Computational neuroscience can provide powerful insights into the design and optimization of neuroprosthetic devices. This study combines the advantages of two numerical approaches to develop a predictive model of electrical stimulation of the retinal network for visual prostheses. A continuum bidomain formulation was used to model neurons in the retinal inner nuclear layer, which provide synaptic inputs to a population of discrete morphologically-realistic retinal ganglion cells. The ability to model bulk tissue activation for selective layers in the retina, as well as dendritic processing in ganglion cells provides a powerful simulation tool to test and optimize electrical stimulation strategies for future retinal prosthesis devices.
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