New insight into functional eye evolution: seeing the world through moving photoreceptors.

我们希望了解昆虫如何感知它们所生活的三维世界，并利用这些知识来模拟它们所看到的数学。我们已经通过产生一种新的理论来预测果蝇对三维物体的感知能力，并证明其在预测神经反应和视觉行为方面的准确性，迈出了这种独特方法的关键一步。这项计划的下一步目标是：测试并将这种方法扩展到其他昆虫，它们的眼睛和大脑已经适应了不同的生活方式和环境，从一个全新的动态角度解读立体视觉。为了有效地移动，动物必须不断地计算出它们相对于现实世界物体的x，y，z位置，许多动物都有一双眼睛来实现这一点。光感受器如何主动地对眼睛的光学图像视差进行采样尚不清楚，因为该基本信息限制步骤尚未在眼睛的整个采样矩阵上进行体内研究。这种综合性的多尺度研究旨在推进我们目前对昆虫复眼立体视觉的理解，从静态图像视差比较到新的形态动态主动采样理论。它的设计目的是利用实验和理论来揭示和分析蝴蝶、蜜蜂、蚂蚁和苍蝇眼睛中的光机械感光器微跳视如何通过进化进行适应，以提供超分辨率3D视觉。这项研究旨在揭示这些昆虫物种对三维世界的感知能力，并利用这些信息来预测它们的视觉能力和行为。此外，本研究所获得的结果具有真实的潜力，为机器人传感和三维机器视觉提供新的算法。

We wish to understand how insects perceive the 3-dimensional world they live in and use this knowledge to simulate what they see, mathematically. We have made the first critical step of this unique approach by generating a new theory that predicts how well a fruit fly sees 3-dimensional objects and demonstrated its accuracy in predicting neural responses and visual behaviours. This proposal aims for the next step: to test and expand this approach to other insects, in which eyes and brains have adapted to different lifestyles and environments, to decipher stereo vision from a completely new dynamic perspective.To move efficiently, animals must continuously work out their x,y,z-positions in respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes' optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes' whole sampling matrix. This integrative multiscale study aims to advance our current understanding of stereopsis in insect compound eyes, from static image disparity comparison to a new morphodynamic active sampling theory. It is designed, using experiments and theory, to reveal and analyse how photomechanical photoreceptor microsaccades in the butterfly, honeybees, ant and housefly eyes have adapted through evolution to provide super-resolution 3D vision. This research aims to reveal how well each of these insect species see the three-dimensional world, and use this information to predict their visual capabilities and behaviours. Moreover, the results obtained with this research have real potential to provide new algorithms for robotic sensing and three-dimensional machine vision.