Learning to See via Epiretinal Implant Stimulation in silico with Model-Based Deep Reinforcement Learning 文章

ArXiv CS.CV2026-06-03NEWSen作者: Jacob Lavoie, Marwan Besrour, William Lemaire, Jean Rouat, R\'ejean Fontaine, Eric Plourde

摘要

arXiv:2606.03118v1 Announce Type: cross Abstract: Objective: Diseases such as age-related macular degeneration and retinitis pigmentosa cause the degradation of the photoreceptor layer. One approach to restore vision is to electrically stimulate the surviving retinal ganglion cells with a microelectrode array such as epiretinal implants. Epiretinal implants are known to generate visible anisotropic shapes elongated along the axon fascicles of neighboring retinal ganglion cells. Recent work has demonstrated that to obtain isotropic pixel-like shapes, it is possible to map axon fascicles and avoid stimulating them by inactivating electrodes or lowering stimulation current levels. Avoiding axon fascicle stimulation aims to remove brushstroke-like shapes in favor of a more reduced set of pixel-like shapes.