Greedy Optimization of Electrode Arrangement for Epiretinal Prostheses

TL;DR

This paper introduces a novel method for optimizing electrode placement in epiretinal prostheses using dictionary learning and a validated visual model, aiming to improve visual coverage for retinal blindness patients.

Contribution

It presents a new optimization approach for electrode arrangement based on a psychophysically validated model, enhancing prosthetic visual field coverage.

Findings

Optimized electrode arrangements outperform traditional grids.

Systematic evaluation across diverse phosphene shapes.

Recommendations for next-generation neuroprosthesis design.

Abstract

Visual neuroprostheses are the only FDA-approved technology for the treatment of retinal degenerative blindness. Although recent work has demonstrated a systematic relationship between electrode location and the shape of the elicited visual percept, this knowledge has yet to be incorporated into retinal prosthesis design, where electrodes are typically arranged on either a rectangular or hexagonal grid. Here we optimize the intraocular placement of epiretinal electrodes using dictionary learning. Importantly, the optimization process is informed by a previously established and psychophysically validated model of simulated prosthetic vision. We systematically evaluate three different electrode placement strategies across a wide range of possible phosphene shapes and recommend electrode arrangements that maximize visual subfield coverage. In the near future, our work may guide the prototyping of next-generation neuroprostheses.