Computational Theory of Motion Perception

这项提议将发展对人类视觉系统各方面的基本理解。目标是了解人类是如何感知运动的。换句话说，当一个人看到一群飞翔的鸟儿或飘落的雪花时，他或她的大脑内部发生了什么。这项提议是跨学科的，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。这一理论是由计算机算法实现的，这些算法应用于图像的运动序列，并预测估计的运动速度和其他特性。这些图像的运动序列是伪现实的，因为它们看起来是自然图像(例如飞行的鸟或雪)，但实际上是人工参数模型(这使我们能够通过改变参数来设计受控实验)。心理物理实验将我们理论的预测与执行一系列运动估计任务的受试者的表现进行了比较。这些实验解决了这样的问题，比如，人们擅长感知哪些类型的运动刺激？这些生理学实验试图确定运动处理在大脑中的位置。特别是，我们研究了大脑不同部分的神经细胞(神经元)在运动感知过程中的活动。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健壮和强大的计算机视觉算法，这将有许多技术应用(例如，机器人和自动化医疗诊断)。此外，了解神经元是如何进行计算的，对于神经科学的整个事业来说是至关重要的，因为它试图对我们精神生活背后的大脑机制进行科学解释。拨款将通过支持一名女性博士后研究员来帮助鼓励代表不足的群体。这笔赠款将包括生理实验的多电极记录的数据共享，此外，我们还将提供制造新的伪随机刺激的代码。这项提议还具有教育影响，因为它将有助于培养一名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.