Supraspinal Control of Human Locomotor Adaptation

人类运动适应的脊髓上控制

基本信息

批准号：
9531486
负责人：
Daniel P Ferris
金额：
$ 40.62万
依托单位：
UNIVERSITY OF FLORIDA
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-04-01 至 2023-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9531486
关键词：
Ankle Anterior Area Balance training Basic Science Behavior Biomechanics Brain Brain imaging Cerebellum Cerebral Dominance Cognition Consensus Data Diagnosis Electrodes Electroencephalography Equilibrium Excision Functional Magnetic Resonance Imaging Gait Gait speed Goals Head Human Image Imaging technology Laboratories Lead Leg Limb structure Literature Locomotion Locomotor adaptation Measures Modeling Monitor Morphologic artifacts Motion Motor Motor Cortex Movement Disorders Nervous System Trauma Noise Paper Parietal Lobe Peer Review Performance Process Publishing Research Personnel Robotics Running Signal Transduction Somatosensory Cortex Speed System Technology Testing Training United States National Institutes of Health Upper Extremity Visual Walking Work base blood oxygen level dependent brain computer interface cingulate cortex data warehouse density disability exoskeleton foot human subject imaging modality improved innovation insight locomotor control locomotor tasks mind control novel public health relevance relating to nervous system robot exoskeleton signal processing somatosensory temporal measurement treadmill walking speed

项目摘要

Title Supraspinal Control of Human Locomotor Adaptation Abstract Advances in electroencephalography (EEG) technology have made it feasible to study electrical brain dynamics during human gait. Active electrodes, novel signal processing approaches, and subject-specific inverse electrical head models allow for unprecedented insight into how the human brain controls locomotion. Further advances in EEG based mobile brain imaging will increase our fundamental understanding of how the human brain works in real world situations, improve diagnosis and treatment of movement disorders, and result in new brain- computer interfaces. We recently developed a novel noise-cancelling EEG system that can greatly improve the signal to noise ratio for EEG. We propose to use our novel EEG system to investigate human locomotor adaptation. Many studies have used blood-oxygen-level dependent imaging (e.g. fMRI or fNIRS) to study supraspinal control of upper limb motor adaptation or imagined human walking, but the timescale of those imaging modalities do not allow for identifying brain activity relative to the biomechanics of the gait cycle. We propose to use our novel EEG system to document the brain areas involved in locomotor adaptation. Specifically, we will quantify brain activity spectral fluctuations within the gait cycle that demonstrate correlations with locomotor adaptation. We expect that multiple brain areas, including the anterior cingulate, cerebellum, somatosensory cortex, and motor cortex are likely involved in the control and adaptation of walking. We also expect that areas involved in locomotor adaptation will decrease spectral power fluctuations with improvements in locomotor performance during challenging gait tasks. The specific tasks that we will investigate are walking at different speeds, walking on a split-belt treadmill, walking with a unilateral robotic ankle exoskeleton, and walking on a balance beam with visual perturbations. The high temporal resolution of EEG provides particularly valuable insight into both amplitude and timing of brain activity within the gait cycle. Our preliminary data suggest that there are more cortical areas involved in controlling human walking than are generally recognized in the literature. The results from these studies will increase our basic science understanding of the supraspinal control of human locomotor adaptation and should lead to further advances in EEG mobile brain imaging technology.

标题人类运动适应的脊髓上控制抽象的脑电图 (EEG) 技术的进步使得研究脑电动力学成为可能在人类步态过程中。有源电极、新颖的信号处理方法和特定主题的逆电学头部模型可以让我们前所未有地深入了解人脑如何控制运动。进一步的进展基于脑电图的移动大脑成像将增加我们对人脑如何工作的基本理解在现实世界中，改善运动障碍的诊断和治疗，并产生新的大脑计算机接口。我们最近开发了一种新型的降噪脑电图系统，可以大大改善脑电图的信噪比。我们建议使用我们新颖的脑电图系统来研究人类运动适应。许多研究使用血氧水平依赖性成像（例如 fMRI 或 fNIRS）来研究上肢运动适应或想象的人类行走的脊髓上控制，但这些的时间尺度成像方式无法识别与步态周期生物力学相关的大脑活动。我们建议使用我们新颖的脑电图系统来记录参与运动适应的大脑区域。具体来说，我们将量化步态周期内的大脑活动光谱波动，以证明与运动适应。我们预计多个大脑区域，包括前扣带回、小脑、体感皮层和运动皮层可能参与步行的控制和适应。我们也预计涉及运动适应的区域将通过改进减少光谱功率波动在具有挑战性的步态任务中的运动表现。我们要研究的具体任务是步行不同速度、在分带式跑步机上行走、使用单侧机器人踝关节外骨骼行走以及行走在具有视觉扰动的平衡木上。脑电图的高时间分辨率提供了特别有价值的深入了解步态周期内大脑活动的幅度和时间。我们的初步数据表明控制人类行走的皮质区域比文献中普遍认识的要多。这些研究的结果将增加我们对人类脊髓上控制的基础科学理解运动适应应该会导致脑电图移动脑成像技术的进一步进步。