Sensorimotor integration and balance

感觉运动控制依赖于生物相关事件和运动动作的不确定编码。这两个过程的不确定性塑造了自我运动线索的多感官整合，这对站立平衡至关重要。我的研究计划的长期目标是揭示站立平衡的感觉运动整合的神经原理。为了实现这一总体目标，拟议的研究计划将解决不确定性如何影响与站立平衡相关的感觉和运动线索的中央处理以及这些机制在三个核心短期目标下的适应性：目标1。了解前庭自我运动线索中不确定性的作用。目标2.确定躯体感觉和运动线索如何使站立平衡。目标3.了解大脑对重力的编码如何影响站立平衡。 科学方法。 拟议的研究活动结合联合收割机计算建模和实验方法，以正式化，预测和测试的基本原则的感觉运动控制站立平衡。在我的监督下，我们与HQP密切合作，沿着还有主要的合作者，我们将首先确定感觉编码的不确定性是否有益，以及身体内部估计的不确定性是否波动。我们提出了一个贝叶斯推理方法，使用粒子（粒子滤波）来代表人口的前庭传入编码全身旋转。基于这种方法的预测，我们假设，参与者将表现出历史依赖性的感知和视觉反应，而不会对控制良好的全身旋转刺激的旋转方向产生不正确的推断。其次，我们将使用我们的NSERC资助的站立平衡机器人来表征站立平衡过程中体感传入编码的自然统计数据，计算它们的感觉阈值，并揭示平衡控制器如何结合不确定的感觉和运动信息来产生首选直立姿势的感觉。我们假设，肌梭传入将表现出更高的阈值，同时积极平衡比直立时没有平衡，不确定的感觉和运动信息的概率组合提供了一种感觉的首选姿势。最后，我们将揭示大脑如何适应改变的重力以及大脑内部对重力的表达的平衡结果。我们假设大脑会将长时间的线性加速度解释为一种新的重力环境，并且大脑对重力的内部表征会引起刻板的平衡反应。 冲击 拟议的工作将产生关于与人体平衡相关的感觉运动整合的基本原则的新知识，将有助于培养下一代综合感觉运动生理学家，并将通过有影响力的同行评审出版物和会议演讲进行翻译。

Sensorimotor control relies on uncertain encoding of biologically-relevant events and motor actions. Uncertainty in both processes shapes the multisensory integration of self-motion cues that is critical for standing balance. The long-term objective of my research program is to reveal the neural principles underlying sensorimotor integration for standing balance. To address this overarching goal, the proposed research program will address how uncertainty influences central processing of sensory and motor cues relevant for standing balance and the adaptability of these mechanisms under three core short-term objectives: Objective 1. Understand the role of uncertainty in vestibular cues of self-motion. Objective 2. Determine how somatosensory and motor cues enable standing balance. Objective 3. Understand how the brain encoding of gravity affects standing balance. Scientific approach. The proposed research activities combine computational modelling and experimental approaches to formalize, predict and test the governing principles underlying the sensorimotor control of standing balance. In close collaboration with HQP under my supervision along with key collaborators, we will first determine if uncertainty in sensory encoding can be beneficial and whether uncertainty in the internal estimate of the body fluctuates. We propose a Bayesian inference approach using particles (particle filtering) to represent population of vestibular afferents encoding whole-body rotation. Based on predictions from this approach, we hypothesize that participants will exhibit history-dependent perceptual and ocular responses without an incorrect inference of rotation direction to well-controlled whole-body rotational stimuli. Second, we will use our NSERC-funded standing balance robot to characterize the natural statistics of somatosensory afferents encoding during standing balance, calculate their sensory thresholds and reveal how the balance controller combines uncertain sensory and motor information to give rise to a sense of preferred upright posture. We hypothesize that muscle spindle afferents will exhibit higher thresholds while balancing actively than when standing upright without balancing and that a probabilistic combination of uncertain sensory and motor information affords a sense of preferred posture. Finally, we will reveal how the brain adapts to altered gravity and the balance consequences of the brain's internal representation of gravity. We hypothesize that the brain will interpret a prolonged linear acceleration as a novel gravitational environment and that the brain's internal representation of gravity induces stereotypical balance responses. Impact. The proposed work will generate new knowledge on principles underlying sensorimotor integration related to human balance, will help train the next generation of integrative sensorimotor physiologists and will be translated through impactful peer-reviewed publications and conference presentations.