Automatic Identification of Axon Bundle Activation for Epiretinal Prosthesis.

Pulkit Tandon,Victoria H Fan,Nandita Bhaskhar,Subhasish Mitra,Lauren Grosberg,Alan M Litke,Pawel Hottowy,E J Chichilnisky,Sasi Madugula,Nishal Shah,Alexander Sher

doi:10.1109/tnsre.2021.3128486

Abstract

Objective:Retinal prostheses must be able to activate cells in a selective way in order to restore high-fidelity vision. However, inadvertent activation of far-away retinal ganglion cells (RGCs) through electrical stimulation of axon bundles can produce irregular and poorly controlled percepts, limiting artificial vision. In this work, we aim to provide an algorithmic solution to the problem of detecting axon bundle activation with a bi-directional epiretinal prostheses.Methods:The algorithm utilizes electrical recordings to determine the stimulation current amplitudes above which axon bundle activation occurs. Bundle activation is defined as the axonal stimulation of RGCs with unknown soma and receptive field locations, typically beyond the electrode array. The method exploits spatiotemporal characteristics of electrically-evoked spikes to overcome the challenge of detecting small axonal spikes.Results:The algorithm was validated using large-scale, single-electrode and short pulse, ex vivo stimulation and recording experiments in macaque retina, by comparing algorithmically and manually identified bundle activation thresholds. For 88% of the electrodes analyzed, the threshold identified by the algorithm was within ±10% of the manually identified threshold, with a correlation coefficient of 0.95.Conclusion:This works presents a simple, accurate and efficient algorithm to detect axon bundle activation in epiretinal prostheses.Significance:The algorithm could be used in a closed-loop manner by a future epiretinal prosthesis to reduce poorly controlled visual percepts associated with bundle activation. Activation of distant cells via axonal stimulation will likely occur in other types of retinal implants and cortical implants, and the method may therefore be broadly applicable.

Highlights

Retinal prostheses are designed to restore partial vision in patients with photoreceptor degenerative diseases such as age-related macular degeneration and retinitis pigmentosa
The multi-electrode arrays (MEAs) is placed on the anterior surface of the retina in order to precisely stimulate retinal ganglion cells (RGCs), ideally with single-cell resolution, to emulate naturally-evoked visual perception [2]–[7]
The results indicate that the algorithm is able to accurately and efficiently detect axon bundle activation while being robust to the selection of the sole hyperparameter

Summary

Introduction

Retinal prostheses are designed to restore partial vision in patients with photoreceptor degenerative diseases such as age-related macular degeneration and retinitis pigmentosa. These devices aim to overcome the loss of photoreceptors by electrically stimulating the downstream retinal circuitry through current injection via multi-electrode arrays (MEAs) [1], [2]. A major challenge in achieving this goal is inadvertent electrical activation of the numerous RGC axons in the nerve fiber layer between the electrodes and RGCs. Activation of axons has been shown to produce irregular arc-shaped phosphenes in patients with epiretinal implants, distorting their artificial visual perception [8]–[10]. Avoiding indiscriminate axon bundle stimulation [4] could drastically improve artificial vision

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Discussion

Conclusion