DOI: https://doi.org/10.29363/nanoge.nias.2021.015
Publication date: 13th September 2021
Retinal prostheses seek to create artificial vision by stimulating surviving inner retinal neurons of patients with profound vision impairment. Notwithstanding tremendous research efforts, the performance of all implants tested to date have remained rudimentary, incapable of overcoming the threshold for legal blindness. To maximize the perceptual efficacy of a retinal prostheses, a device must be capable of controlling retinal ganglion cells (RGCs), the output cells of the retina, with greater spatiotemporal precision. Most (if not all) studies of high resolution retinal stimulation were either derived from non-primate species or the peripheral primate retina, despite the uniqueness and high acuity of the central primate retina’s foveal region. In addressing this shortcoming, we are developing a more clinically relevant computational model capable of generating anatomically accurate RGC populations within the central human retina. The critical improvements of this model lie in its capacity to uphold location-dependent characteristics such as RGC density and dendritic diameter, whilst incorporating anatomically accurate features such as axon projection and three-dimensional RGC layering, features often forgone in favour of reduced computational complexity. Our model of epiretinal stimulation produced RGC excitation in the shape of wedges, halos, and elongated streaks, analogous to the perplexing and non-trivial percepts reported in clinical trials. Following this, multiple RGC populations across the central retina were stimulated to compare and assess neurostimulation configurations based on their ability to improve perceptual efficacy. Finally, these results were used to determine an upper-bound on artificial visual acuity achievable with retinal implants using today’s technologies. Our model and results could provide the means and new insights towards the development of neurostimulation protocols for next-generation, high-resolution retinal protheses.
This work is funded in part by National Health and Medical Research Council grants (APP1087224 and APP1188414).
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