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觉整合，这对站立平衡至关重要。我研究项目的长期目标是揭示站立平衡中感觉运动整合的神经原理。为了实现这一总体目标，拟议的研究计划将探讨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。了解不确定性在自我运动的前庭提示中的作用。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。科学的方法。提出的研究活动将计算建模和实验方法相结合，以形式化，预测和测试站立平衡感觉运动控制的基本原则。在我和主要合作者的监督下，我们将与HQP密切合作，首先确定感官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。我们提出了一种贝叶斯推理方法，使用粒子（粒子滤波）来表示编码全身旋转的前庭传入事件的数量。基于这种方法的预测，我们假设参与者将表现出历史依赖的知觉和眼反应，而不会对控制良好的全身旋转刺激的旋转方向做出错误的推断。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事件编码的自然统计，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，与不平衡直立站立相比，主动平衡时肌肉纺锤体传入将表现出更高的阈值，并且不确定的感觉和运动信息的概率组合提供了首选姿势的感觉。最后，我们将揭示大脑如何适应改变的重力和大脑内部重力表征的平衡后果。我们假设大脑会将长时间的线性加速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。的影响。拟议的工作将产生与人类平衡相关的感觉运动整合原理的新知识，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报告进行翻译。

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.