Posture and Orientation in Older Adults and Post-Stroke

描述（由申请人提供）：本研究的总体目标是确定相互冲突的视觉和自我运动信息如何调节老年人和中风后个体的姿势控制系统的反应。当视野信息与自我运动反馈不匹配时，健康的老年人对视觉、前庭和本体感受信号的反应与年轻人不同。年轻人将所有输入的频率成分纳入他们的反应;老年人主要依靠视觉。我们假设老年人和中风后个体对复杂的多模态刺激的感觉阈值增加，这产生了对预测或视觉输入的更大依赖，使得他们更难以选择性地对视觉和身体不稳定做出反应。通过将虚拟环境技术与支撑表面平移相结合，我们计划操纵视觉输入、体感（即，本体感受和前庭）输入，并预测以揭示节段输入和高阶处理对姿势响应的贡献。我们计划比较健康的年轻人和老年人与中风后的年轻人和老年人，以区分年龄和CNS损伤的影响。我们将首先探讨受试者是否会随着时间的推移而改变他们对特定感觉方式的反应。然后，头部和躯干将在不同的位置相对于视觉和支持表面运动，揭示如何改变感觉和生物力学方向影响视觉运动信号的反应。最后，我们将研究可预测的和随机的视觉输入如何影响对随机支持面输入的响应。视野依赖性将采用杆框测试进行测量。我们将采用主成分分析和自回归建模的新方法来区分身体力学和特定的神经过程。这些分析应该揭示如何选择的控制通路的任务，以及进一步定义传入通路的响应特性。将通过运动学测量（包括压力中心、质心位移和肌电图）检查节段和肌肉反应策略，并使用MANOVA检验显著性。澄清视觉输入和姿势稳定之间的关系将确定功能的情况下，提出了一个高概率的不稳定和下降。从拟议的研究结果可以潜在地用于开发个性化设计的治疗干预方案。

DESCRIPTION (provided by applicant): The overall goal of this research is to determine how conflicting visual and self-motion information modulates the responses of the postural control system in elderly adults and in individuals post-stroke. When visual field information does not match self-motion feedback, healthy elderly respond to combined visual, vestibular, and proprioceptive signals differently than young adults. Young adults incorporate frequency components of all inputs into their responses; elderly adults rely primarily on vision. We hypothesize that elderly adults and individuals post-stroke have increased sensory thresholds to complex multimodal stimuli which produces a greater reliance on predictive or on visual inputs making it more difficult for them to selectively respond to visual and physical destabilization. By combining the technology of a virtual environment with support surface translations we plan to manipulate the influence of visual inputs, somatosensory (i.e., proprioceptive and vestibular) inputs, and prediction to reveal the contribution of segmental inputs and higher order processing to the postural response. We plan to compare healthy young and elderly individuals with young and elderly individuals post-stroke in order to distinguish between the effects of age and CNS impairment. We will first explore whether subjects change their responses to particular sensory modalities over time. Then the head and trunk will be aligned in different positions with respect to visual and support surface motion to reveal how altering sensory and biomechanical orientations affects the response to visual motion signals. Lastly, we will examine how predictable and random visual inputs influence the response to random support surface inputs. Visual field dependence will be measured with a Rod and Frame test. We will employ novel methods of Principal Component Analysis and autoregressive modeling to distinguish between body mechanics and specified neural processes. These analyses should reveal how the selection of control pathways is determined by the task as well as further define response properties of the afferent pathways. Segmental and muscle response strategies will be examined through kinematic measures including center of pressure, center of mass displacement, and electromyography, and tested for significance with a MANOVA. Clarifying the relation between visual inputs and postural stabilization will identify functional situations that present a high probability for instability and falling. Results from the proposed studies can potentially be used for developing individually designed programs of therapeutic intervention.