Abstract
Developing visual prostheses that target inner brain structures along the visual pathway represent a new hope for patients with completely damaged early visual pathway sites. One of the major challenges in the development of subcortical and cortical visual prostheses is tuning electrical stimulation that could optimally induce desired visual percepts. In this paper, we propose a Kalman filter-based strategy that could be used to identify electrical stimulation patterns that mimic a specific visual input for thalamic visual prostheses. We demonstrate the performance of the proposed strategy using a population of lateral geniculate nucleus neurons modeled using an adapted generalized non-linear model. A mean correlation of 0.69 is obtained between visually evoked and electrically evoked responses-driven using the proposed strategy-for an optimal electrode-placement setup. In addition, we demonstrate the performance for a random electrode-placement setup in which a mean correlation of 0.26 is obtained. For this latter setup, our analysis reveals an inversely proportional relationship between the obtained correlation and the distance between each neuron and the nearest electrode. The proposed strategy could be thus utilized to tune and enhance the performance of thalamic visual prostheses as well as other prosthesis systems.
Published Version
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