Behavioural and biological predictors of flow parsing performance across the adult lifespan

人类主要是活跃的，在环境中移动，与感兴趣的物体互动，同时避开静态和移动的障碍物。然而，活动给大脑带来了一个问题：视网膜运动可能是由观察者或场景中其他物体的运动引起的。那么，我们如何解析传入的视觉流，以确定场景的哪些部分正在移动，如果是的话，它们将前往哪里？这些问题是普遍而重要的；如果不对视觉运动进行快速而准确的处理来解决这些问题，那么与障碍物相撞和相关伤害的可能性就会增加。在过去的十年中，出现了一种新的、纯可视化的解决方案来解决这个解析问题。流解析假说[1]表明，人类有选择地过滤(或解析出)由观察者运动引起的全球运动的结构化模式(称为光流)。目前，对这一机制的神经实现知之甚少。为了解决这一问题，我们将考察成人一生中心流分析成绩的个体差异，并考虑生物学和较低水平的视觉心理物理学对心流分析成绩的预测。特别是，已经知道老年人在广泛的运动处理任务中受到损害(例如，见[2])。我们预计，流解析和对象移动检测也将对该组造成影响。在这个项目中，我们将使用涉及行为实验和神经成像方法的多学科方法来：1.测量广泛年龄范围的健康参与者的流解析速度和强度，并调查年龄对流解析的影响。2.通过考虑低级视觉运动处理任务中的个体差异如何预测流解析的基础机制，阐明流解析的基础机制。3.研究心流分析的速度(被认为是在自我运动开始后10-15毫秒[3]启动)和脱髓鞘之间的关系[4]，这种脱髓鞘被认为会减缓认知加工。作为第一个研究：i)在老年观察者中流分析的损害；ii)流分析和低水平运动处理之间的关系；iii)流分析的生物学相关性，该项目将处于有利地位，对视觉神经科学文献做出重要贡献。

Humans are primarily active, moving through the environment to interact with objects of interest while avoiding static and moving obstacles. Activity, however, creates a problem for the brain: retinal motion could arise from movement of either the observer or other objects in the scene. How, then, do we parse the incoming visual flow to work out which parts of the scene are moving and if so where they are going? These problems are ubiquitous and important; Without rapid and accurate processing of visual motion to solve them the likelihood of colliding with obstacles and associated injury is increased. In the last decade evidence has emerged for a new, purely visual solution to this parsing problem. The flow parsing hypothesis [1] suggests that humans selectively filter (or parse out) the structured patterns of global motion that arise from observer movement (termed optic flow). Currently, little is known about neural implementation of this mechanism. To address this we will examine individual differences in flow parsing performance across the adult lifespan and consider both biological and lower-level visual psychophysics predictors of flow parsing performance. In particular, it is already known that older individuals are impaired across a wide range of motion processing tasks (e.g. see [2]). We anticipate that flow parsing and hence object movement detection will also be compromised for this group. Such impairments could contribute to increased fall risk and/or motoring accidents in ageing.In this project we will use a multi-disciplinary approach involving behavioural experiments and neuroimaging approaches to:1. Measure speed and strength of flow parsing across a wide age range of healthy participants and investigate the effects of ageing on flow parsing 2. Shed light on the underpinning mechanisms of flow parsing by considering how performance is predicted by individual differences in lower-level visual motion processing tasks. 3. Investigate the relationship between speed of flow parsing (thought to be initiated only 10-15 ms [3] after onset of self-movement) and demyelination which is known to occur in older participants [4] and thought to slow cognitive processing [5]. As the first study to examine: i) impairments in flow parsing in older observers; ii) the relationship between flow parsing and lower level motion processing and iii) biological correlates of flow parsing, the project will be well placed to make important contributions to the visual neuroscience literature.