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Closed-loop Optimization of Retinal Ganglion Cell Responses to Epiretinal Stimulation: A Computational Study

机译:视网膜神经节细胞对闭锁刺激的闭环优化:计算研究

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Retinal prostheses improve vision for patients with retinal degeneration. However, the shape recognition ability of retinal prostheses users is limited due to the low visual resolution of these devices. Off-target retinal ganglion cell (RGC) activation is an important contributing factor to the low stimulation precision. Previous research has shown RGC spatial activity and perception of shapes by users can be difficult to predict due to the complexity of retina structure and electrode-retina interactions. In this study we demonstrate a method to iteratively search for optimal stimulation parameters that create focal RGC activation in silico. Our findings indicate that stimulation parameters can be customized to each electrode in a closed-loop manner. This approach can potentially eliminate the time-consuming process of searching a broad range of parameters for optimal stimulation outcome and provide more control over personalized fitting of retinal implants.
机译:视网膜假体改善视网膜变性患者的视觉。 然而,由于这些装置的视觉分辨率低,视网膜假体用户的形状识别能力受到限制。 偏离目标视网膜神经节细胞(RGC)活化是低刺激精度的重要贡献因素。 以前的研究表明,由于视网膜结构和电极 - 视网膜相互作用的复杂性,用户难以预测对RGC空间活动和对形状的感知。 在这项研究中,我们演示了一种方法来迭代地搜索在硅中产生焦点RGC激活的最佳刺激参数。 我们的研究结果表明,刺激参数可以以闭环方式定制到每个电极。 这种方法可能会消除搜索广泛参数以获得最佳刺激结果的耗时过程,并提供更多控制视网膜植入物的个性化配件。

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