The information used to perceive binocular motion in depth

因为我们的眼睛在我们的头部并排放置，所以我们的视野的很大一部分可以同时通过两只眼睛看到。但是每只眼睛看到的世界略有不同，因为它位于略有不同的位置，因此每只眼睛的图像略有不同。眼睛之间的微小差异称为双眼差异，大约150年前就知道我们的大脑利用差异来帮助我们看到世界的深度和形状。事实上，我们的大脑对差异非常敏感：我们可以在手臂两倍的距离内检测到一张纸厚度的深度差异。双目视差对于感知物体如何在深度上移动也是潜在有用的。在物体三维运动过程中，物体的双眼视差会发生变化。然而，每只眼睛中的运动信号的大小也将存在直接差异。例如，如果物体直接朝向鼻子移动，则该物体的图像将在一只眼睛中沿一个方向移动，而在另一只眼睛中沿相反方向移动。如果我们想了解大脑是如何看到3D物体运动的，我们必须首先弄清楚它是使用双眼视差，眼睛之间的运动差异，还是两者兼而有之。这些知识对于我们进一步理解基本的大脑过程至关重要。它也有潜在的应用，以增强虚拟现实（VR）技术：虚拟现实系统可以设计成利用视觉系统最敏感的。在过去的10年里，几个研究小组试图测试什么视觉信息被大脑使用，使用简单的视觉测试，试图隔离两个信息源。结果一直存在争议。一个问题是，必须采用复杂的技巧来消除其中一个信息源（在真实的世界中，两者总是存在的）。这些操作导致视觉刺激是嘈杂的，并且可能没有完全消除所有预期的信息。在这个项目中，我们建议不仅仅用这些刺激来测试人类的视觉。此外，我们还将设计称为“理想型”的模型。这些是数学模型，旨在使用刺激中所有可用的信息。例如，用于检测变化的视差的理想观察者将使用视觉刺激内的所有视差信息。事实上，将模型应用于刺激是一种测试刺激包含哪些信息的方法。通过使用这些模型，我们可以设计包含两种信息源的视觉刺激，并计算理想的观察者可以如何使用这些信息来看到3D运动。然后，我们将人类的表现与模型进行比较，而不是简单地测试人们是否可以看到运动。这是第一次，我们将能够测试双眼视差和运动信息的相对重要性，看到三维物体运动。

Because our eyes are positioned side by side in our heads, there is a large portion of our visual field that can be seen through both eyes at the same time. But each eye gets a slightly different view of the world, because it is in a slightly different location, and hence each eye's image is slightly different. The small differences between the eyes are called binocular disparities and it been known for about 150 years that our brains use disparity to help us see depth and shape in the world. In fact, our brains are exquisitely sensitive to disparity: we can detect depth differences as small as the thickness of a sheet of paper at twice arms reach. Binocular disparity is also potentially useful for perceiving how objects move in depth. During object motion in three dimensions (3-D), the binocular disparity of the object will change. However, there will also be direct differences in the size of motion signals in each eye. For example, if an object move directly towards the nose, that object's image will move in one direction in one eye, and the opposite direction in the other eye. If we want to understand how the brain sees 3-D object motion, we must first find out whether it uses binocular disparity, motion differences between the eyes, or both. Such knowledge is critically important for furthering our understanding of basic brain processes. It also has potential application to the enhancement of virtual reality (VR) technology: VR systems can be designed to exploit what the visual system is most sensitive to.Over the last 10 years, several research groups have attempted to test what visual information is used by the brain, using simple visual tests that attempt to isolate the two sources of information. The results have been controversial. One problem is that complex tricks have to be employed to eliminate one of the sources of information (in the real world, both are always present). These manipulations result in visual stimuli that are noisy and that may not have completely eliminated all the expected information. In this project we propose to not just test human vision with such stimuli. Additionally, we will design models called 'ideal observers'. These are mathematical models designed to use all the information available in a stimulus. For example an ideal observer for detecting changing disparity will use all disparity information within a visual stimulus. Indeed, applying the model to a stimulus is a way of testing what information that stimulus contains. By using these models, we can design visual stimuli that contain both sources of information and calculate how well an ideal observer could use the information to see 3-D motion. We then compare human performance with the model, rather than simply testing whether people can see the motion or not. For the first time, we will be able to test the relative importance of binocular disparity and motion information for seeing 3-D object motion.