Behavioural and neural correlates of performance and expertise in an immersive virtual reality motion simulator

像飞机和汽车这样的强大车辆在没有高超技能的情况下操作起来可能是危险的。这种技能可以通过模拟训练获得--这一方法在复杂和潜在危险的情况下尤其重要，因为在这种情况下，实际练习的风险太大。利用模拟环境进行培训是一个日益增长且极其重要的研究领域。技术的进步使培训模拟器变得更加可用，但我们仍然不知道模拟体验的哪些方面会导致有效的学习。如果没有这些知识，模拟器培训可能是无效的，导致代价高昂的错误，甚至生命损失。 一个重要的问题是，训练模拟器是否应该包含身体运动。当我们在空间中导航时，视觉是我们的主导感觉，而视觉线索提供了一种强烈的自我运动感知。尽管我们经常低估运动知觉的贡献，但前庭和本体感觉线索对我们的经验是高度不可或缺的。这些运动提示在学习操作移动车辆时起着至关重要的作用。加拿大交通部民用航空许可证要求飞行员在运动模拟器中进行培训，但在航空以外，大多数模拟器的运动有限或没有运动，部分原因是它昂贵且困难。 我们需要知道什么是(和不是)在模拟环境中创建有效的培训体验所必需的。模拟器设计中的传统智慧一直是在再现环境时争取更高的真实感和保真度，但一些感觉可能对训练没有贡献，可能会给多感觉整合带来问题。视觉、前庭和其他运动线索之间的不匹配会导致不适和疾病，从而扰乱学习。我们需要学习如何模拟身体运动的感知体验，而不是试图完全重现身体运动。 为此，我们必须了解模拟环境中的多感官整合。这个项目将使用行为和大脑测量来揭示成功整合发生的视觉和运动感知的动态范围，并学习如何建立有效的训练模拟器。我们所知道的关于前庭运动知觉的神经关联的大部分来自于分离特定前庭组件的研究。虽然这些严格控制的实验室实验是至关重要的，但我们的兴趣是在人们沉浸在学习驾驶或飞行的同时测量感知和整合。我们对自我运动的感知对呈现给多种感官的信息高度敏感。 我们结合工程学和神经科学的专业知识，开发技术和工具，在不同的训练场景下研究运动模拟器中的学习和表现。我们使用脑电图仪测量大脑反应，监测头部和眼睛的运动，并收集应激反应的生理指标。使用这些测量方法，结合一系列行为观察，我们将建立一个行为和大脑与运动感知和多感觉整合相关的分类法。我们将使用这些工具来促进对沉浸式环境哪些方面最有效地获得技能的理解，并改进培训从模拟到现实生活的转移。 我们的目标是将这一新的理解应用到新一代训练模拟器的设计中。这项工作将带来技术进步和更安全、更有效的培训。随着我们的人口老龄化，我们的司机也在老龄化；有证据表明，老年人比年轻人更依赖多感官整合。这项工作将为老年司机的评估和再培训带来重要的新方法。

Powerful vehicles like airplanes and automobiles can be dangerous when operated without great skill. That skill can be acquired through simulation training - an approach that is especially important in complex and potentially dangerous situations where there is too much risk for real practice. The use of simulated environments for training is a growing and critically important area of research. Advances in technology have made training simulators more available, but we still do not know which aspects of a simulated experience lead to effective learning. Without this knowledge simulator training can be ineffective, resulting in costly mistakes and even loss of life. One important question is whether training simulators should incorporate physical motion. When we navigate through space, vision is our dominant sense, and visual cues provide a strong perception of self-motion. Although we often underestimate the contribution of kinesthetic perception, vestibular and proprioceptive cues are highly integral to our experience. These motion cues play a critical role when learning to operate moving vehicles. Transport Canada Civil Aviation licensing requires that pilots train in a motion simulator, but outside of aviation, most simulators have limited or no motion, in part because it is expensive and difficult. We need to know what is (and is not) necessary to create effective training experiences in simulated environments. Conventional wisdom in simulator design has been to strive for higher realism and fidelity in reproducing the environment, but some sensations may not contribute to training and can present problems for multisensory integration. Mismatches between visual, vestibular, and other motion cues cause discomfort and illness, which disrupts learning. Rather than trying to fully recreate physical motion, we need to learn how to simulate the perceptual experience of physical motion. To this end, we must understand multisensory integration in simulated environments. This project will use behavioural and brain measures to reveal the dynamic range of visual and motion perception within which successful integration occurs, and to learn how to build effective training simulators. Most of what we know about the neural correlates of vestibular motion perception comes from studies that isolate specific vestibular components. While these tightly controlled, laboratory experiments are crucial, our interest is to measure perception and integration while people are immersed in learning to drive or fly. Our perception of self-motion is highly sensitive to information presented to multiple senses. We combine engineering and neuroscience expertise, developing technology and tools to study learning and performance in a motion simulator under different training scenarios. We use electroencephalography to measure brain responses, we monitor head and eye movements, and we collect physiological measures of stress responses. Using these measures, together with a range of behavioural observations, we will build a taxonomy of behavioural and brain correlates of motion perception and multisensory integration. We will use these tools to advance understanding about what aspects of an immersive environment lead most effectively to skill acquisition, and to improve transfer of training from simulation to real life. We aim to apply this new understanding to a new generation of design for training simulators. The work will lead to technological advances and safer and more effective training. As our population ages, so do our drivers; there is evidence that older adults rely on multisensory integration to a greater extent than young adults. This work will lead to important new methods of evaluation and re-training for elderly drivers.