Visual motion processing for perception and smooth pursuit eye movements

用于感知和平滑追踪眼球运动的视觉运动处理

• 批准号: 418493-2012
• 负责人: Spering, Miriam
• 金额: $ 2.33万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2016
• 资助国家: 加拿大
• 起止时间: 2016-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=596382
• 关键词: Visual; motion; processing; perception; smooth

My research program involves studies of smooth pursuit eye movements, the type of movement humans use to track moving visual targets. Without the ability to move our eyes in this fashion, image motion across the retina would produce motion blur and impair visual acuity. One of the hallmarks of pursuit eye movements is their close relationship to how we perceive visual motion. Many researchers believe that perception and pursuit are controlled by the same brain areas and mechanisms, but recent studies question this assumption. The long-term objective of my research program is to characterize the relationship between perception and pursuit eye movements and their link to underlying brain mechanisms for visual information processing. To achieve this, two short-term objectives are planned. (1) To assess effects of perception on pursuit. We will investigate whether better perception, due to perceptual learning, improves pursuit. This would indicate commonality in the neural substrate underlying both responses. (2) To study effects of pursuit on perception. We will compare the ability to predict motion trajectories-an essential skill to play sports or drive a car, for example-during pursuit and fixation. Better performance during pursuit would indicate that mere pursuit execution improves perception. All studies in my research program involve trainees who will acquire a multitude of skills ranging from eye tracking to statistical methods, enabling them to contribute successfully to the high-quality research landscape in Canada. My research program will advance our understanding of how visual information is processed in the brain to control perception and pursuit. Examples of industrial sectors or future application that will benefit from this advanced understanding include robotics and automotive industries. For instance, current driverless cars and robots rely on sensors that do not use eye movements to detect moving objects. New eye-movement based sensor technology could improve the design of driverless cars, ultimately improving the mobility of people with visual impairments. These sensors could also be incorporated into standard cars, making driving safer and more efficient, thereby increasing road safety.

我的研究计划涉及对流行眼动运动的研究，这是人类用于跟踪移动视觉目标的运动类型。如果没有这种方式使我们的眼睛移动，则跨视网膜的图像运动会产生动作模糊并损害视力。追求眼动的标志之一是它们与我们如何看待视觉运动的密切关系。许多研究人员认为，感知和追求受相同的大脑区域和机制控制，但最近的研究质疑这一假设。我的研究计划的长期目标是表征感知与追求眼运动之间的关系及其与视觉信息处理的潜在大脑机制的联系。为此，计划了两个短期目标。 （1）评估感知对追求的影响。我们将研究由于感知学习而更好的感知是否可以改善追求。这将表明两个反应的神经基质中的共同点。 （2）研究追求对感知的影响。我们将比较预测运动轨迹的能力，即运动或开车的基本技能，例如锻炼和固定。追求过程中的更好绩效将表明仅追求执行会提高感知。我的研究计划中的所有研究都涉及学员，他们将获得从眼睛跟踪到统计方法的多种技能，使他们能够成功地为加拿大的高质量研究领域做出贡献。我的研究计划将促进我们对大脑中视觉信息的处理方式的理解，以控制感知和追求。工业部门或将来的应用程序的示例将从这种先进的理解中受益，包括机器人和汽车行业。例如，当前的无人驾驶汽车和机器人依赖于不使用眼动物来检测移动对象的传感器。新的基于眼动的传感器技术可以改善无人驾驶汽车的设计，最终改善视觉障碍者的移动性。这些传感器也可以将其纳入标准汽车中，从而使行驶更安全，更高效，从而提高道路安全性。