Insights from Computational Modelling: Selective Stimulation of Retinal Ganglion Cells

Abstract

AbstractImprovements to the efficacy of retinal neuroprostheses can be achieved by developing more sophisticated neural stimulation strategies to enable selective or differential activation of specific retinal ganglion cells (RGCs). Recent retinal studies have demonstrated the ability to differentially recruit ON and OFF RGCs – the two major information pathways of the retina – using high-frequency electrical stimulation (HFS). However, there remain many unknowns, since this is a relatively unexplored field. For example, can we achieve ON/OFF selectivity over a wide range of stimulus frequencies and amplitudes? Furthermore, existing demonstrations of HFS efficacy in retinal prostheses have been based on epiretinal placement of electrodes. Other clinically popular techniques include subretinal or suprachoroidal placement, where electrodes are located at the photoreceptor layer or in the suprachoroidal space, respectively, and these locations are quite distant from the RGC layer. Would HFS-based differential activation work from these locations? In this chapter, we conducted in silico investigations to explore the generalizability of HFS to differentially active ON and OFF RGCs. Computational models are particularly well suited for these investigations. The electric field can be accurately described by mathematical formulations, and simulated neurons can be “probed” at resolutions well beyond those achievable by today’s state-of-the-art experimental techniques.