Probing visual computations and electrical stimulation in the central macaque retina for high fidelity vision restoration

项目摘要/摘要 光感受器退化导致的失明是导致残疾的主要原因。主要治疗方案 是使用视网膜前假体，它直接激活视网膜神经节细胞(RGC)，发送人工视觉 向大脑发出信号。然而，目前视网膜前假体的视力恢复是有限的，因为 粗粒度刺激，无法复制自然的、光诱发的RGC激活模式。在自然视野中， 大约20种功能不同的RGC类型将视觉世界的独特表示传递给大脑 通过协调和精确的特定细胞类型的活动模式。现代植入物不会产生 高视力的部分原因是，由于粗糙和非特异性，它们无法引起自然的RGC反应 刺激。我的研究目标是确定通过以下方式在中央视网膜恢复视力的效果如何 分析灵长类视网膜节细胞对视觉和电刺激的反应。 为了实现这一目标，我将首先在猕猴的中央视网膜进行体外实验 具有视觉和电刺激，同时使用高密度多电极阵列进行记录。在识别出 主要的功能不同的细胞类型，然后我们将描述它们的时空光响应特性 并确定它们与外围视网膜中相同类型的细胞有何不同。我也会比较一下 来自自然图像的特征由主要类型的中央和外围RGC表示。下一步，到 确定中枢RGC的电激活程度，我将确定RGC的电感受野 并量化每种类型的视网膜节细胞可被选择性刺激的程度。到时候我们会的 检测在不激活轴突的情况下，中央视网膜主要类型的RGC被激活的程度 捆绑在一起。为了更好地接触中央视网膜的RGC，我将测试是否移除内部 限制膜降低了刺激阈值，增强了选择性激活。在以下情况下 单电极刺激不能选择性激活视网膜节细胞，我将测试三电极是否 刺激可以通过电流转向更好地将电场集中在感兴趣的细胞上，以增强选择性 激活。最后，为了评估未来靶向植入物恢复高分辨率视力的效果 中央视网膜，我们将通过聚合视觉和电响应特性来开发一个模拟 许多数据集并执行图像重建分析以量化图像的结构细节，从而可以 被察觉到。

Project Summary/Abstract Blindness resulting from photoreceptor degeneration is a leading cause of disability. A primary treatment option is the use of epiretinal prostheses, which directly activate retinal ganglion cells (RGCs), sending artificial visual signals to the brain. However, vision restoration with current-day epiretinal prostheses is limited, due to the coarse-grained stimulation that fails to replicate natural, light-evoked RGC activation patterns. In natural vision, ~20 functionally-distinct RGC types communicate unique representations of the visual world to the brain through coordinated and precise cell type-specific patterns of activity. Modern implants don’t produce high-acuity vision in part because they fail to elicit naturalistic RGC responses, due to coarse and nonspecific stimulation. The goal of my research is to determine how well vision can be restored in the central retina by analyzing the responses of primate RGCs to visual and electrical stimulation. To accomplish this goal, I will first conduct ex vivo experiments in the central retina of the macaque monkey with visual and electrical stimulation while recording with a high-density multi-electrode array. After identifying the major functionally-distinct cell types, we will then characterize their spatiotemporal light response properties and determine how they differ from cells of the same types in the peripheral retina. I will also compare how well features from natural images are represented by central and peripheral RGCs of the major types. Next, to determine how well central RGCs can be electrically activated, I will determine the electrical receptive fields for each cell as well as quantify the extent to which RGCs of each type can be stimulated selectively. We will then test the degree to which RGCs of major types in the central retina can be activated without activating axon bundles. To achieve better electrical access to RGCs in the central retina, I will test whether removing the inner limiting membrane decreases stimulation thresholds and enhances selective activation. In cases in which selective activation of RGCs is unattainable with single-electrode stimulation, I will test whether tri-electrode stimulation can better focus the electric field on a cell of interest through current steering to enhance selective activation. Finally, to estimate how well high-resolution vision can be restored with a future implant targeting the central retina, we will develop a simulation by aggregating the visual and electrical response properties across many data sets and perform image reconstruction analyses to quantify the structural details of images that can be perceived.