Optimization of Electrical Stimulation for a High-Fidelity Artificial Retina

Abstract

Retinal prostheses aim to restore visual perception in patients blinded by photoreceptor degeneration, by stimulating surviving retinal ganglion cells (RGCs), causing them to send artificial visual signals to the brain. Present-day devices produce limited vision, in part due to indiscriminate and simultaneous activation of many RGCs of different types that normally signal asynchronously. To improve artificial vision, we propose a closed-loop, cellular-resolution device that automatically identifies the types and properties of nearby RGCs, calibrates its stimulation to produce a dictionary of achievable RGC activity patterns, and then uses this dictionary to optimize stimulation patterns based on the incoming visual image. To test this concept, we use a high-density multi-electrode array as a lab prototype, and deliver a rapid sequence of electrical stimuli from the dictionary, progressively assembling a visual image within the visual integration time of the brain. Greedily minimizing the error between the visual stimulus and a linear reconstruction (as a surrogate for perception) yields a realtime algorithm with an efficiency of 96% relative to optimum. This framework also provides insights for developing efficient hardware. For example, using only the most effective 50% of electrodes minimally affects performance, suggesting that an adaptive device configured using measured properties of the patient's retina may permit efficiency with accuracy.

Focal Electrical Stimulation of Human Retinal Ganglion Cells for Vision Restoration

“…To assess the potential application of the above findings for restoration of vision, a newly developed stimulation algorithm and assessment metric were used [11]. To produce high-fidelity artificial vision with a retinal implant, precise RGC activity evoked by individual electrodes must be combined across the array to reproduce the rich spatiotemporal response patterns evoked by natural visual stimuli.…”

“…This suggests that stimulation of earlier retinal neurons -specifically, bipolar cells --may be more effective for sight restoration [3,4], despite the limited scientific understanding of bipolar cells and the difficulties of recording from them to validate stimulation. However, extensive experiments in isolated macaque monkey retina have demonstrated that RGCs can be activated precisely by direct electrical stimulation at very low current levels, in many cases with single-cell, single-spike, cell-type resolution [5][6][7][8][9], with the potential to deliver high-quality artificial vision [10,11]. Because electrical stimulation and recording have never been performed simultaneously in the human retina, it remains unclear whether these promising findings in macaque retina can be used to develop high-resolution retinal implants for vision restoration.…”

Reconstruction of natural images from responses of primate retinal ganglion cells

“…Using reconstruction to understand the signals transmitted by neurons may be increasingly important in future efforts to read and write neural codes using brain-machine interfaces (BMIs). In the retina, certain types of blindness can be treated with implants that use electrical stimulation to activate the remaining retinal neurons (Goetz & Palanker, 2016), and the visual messages described in the present work can help guide the selection of optimal stimulation patterns (Goetz & Palanker, 2016;Golden et al, 2019;Shah et al, 2019). Reconstruction can also be used to compare the evoked visual representation with the representation produced by natural neural activity.…”

Stimulation Strategies for Improving the Resolution of Retinal Prostheses

“…Sequential stimulation was performed by Shah et al (2019), in which each electrode was stimulated in series, at a rate expected to be faster than the integration time of visual perception. They first created a response library by recording the RGC responses to individual electrode stimulation.…”