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A fresh look at visual sampling: How are fixational eye-movements optimised? [PhysFEM]

重新审视视觉采样：如何优化注视眼球运动？

基本信息

批准号：
EP/W023873/1
负责人：
Hannah Smithson
金额：
$ 257.37万
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2022
资助国家：
英国
起止时间：
2022 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FW023873%2F1
关键词：
fresh look visual sampling How

项目摘要

How should a sensory system, such as vision or hearing, optimally sample the world? Too much detail takes too long, and too much resource to acquire and process; too little risks failing to capture the vital information on what is going on around us. Human vision is a fascinating example - for even when the gaze is 'fixed' onto a target object or performing a specific task such as deciding which of two objects is higher, the eyes are in constant, apparently-random, motion that we do not understand. One might assume that such involuntary movements of the eye could only 'blur' vision, but there are reasons to believe that they might actually enhance it. One reason for suspecting this is that we know that many aspects of vision have evolved towards the best performance possible.This project - the Physics of Fixational Eye Movements (PhysFEM) - addresses the challenge of these ever-present involuntary movements of our eyes by combining ideas, methods and people from theoretical physics of random motion, and from the life sciences of visual neuroscience and psychology. The combination is new and potentially powerful: there is almost no realm of physics that does not think about finding paths of trajectories that optimise something. Examples arise in complex classical mechanics, quantum mechanics, and the thermal physics of random processes. These ideas from physics provide a natural but fresh way of thinking about the possibility that fixational eye movements optimise some aspects of vision. More than that, they bring new calculation methods to find such paths, leading to empirically testable predictions about how the eyes might move to maximise the information available given particular task-demands. The objective measurement of human visual performance under controlled conditions - the domain of 'psychophysics' - completes the iterative cycles of model predictions and testing.Physics enters the experimental mode of this project also in terms of the equipment used in in the Oxford Perception Lab to measure eye movements. The team use 'adaptive optics' - first developed for large astronomical telescopes to correct the optical distortions of the atmosphere - to image the retina at the back of the eye whilst correcting for distortions in the eye's fluid-filled optical components. Such correction permits high-resolution imaging of individual cells in the human retina without any invasive procedure. The Adaptive Optics Scanning Laser Ophthalmoscope (AO-SLO) will perform three simultaneous tasks in PhysFEM: (i) projecting controlled images onto the retina; (ii) imaging the retina at the resolution of individual light-detecting ('photoreceptor') cells; (iii) measuring eye movements with unprecedented accuracy, under a series of specific visual tasks.The findings of the project will be built into a growing, open-access computational tool for vision science and technology, ISETBio, through a collaboration with its originator and director at the University of Pennsylvania, USA. ISETBio is an open-source set of software tools that characterise the sensory processes of early vision, and provides a platform for realistic computational implementation and evaluation of models for how neural processing incorporates FEMs, and transferring this to the international community of researchers in biological- and computer-vision and medicine.

视觉或听觉等感官系统应该如何以最佳方式对世界进行采样？太多的细节需要花费太长的时间和太多的资源来获取和处理;太少的风险无法捕捉到关于我们周围正在发生的事情的重要信息。人类的视觉就是一个迷人的例子--即使当目光“固定”在一个目标物体上，或者执行一项特定的任务，比如决定两个物体中哪一个更高，眼睛也在不断地、明显地、随机地运动，这是我们无法理解的。有人可能会认为，这种眼睛的无意识运动只能“模糊”视力，但有理由相信它们实际上可能会增强它。怀疑这一点的一个原因是，我们知道视觉的许多方面已经朝着尽可能最好的性能发展。这个项目-注视眼动物理学（PhysFEM）-解决了这些挑战-通过结合随机运动的理论物理学以及视觉神经科学和心理学的生命科学的思想，方法和人员，呈现我们眼睛的不自主运动。这种结合是新的，而且可能是强大的：几乎没有一个物理学领域不考虑寻找优化某些东西的轨迹路径。例子出现在复杂的经典力学、量子力学和随机过程的热物理学中。这些来自物理学的想法提供了一种自然但新鲜的方式来思考注视眼球运动优化视觉某些方面的可能性。更重要的是，他们带来了新的计算方法来找到这样的路径，从而导致经验上可检验的预测，即眼睛如何移动，以最大限度地利用特定任务需求的信息。在受控条件下对人类视觉表现的客观测量--“心理物理学”领域--完成了模型预测和测试的迭代循环。物理学也进入了这个项目的实验模式，在牛津感知实验室使用的设备来测量眼球运动。该团队使用“自适应光学”-首先为大型天文望远镜开发，以纠正大气的光学失真-对眼睛后部的视网膜成像，同时纠正眼睛充满液体的光学组件的失真。这种校正允许在没有任何侵入性程序的情况下对人类视网膜中的单个细胞进行高分辨率成像。自适应光学扫描激光检眼镜（AO-SLO）将在PhysFEM中同时执行三项任务：（i）将受控图像投射到视网膜上;（ii）以单个光检测的分辨率对视网膜成像;（“感光细胞”）;（iii）在一系列特定的视觉任务下，以前所未有的准确度测量眼球运动。该项目的研究结果将纳入一个不断增长的，视觉科学和技术的开放获取计算工具ISETBio，通过与美国宾夕法尼亚大学的创始人和主任合作。ISETBio是一套开源的软件工具，可以模拟早期视觉的感觉过程，并提供一个平台，用于现实的计算实施和评估神经处理如何结合FEM的模型，并将其转移到生物和计算机视觉和医学研究人员的国际社区。