Part of what makes solving these systems very challenging is the fact that the size of the model tends to be large in comparison with the minimum feature size, resulting in extremely large linear systems, which can only be solved by using iterative algebraic methods. In addition, the material properties and consequently the current and voltage magnitudes involved can vary multiple orders of magnitude, making the convergence of the system harder for iterative solvers. Some of the models we are currently working with involve matrices having over 50 million rows and columns. These systems are being solved using multi-resolution techniques and sparse iterative linear solvers [17, 18].

The configurations analyzed in this article considered an intraocular current return. Characterizing performance for different current return configurations in epiretinal implants is complex. Part of the issue is that biological tissue in the area is arranged in layers, and the range of conductivities involved varies by several orders of magnitude. Further, if the current return electrode is implanted extraocularly and the eye retain movement after surgery, current densities will vary with the position of the eye as well. In general, as the electrode array is pressed into the retina, the current injected tend to penetrate the retinal surface under each of the active electrodes regardless of the current return configurations. The currents injected for each electrode will then seek a path towards the current return, and any asymmetry in the conductive path from the electrode through the tissue to the current return will result in different current density patterns; areas having shadows of lower current densities will appear. This shadow effect is more pronounced with larger and denser electrode arrays, and it is hard to characterize. Some of the current return related factors that affect performance include current return shape, size, material, surrounding tissue structures, and distance.

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Chapter 9

Neurotransmitter Stimulation for Retinal Prosthesis: The Artificial Synapse Chip

Raymond Iezzi and Paul G. Finlayson

Abstract  Retinal prostheses may one day improve the lives of hundreds of thousands of patients with retinitis pigmentosa (RP) or millions of blind patients with advanced age-related macular degeneration (ARMD), depending on their effectiveness. While considerable progress has been made in electrical stimulation of the retina, herein we explore some possible alternatives to electrical stimulation for retinal prosthesis. Since neurotransmitters normally shape visual responses, some groups have been developing visual prostheses based upon the spatially and temporally controlled delivery of neurotransmitters to the retina. This chapter examines the possibilities for utilizing these chemical messengers, as a means to effectively stimulate retinal ganglion cells and produce vision along established visual information channels.

Abbreviations

R. Iezzi (*)

Department of Ophthalmology, Mayo Clinic, 200 First Street, SW, Rochester, MN 55905, USA

e-mail: iezzi.raymond@mayo.edu

9.1  Pathophysiology of Retinal Degeneration

Two major classes of retinal disorders, retinitis pigmentosa and age-related macular degeneration, result in the loss of vision, due to progressive loss of photoreceptors (PR). Retinitis pigmentosa is a term used to designate diverse genetic disorders [15, 34, 38, 64] that vary in their hereditary linkage – autosomal recessive, autosomal dominant, sex linked, mitochondrial or digenic, and in the underlying genetic mutations (see Chap. 3). Although, the onset, rate and type of PR loss vary between these genetic deficits, they all result in a progressive loss of photoreceptors. It also appears that several different factors, including genetic mutations play a role in PR degeneration in ARMD [14, 33, 56, 67] (see also Chap. 3). The diverse etiologies of RP and ARMD suggest that a single treatment will likely not be possible. Animal models of retinitis pigmentosa indicate that although further neurodegeneration and reorganization in the remaining neural retina occurs (see below), much of the rich network within the retina remains intact for extended periods of time. This presents the opportunity to produce visual sensations through the artificial stimulation of the degenerated retina.

9.2  Modes of Interneuronal Communication

Within the Normal Retina

Although, excitatory (glutamate) and inhibitory (GABA and glycine) amino acids are the major neurotransmitter systems in the retina, other transmitters, including acetylcholine, serotonin, dopamine and a variety of neuropeptides shape the visual response (Table 9.1). There is a large diversity of receptors on retinal cell somata and dendrites in the inner and outer plexiform layers (IPL and OPL) and retinal ganglion cell layer (Table 9.2). The outer and inner plexiform layers are near enough to the subretinal and epiretinal surfaces, respectively, for effective activation by application of exogenous agents. In addition, the diversity and location of receptors may allow for differential stimulation of pathways, such as OFF and ON.