Electrical Neuroimaging of Brain Processes during Human Gait

描述（由申请人提供）：有一个重要的临床需要开发功能成像技术，可以量化人类运动过程中的大脑过程，并将其与身体动力学联系起来。移动脑成像可以帮助诊断和治疗许多运动障碍和神经损伤患者。我们提出独立成分分析的高密度脑电图（EEG）可以量化不同的脑过程参与控制人类的步态。此外，我们认为使用EEG独立分量分析识别的脑皮层电过程与全身动力学相关。我们将研究健康的年轻受试者进行各种运动任务，同时我们使用活动头皮电极记录运动运动学和256通道脑电图。在具体目标1中，我们将检查以一定速度行走的受试者，以确定与步态周期同步的步幅内激活和失活模式是否在不同的行走速度下一致。在具体目标2中，我们将检查受试者进行被动平躺行走和主动平躺行走，以确定感觉反馈与运动前馈命令对脑电皮质过程的相对影响。我们假设被动的平躺行走比主动的平躺行走更少的电皮质源。我们还将比较主动平躺行走和跑步机行走，以确定平躺行走和行走在激活大脑皮质过程中的相似性。在具体目标3中，我们将检查受试者在分离式带跑步机上行走，使用相干性来量化感觉运动半球独立性。在具体目标4中，我们将研究受试者在狭窄的跑步机上行走平衡木，以确定参与维持和监测平衡的皮层电过程。这项研究的结果将促进我们对与人类行走控制相关的皮层电动力学的理解，并将为探索神经性步态障碍的机制带来新的研究。这一发现也可以促进新的脑机接口技术来控制机器人矫形器或假肢。

DESCRIPTION (provided by applicant): There is an important clinical need to develop functional imaging techniques that can quantify brain processes during human locomotion and relate them to body dynamics. Mobile brain imaging could assist with the diagnosis and treatment of patients with numerous movement disorders and neurological injuries. We propose that Independent Component Analysis of high-density electroencephalography (EEG) can quantify distinct brain processes involved in the control of human gait. Furthermore, we contend that electrocortical brain processes identified using Independent Component Analysis of EEG correlate with whole body dynamics. We will study healthy young subjects performing various locomotor tasks while we record movement kinematics and 256-channel EEG using active scalp electrodes. In Specific Aim 1, we will examine subjects walking at a range of speeds to determine if intra-stride patterns of activation and deactivation synchronized to the gait cycle are consistent across walking speeds. In Specific Aim 2, we will examine subjects performing passive recumbent stepping and active recumbent stepping to determine the relative effects of sensory feedback vs. motor feed forward commands with sensory feedback on electrocortical brain processes. We hypothesize that passive recumbent stepping will engage fewer electrocortical sources than active recumbent stepping. We will also compare active recumbent stepping with treadmill walking to determine the similarities between recumbent stepping and walking in activating cortical brain processes. In Specific Aim 3, we will examine subjects walking on a split-belt treadmill to quantify sensorimotor hemispheric independence using coherence. In Specific Aim 4, we will study subjects walking on a narrow treadmill-mounted balance beam to identify the electrocortical processes involved in maintaining and monitoring balance. The results from this study will advance our understanding of electrocortical dynamics related to the control of human walking, and will lead to new studies probing mechanisms of neurological gait impairments. The findings could also facilitate new brain- machine interface technologies for controlling robotic orthoses or prostheses. PUBLIC HEALTH RELEVANCE: We will use head mounted electrodes and signal processing techniques to identify brain activity related to the control of human walking. The results may lead to new imaging techniques for studying brain function during diagnosis and rehabilitation of movement disorders.