Stork: Supraspinal Control of Human Locomotor Adaptation

DANIEL P FERRIS (2018-04-01 to 2023-03-31) Supraspinal Control of Human Locomotor Adaptation. Amount: $1237701



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.

人体运动适应的脊柱控制摘要摘要脑电图(EEG)技术的进步使得研究人类步态时的电脑动力学变得可行。有源电极,新颖的信号处理方法和特定主题的逆电头模型可以前所未有地洞察人类大脑如何控制运动。基于脑电图的移动脑成像的进一步发展将增加我们对人类大脑如何在现实世界中工作的基本理解,改善运动障碍的诊断和治疗,并导致新的脑 - 计算机接口。我们最近开发了一种新颖的降噪EEG系统,可以大大提高脑电信号的信噪比。我们建议使用我们的新型EEG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柱控制,但这些成像模式的时间尺度不允许识别相对于生物力学的大脑活动。步态周期。我们建议使用我们的新型脑电图系统记录涉及运动适应的大脑区域。具体而言,我们将量化步态周期内的大脑活动频谱波动,证明与运动适应的相关性。我们预计多个大脑区域,包括前扣带,小脑,躯体感觉皮层和运动皮层可能参与控制和适应步行。我们还期望参与运动适应的区域将减少光谱功率波动,同时在具有挑战性的步态任务期间改善运动性能。我们将研究的具体任务是以不同的速度行走,在分开式跑步机上行走,使用单侧机器人踝关节外骨骼行走,以及在视觉扰动的平衡木上行走。 EEG的高时间分辨率为步态周期内的大脑活动的幅度和时间提供了特别有价值的见解。我们的初步数据表明,控制人类行走的皮质区域多于文献中普遍认可的区域。这些研究的结果将增加我们对人体运动适应的脊柱控制的基本科学理解,并应导致脑电移动脑成像技术的进一步发展。

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