Active Visual Depth Perception by Looming

Looming 的主动视觉深度感知

• 批准号: 0096790
• 负责人: Terrence Sejnowski
• 金额: $ 10.85万
• 依托单位: The Salk Institute for Biological Studies
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-09-01 至 2002-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0096790&HistoricalAwards=false
• 关键词: Active; Visual; Depth; Perception; Looming

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.

人类和其他动物使用刺激的视觉“迫在眉睫”来检测视野深度刺激的距离的变化。 目前尚不清楚这种视觉提示如何驱动神经信号，以指导适当的行为反应（例如方法或避免这种刺激）。 该项目使用一种昆虫，蛾甘达（Moth Manduca），该昆虫在飞行过程中徘徊在花前，作为一个简单的实验系统。 一种组合的方法将行为实验与生理学和建模联系起来，以实验测试哪些视觉提示与指导行为相关的替代假设，这是开发具有现实生物学参数的计算模型的基础。 结果将在昆虫视觉之外至关重要，以理解一般的视觉机制的深度检测和避免障碍物，并在机器人技术中开发有用的机器视觉和指导系统。 该项目还提供了在非常强大的计算神经科学环境中，对博士后女性神经障碍者的出色跨学科培训。