  Retinal implants are a promising treatment option for degenerative retinal
disease. While numerous models have been developed to simulate the appearance
of elicited visual percepts ("phosphenes"), these models often either focus
solely on spatial characteristics or inadequately capture the complex temporal
dynamics observed in clinical trials, which vary heavily across implant
technologies, subjects, and stimulus conditions. Here we introduce two
computational models designed to accurately predict phosphene fading and
persistence under varying stimulus conditions, cross-validated on behavioral
data reported by nine users of the Argus II Retinal Prosthesis System. Both
models segment the time course of phosphene perception into discrete intervals,
decomposing phosphene fading and persistence into either sinusoidal or
exponential components. Our spectral model demonstrates state-of-the-art
predictions of phosphene intensity over time (r = 0.7 across all participants).
Overall, this study lays the groundwork for enhancing prosthetic vision by
improving our understanding of phosphene temporal dynamics.
