Multisensory processing, self-motion perception, and performance across the lifespan: Behavioural and neural measures

开车是一项危险的活动。虚拟环境驾驶模拟器为潜在危险的情况提供安全培训，是旨在了解操作大型机器所涉及的行为的日益增长的研究领域的一部分。自动感知是操作移动车辆不可或缺的一部分，它提供有关速度、加速度、旋转、航向和地形的信息。自我运动感知对于判断与其他运动物体(如交通、行人)的动态交互作用至关重要。虽然前庭信息是自我运动知觉的重要组成部分，但大多数模拟器的物理运动能力有限或没有。我们的工作旨在促进对涉及自我运动感知、车辆控制和导航的神经和行为机制的了解，以及研究使用运动模拟器来培训和测试司机。关键的是，自我运动知觉是多种感官信息复杂整合的结果，包括视觉、听觉和前庭。我们考察了各种驾驶场景中多感官处理的本质，观察了对速度、加速度、航向、危险、转向和踏板控制的操纵的反应。我们研究注意力、多任务处理、警觉性、空间记忆和导航如何与自我运动感知相互作用，从而影响驾驶。我们研究的一个重要组成部分是了解随着年龄的增长，这些反应是如何变化的。与年龄相关的差异包括有助于自我运动感知的基本感觉过程，我们知道多感觉整合在整个生命周期中都会发生变化。驾驶专业知识和不断变化的大脑动力学都有助于维持安全的驾驶行为。我们感兴趣的是，这些因素如何导致自动驾驶感知和车辆控制的变化，以及我们如何提高老年司机的驾驶安全。我们将对18至80岁的司机进行研究，以了解驾驶过程中涉及的基本神经和行为过程如何在整个寿命周期内发生变化。感知自我运动是操作移动车辆不可或缺的一部分，但很少有研究模拟器包含完整的身体运动，更少的研究模拟器包含大脑成像。我们正在用创新的方法来评估与自主感知和车辆控制相关的神经反应，这是一项开创性的工作。随着技术转向清洁能源和电动汽车，加拿大司机的平均年龄正在增加，驾驶的性质也在发生变化。新车的趋势是让它们对路况不那么敏感，以提供更顺畅的行驶。然而，如果多感觉整合是老年司机自适应神经策略的一部分，他们可能需要提供增强的听觉、前庭和本体感觉信号的车辆。我们的研究解决了关于感知和学习的基本问题，这些问题将为未来关于技术和培训的决策提供信息。

Driving a car is a dangerous activity. Virtual environment driving simulators provide safe training for potentially dangerous situations, and are part of a growing area of research aimed at understanding the behaviour involved in operating large machines. Self-motion perception is integral to operating moving vehicles, providing information about speed, acceleration, rotation, heading, and terrain. Self-motion perception is critical for judging dynamic interactions with other moving objects (e.g. traffic, pedestrians). Although vestibular information is a critical component of self-motion perception, most simulators have limited or no physical motion capability. Our work is aimed at advancing knowledge about neural and behavioural mechanisms involved in self-motion perception, vehicle control, and navigation, as well as studying the use of motion simulators for training and testing drivers. Critically, self-motion perception is a result of a complex integration of information from multiple senses, including visual, auditory, and vestibular. We examine the nature of multisensory processing in a variety of driving scenarios, looking at responses to manipulations of speed, acceleration, heading, hazards, steering and pedal control. We look at how attention, multitasking, vigilance, spatial memory, and navigation interact with self-motion perception to affect driving. An important component of our research is to understand how these responses change as we grow older. Age-related differences include basic sensory processes that contribute to self-motion perception, and we know that multisensory integration changes across the lifespan. Both driving expertise and changing brain dynamics contribute to the maintenance of safe driving behaviour. We are interested in how these factors lead to changes in self-motion perception and vehicle control, and how we might improve driving safety for older drivers. We will be studying drivers from 18 to 80 years old to understand how fundamental neural and behavioural processes involved in driving change across the lifespan. Perception of self-motion is an integral part of operating a moving vehicle but very few research simulators incorporate full physical motion and even fewer incorporate brain-imaging. We are breaking ground with innovative methods to evaluate neural responses associated with self-motion perception and vehicle control. The average age of drivers in Canada is increasing and the nature of driving is changing as technology moves to clean energy and electric cars. The trend with newer cars is to make them less sensitive to road conditions to provide a smoother ride. However, if multisensory integration is part of an adaptive neural strategy for older drivers, they may need vehicles that provide enhanced auditory, vestibular, and proprioceptive signals. Our research addresses fundamental questions about perception and learning that will inform future decisions about technology and training.