Three-dimensional electro-neural interfaces for high-resolution subretinal prostheses

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Abstract/Contents

Abstract
Therapeutic applications of electro-neural interfaces in the central and peripheral nervous system are rapidly expanding. Sensory prostheses, such as cochlear and retinal implants, restore perception from diseased neural circuits by electrically stimulating preserved neurons, thereby bypassing malfunctioning biological transducers. At Stanford, our group has developed a photovoltaic retinal prosthesis, wherein silicon photodiodes in each pixel of a subretinal array convert pulsed, near-infrared illumination projected from video goggles into electric current to stimulate the degenerate retina. Recent clinical trials of this technology in patients blinded by age-related macular degeneration (AMD) confirm that the spatial resolution of prosthetic vision can reach the sampling density limit with 100 um pixels, corresponding to the highest reported visual acuity of any visual prosthesis - in the range of 20/460 to 20/550. For practical use in patients with AMD, prosthetic vision must exceed the legal blindness limit (20/200), which requires denser stimulating arrays with pixels < 55 um. Miniaturization of pixels for photovoltaic retinal stimulation is impeded by many design challenges, most notably the limited penetration depth of the stimulating electric field, reduced charge-injection capacity within safe operating limits, and loss of photosensitive area necessary for sufficient light-to-\current conversion. Natural migration of retinal tissue into cavities in the subretinal space enables the use of three-dimensional (3-D) electrode configurations to overcome these limitations. Efficient design of such structures, however, requires models that replicate the device physics and network-mediated stimulation. This work presents the evolution of our photovoltaic retinal prosthesis into a 3-D electronic stimulator capable of safely and efficiently restoring vision beyond the legal blindness limit, and up to 20/80 equivalent visual acuity. In-vivo trials with our high-density planar array configuration show 40 um and 55 um arrays can stimulate the degenerate rat retina, but only achieve maximum grating acuity of 20/190 with 55 um pixels. To guide development in 3-D, we will describe proper electric boundary conditions for electrode-electrolyte interfaces in steady state, validate a model of network-mediated stimulation thresholds, and utilize an equivalent circuit model for our photovoltaic pixels. A 3-D prosthesis with pillar electrodes induces retinal migration to reduce the separation distance between the electrode surface and target inner-nuclear layer (INL), but does not adequately reduce stimulation thresholds in-vivo due to spherical expansion of electric field. To solve this issue, we introduce the honeycomb electrode configuration to decouple field penetration depth from pixel size, increase stimulation efficacy, and eliminate pixel cross-talk for pixel size down to 20 um. Finally, we conclude by describing our efforts to further leverage retinal migration to create single-cell interfaces for prosthetic vision.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2019; ©2019
Publication date 2019; 2019
Issuance monographic
Language English

Creators/Contributors

Author Flores, Thomas Anthony
Degree supervisor Palanker, Daniel
Degree supervisor Reis, David A, 1970-
Thesis advisor Palanker, Daniel
Thesis advisor Reis, David A, 1970-
Thesis advisor Melosh, Nicholas A
Degree committee member Melosh, Nicholas A
Associated with Stanford University, Department of Applied Physics.

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Thomas Flores.
Note Submitted to the Department of Applied Physics.
Thesis Thesis Ph.D. Stanford University 2019.
Location electronic resource

Access conditions

Copyright
© 2019 by Thomas Anthony Flores
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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