CRCNS: Complete functional characterization of a population of retinal ganglion c

描述(申请人提供)：拟议研究的目标是了解整个视网膜神经元群体如何将视觉信息传递到大脑，视网膜网络活动如何从其元素中产生，以及网络功能如何服务于有机体的需求。到目前为止，在这些基本问题上的进展一直受到以下方面的限制：(A)直接通过实验获得完整的神经元群体的活动，以及(B)使我们能够理解完整的神经元群体如何相互作用来代表信息的多神经元反应模型。我们最近开发了从分离的猕猴视网膜中记录完整的视网膜神经节细胞(RGC)的技术，以及对这些反应进行建模的方法，这为理解整个网络如何编码视觉场景提供了巨大的希望。我们将结合这些强大的新技术来解决以下目标：(1)感觉输入、非线性、噪声和相互连接如何结合在一起，以确定RGC的大型集合中的详细尖峰模式？(2)基于RGC的集合放电模式，视觉刺激如何有效地被解码，以及刺激的辨别力如何依赖于尖峰序列的精细时间结构？(3)视觉刺激的哪些方面通过RGC集合活动最有效地编码，以及这些在多大程度上反映了人类的感知能力和自然视觉环境的结构？ 相关性：由于视网膜神经节细胞将所有视觉信息传输到大脑，了解它们如何共同编码视觉信息是理解视觉、健康和疾病的一个基本方面。这项拟议的工作将首次使我们能够在一个单一的框架内解释完整细胞群体的尖峰序列，该框架结合了它们的响应特性、生理噪声源和网络连接。其中每一项最终都有助于视觉系统的健康功能，而每一项的破坏将以拟议的方法可以预测和理解的方式降低由RGC群体传输到大脑的视觉信号。此外，目前正在人体上测试的替代视网膜功能的假体设备，最终将需要重现正常的尖峰活动模式，才能向大脑提供自然的视觉信号。因此，我们最近利用多电极阵列的电刺激进行假体设计的实验将从拟议的工作中受益匪浅。总而言之，了解整个视网膜网络如何编码棘波序列中的视觉场景，是了解健康的视觉系统和设计针对疾病损害的视网膜的假体治疗的关键要素。

DESCRIPTION (provided by applicant): The objective of the proposed research is to understand how entire populations of retinal neurons convey visual information to the brain, how the activity of the retinal network activity emerges from its elements, and how network function serves the needs of the organism. Until now, progress on these basic problems has been limited by lack of: (a) direct experimental access to the activity of a complete population of neurons, and (b) models of multineuronal responses that allow us to understand how complete populations of neurons interact to represent information. We have recently developed techniques for recording from complete populations of retinal ganglion cells (RGCs) in isolated macaque monkey retina, and approaches to modeling these responses that provide great promise in understanding how the entire network encodes the visual scene. We will combine these powerful new techniques to address the following aims: (1) How do sensory inputs, nonlinearities, noise, and inter-connections combine to determine the detailed spiking patterns in large ensembles of RGCs? (2) How effectively can visual stimuli be decoded based on the ensemble firing patterns of RGCs, and how does stimulus discriminability depend on the fine temporal structure of spike trains? (3) What aspects of the visual stimulus are most effectively encoded by ensemble RGC activity, and to what degree do these reflect the perceptual abilities of humans and the structure of the natural visual environment? Relevance: Because retinal ganglion cells transmit all visual information to the brain, understanding how they collectively encode visual information is a fundamental aspect of understanding vision, in health and in disease. The proposed work will for the first time allow us to explain the spike trains of a complete population of cells in a single framework that incorporates their response properties, sources of physiological noise, and network connectivity. Each of these ultimately contribute to the healthy function of the visual system, while disruption of each will degrade the visual signals transmitted by the RGC population to the brain in ways that may be predicted and understood with the proposed approach. Furthermore, prosthetic devices to replace retinal function, which are now being tested in humans, will eventually need to reproduce the normal patterns of spiking activity in order to provide natural visual signals to the brain. Therefore, our recent experiments using electrical stimulation with multi-electrode arrays for prosthetic design will benefit greatly from the proposed work. In summary, knowing how the entire retinal network encodes the visual scene in spike trains is a key element in understanding the healthy visual system and designing prosthetic treatments for retinas damaged by disease.