Administrative supplement for Multimodal imaging of brain activity to investigate walking and mobility decline in older adults

摘要描述了本行政副刊所在的母项目的目标和措施 旨在完成。除了父项目提出的措施外，不会有其他措施 已执行。家长项目描述：目前研究步行神经控制的方法有限 通过无法在行走过程中测量人(功能磁共振成像，fMRI)或 无法测量皮质以下的活动(功能性近红外光谱，fNIRS)。我们断言，一个 充分和准确地了解老年人行走的神经控制需要实时测量 在实际行走过程中整个大脑的活跃区域。我们将通过使用创新的移动电话来实现这一目标 使用高密度脑电(EEG)进行脑成像。这种方法依赖于创新的硬件 和软件，提供活跃的皮质和皮质下大脑区域的三维定位 步行时的空间和时间分辨率。其结果是对神经控制的前所未有的洞察 走路。在这里，我们的首要目标是通过以下方式确定老年人活动的中枢神经控制 收集步行时的脑电，并将这些发现与一组全面的不同移动性相关联 结果(基于诊所的步行、复杂步行和社区活动测量)。我们的首要目标是 评估实际行走过程中的大脑活动在多大程度上解释了行动能力下降。在两个十字架上 分段和纵向设计，我们将确定是否行走性能较差和坡度较大 递减轨迹与补偿相关的神经回路假说的应用 (嘎吱作响)。Crunch是一个得到很好支持的大脑活动模式模型，当老年人 执行日益复杂的任务。Crash描述额顶脑的过度招募 与年轻人相比，老年人表现出的网络，即使在任务复杂性较低的情况下也是如此。 Crunch还描述了老年人大脑中可用的有限储备资源。这些因素导致年龄变大 成年人在执行日益复杂的任务时，大脑资源很快就会达到上限。当 一旦达到上限，业绩就会受到影响。RFA还呼吁提出建议，以“运作和协调” 用于量化动态步态和运动功能的成像方案和技术“。根据本协议， Call，我们的第二个目标是表征和协调使用fNIRS(过程中)行走时的高密度脑电 实际行走和成像行走)和功能磁共振成像(想象行走期间)。这将使我们能够确定最健壮的 不同神经成像方式的大脑活动的与嘎吱声相关的特征，这将加强我们的 结论，并允许广泛应用我们的研究结果。我们的第三个目标是研究 与走路时的嘎吱作响有关。因此，我们的项目将解决NIH RFA-AG的大部分目标- 18-019，并将确定老年人行走的神经关联，导致对 行动能力下降和功能障碍。

This abstract describes the aims and measures of parent project in which this administrative supplement is designed to complete. No additional measures, beyond those that were proposed by the parent project, will be performed. Parent project description: Current approaches to study the neural control of walking are limited by either the inability to measure people during walking (functional magnetic resonance imaging, fMRI) or the inability to measure activity below the cortex (functional near-infrared spectroscopy, fNIRS). We assert that a full and accurate understanding of the neural control of walking in older adults requires real time measurement of active regions throughout the brain during actual walking. We will achieve this by using innovative mobile brain imaging with high-density electroencephalography (EEG). This approach relies upon innovative hardware and software to deliver three-dimensional localization of active cortical and subcortical brain regions with high spatial and temporal resolution during walking. The result is unprecedented insight into the neural control of walking. Here, our overarching objective is to determine the central neural control of mobility in older adults by collecting EEG during walking and correlating these findings with a comprehensive set of diverse mobility outcomes (clinic-based walking, complex walking and community mobility measures). Our first aim is to evaluate the extent to which brain activity during actual walking explains mobility decline. In both cross sectional and longitudinal designs, we will determine whether poorer walking performance and steeper trajectories of decline are associated with the Compensation Related Utilization of Neural Circuits Hypothesis (CRUNCH). CRUNCH is a well-supported model of brain activity patterns that are seen when older individuals perform tasks of increasing complexity. CRUNCH describes the over-recruitment of frontoparietal brain networks that older adults exhibit in comparison to young adults, even at low levels of task complexity. CRUNCH also describes the limited reserve resources available in the older brain. These factors cause older adults to quickly reach a ceiling in brain resources when performing tasks of increasing complexity. When the ceiling is reached, performance suffers. The RFA also calls for proposals to “Operationalize and harmonize imaging protocols and techniques for quantifying dynamic gait and motor functions”. In accordance with this call, our second aim is to characterize and harmonize high-density EEG during walking with fNIRS (during actual and imaged walking) and fMRI (during imagined walking). This will allow us to identify the most robust CRUNCH-related hallmarks of brain activity across neuroimaging modalities, which will strengthen our conclusions and allow for widespread application of our findings. Our third aim is to study the mechanisms related to CRUNCH during walking. Thus, our project will address a majority of the objectives in NIH RFA-AG- 18-019 and will identify the neural correlates of walking in older adults, leading to unprecedented insight into mobility declines and dysfunction.