Statistical estimation of visual features in retinal circuitry

描述（由申请人提供）：这个项目的总体目标是了解视网膜计算是如何根据视觉环境的结构而改变的。人们早就知道视网膜神经节细胞（RGCs）的敏感性依赖于最近的视觉输入。这些敏感性的适应性变化表现出显著的灵活性；一些rgc适应忽略视觉世界中可预测的组件，而倾向于编码不可预测的组件。这种策略被认为可以最大限度地将信息传递给高级大脑。然而，我们实验室最近的研究表明，一些RGCs使用先前的视觉刺激来预测未来的输入。对这些rgc的高对比度输入，比如一个移动的物体，增加了它们的灵敏度，从而编码了物体可能的未来位置。然而，rgc是否对亮度和对比度以外的视觉环境特性敏感，或者，更简单地说，视网膜是否保持对视觉世界更复杂特征的预测，这仍然是未知的。这项工作的第一个目标是了解视网膜表现出预测敏感性的视觉特征类别。第二个目标是利用视网膜的可操控性来探索预测背后的神经机制，这种计算被认为是在整个大脑中进行的。除了提高我们对视网膜的基本理解，这些结果将有直接的应用。视网膜假体装置有望为那些患有光感受器变性疾病的人带来实质性的视力恢复，这种疾病影响着200多万美国人。由于预测敏化的计算很容易在数字电路中实现，本研究将为视网膜假体处理元件的设计提供基础的科学见解和计算模型。

DESCRIPTION (provided by applicant): The overall goal of this project is to understand how retinal computations are modified in response to the structure of the visual environment. It has long been known that the sensitivity of retinal ganglion cells (RGCs) is depen- dent on recent visual input. These adaptive changes in sensitivity show remarkable flexibility; some RGCs adapt to ignore predictable components of the visual world in favor of encoding what is unexpected. This strategy is thought to maximize the amount of information transmitted to the higher brain. Recent work from our lab, how- ever, suggests that some RGCs use previous visual stimuli to predict future input. High-contrast input to these RGCs, such as a moving object, increases their sensitivity, thereby encoding the object's likely future location. It remais unknown, however, whether RGCs sensitize to properties of the visual environment beyond luminance and contrast, or, more simply, whether the retina maintains predictions about more complex features of the visual world. The first goal of this work is to understand the class of visual features to which the retina exhibits predictive sensitization. A second goal is to take advantage of the tractability of the retina to explore the neural mechanisms underlying prediction, a computation thought to be performed throughout the brain. In addition to improving our fundamental understanding of the retina, these results will have direct application. Retinal prosthetic devices hold the promise of substantially restored vision for those suffering from photoreceptor degeneration diseases, which affect more than two million Americans. As the computation of predictive sensitization is easily implemented in digital circuits, this research wil provide basic scientific insight and computational models to inform in the design of processing elements in retinal prosthetics.