Intracortical multiunit implant to create vision for blinds : Integration and validation

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The number of legally blind Americans exceeds 1 million with around 10% of them having no perception of light whatsoever. This project is intended to answer the fundamental questions of creating vision for blinds using direct electrical stimulation for large scale visual prostheses. Several research groups have opted to design visual prostheses. Electrical stimulation of the retina or of the optic nerve can be used to reverse the loss of sight induced by outer retinal degeneration caused by diseases the likes of retinitis pigmentosa or even by age-related macular degeneration. These techniques, however, are not helpful for the case of diseases affecting the inner or whole thickness retina or the optic nerve, nor as well for the case of eye loss. Such diseases, nonetheless, can be reversed by using intracortical visual prostheses. Matrices of electrodes implanted in the visual cortex are used to create a visual image consisting of an array of visual perceptions, or phosphenes. The starting point of this proposed project is a well-established preliminary design which includes ASICs that have already been fabricated and tested on conventional electronic test benches. The ongoing work tackles four different and complementary facets of the problem, namely 1) Modeling, stimulation techniques and parameters, 2) implant implementation and optimization, including electrode matrices fabrication and device encapsulation, 3) an external controller, including image acquisition and processing, and 4) in-vivo implantation in chronic animal and testing. We wish to provide sets of parameters for efficient, safe and effective chronic stimulation of the cortex. As the project involves actual implantation of devices, one important objective is to define reliable surgical techniques and optimal device physical characteristics and to acquire know-how regarding miniaturization and assembly. We also aim at maximizing the exploitation of the device by using advanced acquisition and processing techniques, which involve the design and integration of image sensors, processing algorithms and hardware on efficient and low power devices.