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

成人一生中流解析性能的行为和生物学预测因素

基本信息

批准号：
1908701
负责人：
金额：
--
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1908701
关键词：
Behavioural biological predictors flow parsing

项目摘要

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.

人类主要是活跃的，在环境中移动与感兴趣的物体交互，同时避开静态和移动的障碍物。然而，活动会给大脑带来一个问题：观察者或场景中其他物体的运动可能会引起视网膜运动。那么，我们如何解析传入的视觉流以计算出场景的哪些部分正在移动以及如果移动的话它们要去哪里？这些问题普遍存在且重要；如果不能快速准确地处理视觉运动来解决这些问题，与障碍物碰撞和相关伤害的可能性就会增加。在过去的十年中，出现了针对此解析问题的新的、纯视觉解决方案的证据。流解析假设 [1] 表明人类有选择地过滤（或解析）由观察者运动（称为光流）产生的全局运动的结构化模式。目前，人们对这种机制的神经实现知之甚少。为了解决这个问题，我们将检查整个成人寿命中流解析性能的个体差异，并考虑流解析性能的生物和较低水平的视觉心理物理学预测因素。特别是，众所周知，老年人在各种运动处理任务中都会受到损害（例如参见[2]）。我们预计该组的流解析和对象移动检测也将受到影响。这种损伤可能会导致老年人跌倒风险和/或交通事故的增加。在这个项目中，我们将使用涉及行为实验和神经影像学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，并研究衰老对流解析的影响 2. 通过考虑如何通过较低级别视觉运动处理任务中的个体差异来预测性能，阐明流解析的基础机制。 3. 调查流解析速度（据认为在自我运动开始后仅 10-15 毫秒 [3] 开始）与脱髓鞘之间的关系，脱髓鞘已知发生在老年参与者 [4] 中，并被认为会减慢认知处理 [5]。作为第一项检查以下内容的研究：i）年长观察者的流解析障碍； ii) 流解析和低级运动处理之间的关系以及 iii) 流解析的生物相关性，该项目将很好地为视觉神经科学文献做出重要贡献。