Multisensory self-motion perception

当我们在世界上移动时，我们的大脑有一项非凡的任务，即无缝整合来自我们各种感觉系统的信息，包括视觉，听觉，我们的肌肉和关节，以及我们内耳（前庭）的加速度检测器。通过最佳地整合这些感官输入，这使我们能够估计自我运动参数，如速度，距离和前进方向，其精度高于任何一个感官输入。传统上，这些感觉系统中的每一个都是独立研究的，但我的研究项目旨在量化这些多个感觉输入如何整合到大脑中。我们的研究利用了基本感知任务和最先进的模拟和虚拟现实（VR）技术的独特优势，开发了整个生命周期的多感官自我运动感知模型。拟议的研究计划的主要目标是：目标1：评估不同的感官刺激特性（例如持续时间，速度）如何影响自我运动估计的可靠性，以及这如何影响自我运动感知过程中的感官权重。 目标二：评估知觉学习是否发生在自我运动过程中，以及使用外显反馈的训练是否提高了自我运动估计的精度。 目标3：检验期望对多感觉自我运动知觉和感觉加权的影响程度。 目标4：探索感觉、认知和运动系统的典型年龄相关变化如何影响自我运动过程中的多感觉整合。 科学方法我们将使用环境评估实验室，这是一个最先进的模拟设施，包括VR系统和一个大型6自由度运动平台。这些设施允许在受控条件下系统地操纵感觉输入。我们将使用成熟的心理物理和行为范例和建模技术来测量感官估计精度和感官权重。我们将使用一组成熟的感觉、运动和认知功能基线测试来解释个体差异，并调查特定领域能力和实验任务表现之间的任何关联。 影响这些研究将大大有助于多感觉整合的科学领域;特别是自我运动感知，运动，流动性和衰老。这些研究的长期应用影响可能与虚拟现实系统和模拟器的设计以及老龄化人口的用户界面和车辆设计考虑因素有关。

As we move through the world, our brain has the extraordinary task of seamlessly integrating information from across our various sensory systems including, vision, audition, our muscles and joints, and the acceleration detectors in our inner ear (vestibular). By optimally integrating these sensory inputs, this allows us to estimate self-movement parameters such as speed, distance, and heading direction with greater precision than any one sensory input alone. Traditionally, each of these sensory systems has been studied independently of one another, but my research program is aimed at quantifying how these multiple sensory inputs are integrated in the brain. Our research exploits the unique benefits of basic perceptual tasks and state-of-the-art simulation and Virtual Reality (VR) technologies to develop models of multisensory self-motion perception across the lifespan. The main objectives of the proposed research program are to: Objective 1: Evaluate how different sensory stimulus characteristics (e.g. duration, speed) affect the reliability of self-motion estimates and how this affects sensory weighting during self-motion perception. Objective 2: Assess whether perceptual learning occurs during self-motion and whether training with explicit feedback improves self-motion estimate precision. Objective 3: Examine the extent to which expectations influence multisensory self-motion perception and sensory weighting. Objective 4: Explore how typical age-related changes across sensory, cognitive, and motor systems affect multisensory integration during self-motion. Scientific Approach We will use the Challenging Environment Assessment Laboratory; a state-of-the-art simulation facility that includes VR systems and a large 6 degree-of-freedom motion platform. These facilities allow for the systematic manipulation of sensory inputs under controlled conditions. We will use well-established psychophysical and behavioral paradigms and modelling techniques to measure sensory estimate precision and sensory weights. We will use a battery of well-established baseline tests of sensory, motor, and cognitive functions to account for individual differences and to investigate any associations between domain-specific abilities and experimental task performance. Impact These studies will contribute significantly to the the scientific field of multisensory integration; particularly self-motion perception, locomotion, mobility, and aging. Long-term applied impacts of these studies may be relevant to design of virtual reality systems and simulators, and user interface and vehicle design considerations for an aging population.