These noise-induced changes enable the eye to better perform one of its basic tasks: encoding light intensity. This effect is independent of stochastic resonance, which is often used to describe peri-threshold stimuli. The constructive role of noise in biological signal processing has implications both for understanding the dynamics of the nervous system and for the design of neural interface devices.