Locomotion adaptation deficits in older adults with mild cognitive impairment and Alzheimers disease

项目摘要 社区步行功能需要复杂的运动协调、感觉反馈、动态平衡， 适应不断变化的环境刺激，同时也注意到过马路或说话等任务 在电话里说不幸的是，认知功能障碍，轻度认知障碍（MCI）的标志， 阿尔茨海默氏病（AD）直接影响可用于执行这种治疗的认知运动神经资源。 日常生活活动。先前研究的严谨性表明，与健康的老年人（HOA）相比， 患有MCI和AD的人走得更慢，跌倒更多，并且步态表现有缺陷。特别是步态 步态变异性的紊乱和变化通常先于认知能力下降。因此，我们的总体目标是 了解MCI和AD对步态功能和运动灵活性的影响，以及与 认知障碍运动适应是一个至关重要的过程，它使人类能够 灵活应对环境需求，实现正常的社区步行功能。分带行走是 一个标准化的，稳健的，充分研究的范式，用于量化运动适应能力， 对步行功能和预防跌倒的影响。尽管有大量关于分裂带适应的文献， 令人惊讶的是，在多个年龄和神经病理学的个体中， MCI和AD。先前的一项研究表明，当身体健全时， 参与者被认知任务分心，这表明适应过程与认知过程相互作用。 功能协调发展的另一项研究表明，多次分裂带行走改善了术后的活动性结果。 中风，表明其作为运动干预的潜力。然而，在是否和 分裂带适应如何与MCI和AD患者的认知缺陷和行走功能相关。的 目前的R21将建立在MPI Kesar和Nocera新发表的研究基础上，该研究提供了第一个初步的 有证据表明，与HOA相比，MCI和AD患者的分裂带适应明显受损。我们 前提是，在MCI和AD患者中，运动适应能力降低是一个基本的， 不太清楚的机制，可以是一个敏感的生物标志物的认知运动障碍， 运动干预的重要治疗靶点。在这里，我们提出了分裂的第一个比较- 带适应，结合步态和认知功能的综合评估，在MCI，AD， HOA。我们提出了一个独特的组合的横截面组间比较（目标1）和重复- 测量疾病进展的纵向时间点比较（目标2）。目标3是初步可行性 这项研究旨在指导未来在MCI和AD患者中进行分带式有氧步行运动干预的临床试验。此外，本发明还 与运动适应（以前未研究）平行，我们还将评估步行功能（步态 速度、步态耐力、移动性结果）、步态表现（步长、步态变异性、步幅时间），以及 在同一参与者队列中进行认知，生成一个创新的，丰富的，多模态的数据集。

PROJECT ABSTRACT Community walking function requires complex motor coordination, sensory feedback, dynamic balance, adaptation to changing environmental stimuli, while also attending to tasks such as crossing a street or talking over the phone. Unfortunately, cognitive dysfunction, the hallmark of mild cognitive impairments (MCI) and Alzheimer’s Disease (AD), directly impacts the cognitive-motor neural resources available to carry out such activities of daily living. The rigor of previous research shows that compared to healthy older adults (HOA), people with MCI and AD walk slower, fall more, and have deficits in gait performance. Notably, gait disturbances and changes in gait variability often precede cognitive decline. Thus, our overall goal is to understand the effects of MCI and AD on gait function and locomotor flexibility, and the inter-relationships with cognitive impairments. Locomotor adaptation is a fundamentally important process that enables humans to flexibility respond to environmental demands, enabling normal community walking function. Split-belt walking is a standardized, robust, well studied paradigm for quantifying capacity for locomotor adaptation, with potential implications for walking function and fall prevention. Despite a large body of literature on split-belt adaptation in individuals of multiple ages and neuro-pathologies, surprisingly, split-belt adaptation has not been assessed in MCI and AD. A previous study showed reduction in the rate of split-belt adaptation when able-bodied participants were distracted by a cognitive task, suggesting that adaptation processes interact with cognitive functions. Another study showed multiple sessions of split-belt walking improved mobility outcomes post- stroke, suggesting its potential as an exercise intervention. However, there is a knowledge gap regarding if and how split-belt adaptation relates to cognitive deficits and walking function in individuals with MCI and AD. The current R21 will build upon MPI Kesar and Nocera’s new published study that provides the first preliminary evidence that split-belt adaptation is significantly impaired in people with MCI and AD compared to HOA. Our premise is that in people with MCI and AD, reduced capacity for locomotor adaptation is a fundamental but poorly understood mechanism that can be a sensitive biomarker of cognitive-motor impairments, and an important therapeutic target for exercise-based interventions. Here, we propose the first comparison of split- belt adaptation, in conjunction with comprehensive assessments of gait and cognitive function, in MCI, AD, and HOA. We propose a unique combination of cross-sectional between-group comparisons (Aim 1) and repeated- measures longitudinal time-point comparisons of disease progression (Aim 2). Aim 3 is a preliminary feasibility study to guide future clinical trials on split-belt aerobic walking exercise interventions in MCI and AD. Further, in parallel with locomotor adaptation (not previously studied), we will also evaluate walking function (gait speed, gait endurance, mobility outcomes), gait performance (step length, gait variability, stride time), and cognition in the same participant cohort, generating an innovative, rich, multi-modal dataset.