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.
