Computational Theory of Motion Perception

这个建议将发展对人类视觉系统各个方面的基本理解。目标是了解人类是如何感知运动的。换句话说，当一个人看到一群鸟在飞翔或雪花在飘落时，他或她的大脑里发生了什么。该提案是跨学科的，结合了计算理论、心理物理学和生理学。计算理论为人类如何处理运动提供了一个数学模型。该理论是通过计算机算法实现的，该算法应用于图像的运动序列，并预测运动的估计速度和其他属性。这些图像的运动序列是伪现实的，从某种意义上说，它们看起来是自然图像（例如，飞鸟或雪），但实际上是人工参数化模型（这使我们能够通过改变参数来设计控制实验）。心理物理实验将我们的理论预测与人类受试者执行一系列运动估计任务的表现进行了比较。这些实验解决的问题是，人们擅长感知哪种类型的运动刺激？生理实验试图确定运动处理在大脑中发生的位置。特别是，我们研究在运动感知过程中大脑不同部位的神经细胞（神经元）的活动。预计了解人类视觉系统如何处理运动将使我们能够开发出更强大的计算机视觉算法，这些算法将有许多技术应用（例如机器人和自动医疗诊断）。此外，理解神经元如何进行计算是整个神经科学事业的核心，它试图对我们精神生活背后的大脑机制给出科学的解释。该基金将通过支持一名女性博士后研究人员来帮助鼓励代表性不足的群体。这项资助将包括生理学实验的多电极记录的数据共享，此外，我们将提供制作新颖的伪随机刺激的代码。该提案还具有教育方面的影响，因为它将有助于培养跨学科研究的研究生，包括计算机科学、心理学、神经科学和统计学。

This proposal will develop fundamental understanding of aspects of the human visual system. The goal is to understand how humans perceive motion . In other words, to understand what goes on inside a human's brain when he, or she, looks at a group of birds flying or snowflakes falling. The proposal is interdisciplinary and combines computational theory, psychophysics and physiology. The computational theory provides a mathematical model for how humans process motion. The theory is implemented by computer algorithms, which are applied to a motion sequence of images, and which predict the estimated velocities of motion and other properties. These motion sequences of images are pseudo-realistic, in the sense that they appear to be natural images (e.g. of flying birds, or snow) but instead are artificial parameterized models (which enables us to design controlled experiments by altering the parameters). The psychophysical experiments compare the predictions of our theory with the performance of human subjects performing a range of motion estimation tasks. These experiments address issues such as, what types of motion stimuli are people expert at perceiving? The physiological experiments attempt to pin down where motion processing takes place in the brain. In particular, we study the activity of neural cells (neurons) in different parts of the brain during motion perception. It is anticipated that understanding how the human visual system processes motion will enable us to develop more robust and powerful computer vision algorithms which will have many technological applications (e.g. for robotics and automated medical diagnosis). In addition, understanding how neurons perform computations is central to the entire enterprise of neuroscience in its attempt to give a scientific account of the brain mechanisms underlying our mental life.The grant will help encourage underrepresented groups by supporting a female postdoctoral researcher. The grant will include data sharing of the multi-electrode recordings of the physiological experiments and, in addition, we will make available the code for making novel pseudo-random stimuli. The proposal also has educational impact because it will help train a graduate student in interdisciplinary research, encompassing computer science, psychology, neuroscience and statistics.