Sensorimotor integration and balance

感觉运动控制依赖于对生物相关事件和运动动作的不确定编码。这两个过程中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感觉运动整合的神经原理，以保持站立平衡。为了解决这一首要目标，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.了解不确定性在前庭自我运动线索中的作用。目标2.确定躯体感觉和运动暗示如何使人保持站立平衡。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。拟议的研究活动结合了计算建模和实验方法，以形式化、预测和测试站立平衡的感觉运动控制背后的控制原理。在我的监督下与HQP和主要合作者密切合作，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会波动。我们提出了一种使用粒子(粒子滤波)来表示编码全身旋转的前庭传入总体的贝叶斯推理方法。基于这种方法的预测，我们假设参与者将表现出依赖于历史的知觉和眼睛反应，而不会对控制良好的全身旋转刺激错误地推断旋转方向。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，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，肌梭传入在主动平衡时比直立时表现出更高的阈值，并且不确定的感觉和运动信息的概率组合提供了一种首选姿势的感觉。最后，我们将揭示大脑如何适应改变的重力，以及大脑内部表示重力的平衡后果。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，大脑对重力的内部表征会引发刻板印象的平衡反应。冲击力。拟议的工作将产生关于与人体平衡有关的感觉运动整合基本原理的新知识，将有助于培训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议出版物和会议演示文稿进行翻译。

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.