A biologically plausible phosphene simulator for the optimization of visual cortical prostheses
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2022-07-27
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en
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Abstract
Blindness affects millions of people around the world, and is expected to become an increasingly prevalent
condition in the years to come. For some blind individuals, cortical visual prosthetics provide a promising
solution to restoring vision, by converting camera input to electrical stimulation of the cortex to bypass part of
the impaired visual system. Electrical stimulation in the primary visual cortex has been found to produce dots of
light in the subject’s vision, called phosphenes. By evoking phosphenes in the right patterns, prosthesis wearers
can be shown a representation of the outside world. As this representation has a limited resolution, visual
prosthetics will need to rely on intelligent image processing algorithms that filter meaningful information
from the visual surroundings. To optimise these processing strategies, non-invasive simulated prosthetic
vision (SPV) can be used with sighted subjects or computational models. However, most SPV studies use highly
simplified models of phosphene generation, limiting their validity for real-life applications. In this project, we
developed a fast and fully differentiable phosphene simulator that transforms electrode stimulation patterns
into biologically plausible representations of what the prosthesis wearer is expected to see. To achieve this,
the simulator includes several computational models that take into account the visuotopic organisation of
the cortex and the spread of activation in cortical tissue to determine phosphene locations and sizes. Several
stimulation parameters are taken into account to model phosphene brightness and threshold values. Temporal
dynamics are incorporated to allow for a realistic simulation over time. All models are parameterised and can
be conveniently adapted to model empirical observations. Our results show the usability of the simulator for
both computational applications as well as behavioural experiments.
Keywords: Phosphene vision, bionic vision, visual prosthesis, blindness, computational modelling, deep
learning, neurotechnology, cortical stimulation
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Faculteit der Sociale Wetenschappen