Circuit mechanisms for encoding naturalistic motion in the mammalian retina

摘要 运动检测是视觉系统的一项基本计算，始于视网膜。在 哺乳动物的视网膜，移动物体的方向是由方向选择电路计算的。 该回路的视网膜输出由方向选择性神经节细胞(DSGCs)提供。这些 细胞被其首选方向的运动强烈激活，但被其首选方向的运动所抑制 相反的方向，也就是“零”。他们将运动的方向报告给高级大脑中心 进一步的视觉处理，它们有助于控制眼球运动和意识 幻象。除了方向选择性外，DSGC响应还显著地受 视觉环境的上下文。这些与上下文相关的属性是运动的核心 在自然环境中由DSGCs进行编码。这项提议旨在解决两个重要的问题 与自然刺激相关的上下文相关的回路功能。第一个是噪音 恢复力。自然场景中的运动往往伴随着其他视觉特征的存在 或者“噪音”。目标1将确定保持方向选择性的电路机制 存在背景噪音。第二个功能是运动对比度编码。由于 持续的身体和眼睛运动，视网膜上的视觉输入是全局图像的组合 移动对象与其背景之间的平移和相对运动。DSGC响应为 与全局运动相比，不仅具有方向选择性，而且对相对运动也很敏感。目标 2将确定赋予DSGCs对运动对比度敏感性的电路图案。在目标3中，我们 我将把实验定义的电路主题的算法功能与编码联系起来 DSGCs对自然运动刺激的表现。我们提议的工作结合了功能性、 连接学、计算和理论方法有望产生一个多层次的 动态地使用不同的电路组件以实现上下文相关的电路模型 自然运动的处理，戏剧性地偏离了当前的静态电路模型 视网膜特征选择性。由于视网膜中的连接模式由标准回路组成 在大脑区域和动物物种中重复出现的主题，我们的研究将提供对 利用基本电路模体的算法函数进行神经计算的一般原理。

Abstract Motion detection, a fundamental computation of the visual system, begins in the retina. In the mammalian retina, the direction of moving objects is computed by the direction-selective circuit. The retinal output of this circuit is provided by direction-selective ganglion cells (DSGCs). These cells are strongly activated by motion in their preferred direction, but are suppressed by motion in the opposite, or “null”, direction. They report the direction of motion to higher brain centers for further visual processing, and they contribute to the control of eye movements and conscious vision. Besides their direction selectivity, DSGC responses are prominently influenced by the context of visual environments. These context-dependent properties are central to the motion encoding by DSGCs in the natural environment. This proposal aims to address two important context-dependent circuit functions pertinent to naturalistic stimuli. The first one is noise resilience. Motion in natural scenes is often accompanied by the presence of other visual features or “noise”. Aim 1 will determine circuit mechanisms that preserve direction selectivity in the presence of background noise. The second function is the encoding of motion contrast. Due to constant body and eye movements, visual inputs on the retina are composites of global image shifts and relative motion between moving objects and their backgrounds. DSGC responses are not only direction-selective, but also sensitive to relative motion compared to global motion. Aim 2 will determine the circuit motifs that confer DSGCs sensitivity to motion contrast. In Aim 3, we will link the algorithmic functions of experimentally defined circuit motifs to the encoding performance of DSGCs to naturalistic motion stimuli. Our proposed work combining functional, connectomic, computational and theoretical approaches is expected to produce a multi-layered circuit model that dynamically engages distinct circuit components for context-dependent processing of naturalistic motion, a dramatic departure from the current static circuit model of retinal feature selectivity. Since the connectivity patterns in the retina consist of canonical circuit motifs that recur across brain regions and animal species, our study will provide insights into the general principles of neural computation by the algorithmic functions of elementary circuit motifs.