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Ione Fine, Geoffrey M. Boynton, Arup Roy, Robert Jay Greenberg; Pulse trains to percepts: Developing quantitative models of the percepts produced by sight recovery technologies. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5329.
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© ARVO (1962-2015); The Authors (2016-present)
An extraordinary variety of sight recovery therapies are either about to begin clinical trials, have begun clinical trials, or are currently being implanted in patients. For sight recovery technologies which use artificial stimulation of the retina to elicit percepts (optogenetics, small molecule photoswitches, and electrical prostheses) the interplay between the stimulating technology and the underlying neurophysiology is thought to result in significant distortions of the perceptual experience. However, as yet we do not have quantitative models that can predict the perceptual experience produced by these implants. Here we describe a quantitative model that can predict patient percepts for an epiretinal implant, based on a series of psychophysical studies examining the brightness, size and shape of patient percepts as a function of the pattern of electrical stimulation.
Our spatio-temporal model of the effects of electrical stimulation begins with transforming the pulse train on each electrode into a spatiotemporal representation of current on the retina, based on the height of the array from the retinal surface and a model of the spread of current from a metal disc in a semi-infinite medium. Retinal current is then passed through a perceptual sensitivity model that predicts neuronal activity over time and space based on a model that (1) describes sensitivity as a cascade of nonlinear transformations of the spatiotemporal pattern of stimulation, (2) assumes simultaneous stimulation of both and ON- and OFF-pathways, and (3) includes axonal stimulation that falls off as a function of distance from the ganglion cell body.
This model can successfully predict the percepts produced by epiretinal stimulation over both time and space in current human patients.
This model is also capable of generating predictions about the likely perceptual quality of future implants. These predictions can (1) provide the basis for better stimulation protocols, (2) provide insights into what aspects of the implant are likely to be limiting perceptual performance, and (3) provide patients and reimbursement agencies with clearer insights into what sort of perceptual improvements these implants are likely to provide in the real world.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.
A simulation of the Seattle space needle as viewed with an epiretinal prosthetic device.
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