Active Visual Depth Perception by Looming

人类和其他动物利用刺激的视觉“隐现”来检测刺激在视野深度上的距离变化。目前还不清楚这些视觉线索是如何驱动神经信号，从而引导适当的行为反应，比如对这种刺激的接近或回避。这个项目使用了一种昆虫，Manduca蛾，它在飞行中觅食时盘旋在花前，作为一个更简单的实验系统。一种结合的方法将行为实验与生理学和建模联系起来，实验测试关于哪些视觉线索与指导行为相关的替代假设，作为开发具有现实生物参数的计算模型的基础。研究结果不仅对昆虫视觉有重要意义，对理解一般视觉机制的深度检测和避障，以及在机器人技术中开发有用的机器视觉和制导系统也有重要意义。该项目还为女性博士后神经行为学家提供了优秀的跨学科培训，为计算神经科学提供了一个非常强大的环境。

Humans and other animals use visual 'looming' of a stimulus to detect change in distance of a stimulus in the depth of the visual field. It is unclear how such visual cues drive neural signals that guide appropriate behavioral responses such as approach or avoidance for such a stimulus. This project uses an insect, the moth Manduca, which hovers in front of flowers while feeding in flight, as a simpler system for experimentation. A combined approach links behavioral experiments to physiology and to modeling, to experimentally test alternative hypotheses about which visual cues are relevant for guiding behavior, as a basis for developing computational models with realistic biological parameters. Results will be important beyond insect vision, for understanding depth detection and obstacle avoidance by visual mechanisms in general, and for developing useful machine vision and guidance systems in robotics. This project also provides excellent cross-disciplinary training of a postdoctoral woman neuroethologist in an exceptionally strong environment for computational neuroscience.