Mechanistic model of multisensory postural control

描述(申请人提供)：这项研究的长期目标是了解神经系统如何融合来自多个感官系统的信息来控制直立姿势。在患者和老年人群中，自适应地选择和重新加权另一种定向参考的能力被认为是姿势控制的关键因素。尽管多感官加权很重要，但人们对它是如何实现的知之甚少。我们开发了一种新的实验范式，可以同时操作两种感觉输入(视觉和触觉)来探索多感觉整合的特性。同时，我们开发了一种独特的两步建模方法，使用时间序列技术和机械模型来确定姿势摆动的哪些特征可以：i)归因于估计或控制；以及ii)区分用于多感觉重新加权的不同估计机制。在这里，我们专注于在不断变化的感觉环境中模拟多感觉重加权的过程。我们的目标是开发一种机械模型，明确地将潜在的生理子系统与姿势控制联系起来。未来的工作将使用类似的技术来解决患者群体，以确定他们平衡赤字的基础。

DESCRIPTION (provided by applicant): The long-term goal of this research is to understand how the nervous system fuses information from multiple sensory systems for the control of upright stance. The ability to select and reweight alternative orientation references adaptively is considered a critical factor for postural control in patient and elderly populations. Despite the importance of multisensory reweighting, little is known about how it is achieved. We have developed a new experimental paradigm that simultaneously manipulates two sensory inputs (vision and touch) to probe the properties of multisensory integration. In parallel, we have developed a unique two-step modeling approach using time series techniques and mechanistic models to determine which characteristics of postural sway can: i) be attributed to estimation or control; and ii) distinguish different mechanisms of estimation used for multisensory reweighting. Here we focus on modeling the process of multisensory reweighting in changing sensory environments. The goal is to develop a mechanistic model that will explicitly link underlying physiological subsystems to postural control. Future work will address patient populations with similar techniques to determine the basis of their balance deficits.