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Visual neuroprostheses are the only FDA-approved technology for the treatmentof retinal degenerative blindness. Although recent work has demonstrated asystematic relationship between electrode location and the shape of theelicited visual percept, this knowledge has yet to be incorporated into retinalprosthesis design, where electrodes are typically arranged on either arectangular or hexagonal grid. Here we optimize the intraocular placement ofepiretinal electrodes using dictionary learning. Importantly, the optimizationprocess is informed by a previously established and psychophysically validatedmodel of simulated prosthetic vision. We systematically evaluate threedifferent electrode placement strategies across a wide range of possiblephosphene shapes and recommend electrode arrangements that maximize visualsubfield coverage. In the near future, our work may guide the prototyping ofnext-generation neuroprostheses.

Greedy Optimization of Electrode Arrangement for Epiretinal Prostheses