Electrical Neuroimaging of Brain Processes during Human Gait

人类步态期间大脑过程的电神经成像

基本信息

批准号：
8322574
负责人：
Daniel P Ferris
金额：
$ 32.97万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-09-01 至 2015-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8322574
关键词：
Anterior Area Attention Brain Brain imaging Clinical Cognitive Contralateral Data Diagnosis Electrodes Electroencephalography Equilibrium Event Functional Imaging Functional Magnetic Resonance Imaging Gait Head Human Image Imaging Techniques Impairment Lead Learning Left Locomotion Locomotor adaptation Methods Monitor Motion Motor Movement Movement Disorders Musculoskeletal Equilibrium Near-Infrared Spectroscopy Nervous System Trauma Neurologic Neuronal Plasticity Orthotic Devices Parietal Lobe Patients Pattern Prefrontal Cortex Process Prosthesis Rehabilitation therapy Relative (related person)Research Resolution Robotics Scalp structure Sensory Process Source Speed Stroke Study Subject Systems Analysis Techniques Technology Time Training Validation Walking Work base brain machine interface computerized data processing cranium density disability feeding improved independent component analysis kinematics locomotor tasks neuroimaging novel patient population relating to nervous system sensory feedback

项目摘要

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.

描述（由申请人提供）：临床迫切需要开发功能成像技术，该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患有多种运动障碍和神经损伤的患者。我们提出，高密度脑电图（EEG）的独立成分分析可以量化参与控制人类步态的不同大脑过程。此外，我们认为使用脑电图独立成分分析识别的皮层大脑过程与全身动力学相关。我们将研究执行各种运动任务的健康年轻受试者，同时使用主动头皮电极记录运动学和 256 通道脑电图。在具体目标 1 中，我们将检查受试者以一定速度行走，以确定与步态周期同步的步幅内激活和停用模式在不同步行速度下是否一致。在具体目标 2 中，我们将检查受试者进行被动卧式行走和主动卧式行走，以确定感觉反馈与带有感觉反馈的运动前馈命令对皮层大脑过程的相对影响。我们假设被动卧式行走会比主动卧式行走涉及更少的皮层电源。我们还将比较主动卧式行走和跑步机行走，以确定卧式行走和行走在激活大脑皮层过程方面的相似性。在具体目标 3 中，我们将检查受试者在分带式跑步机上行走，以使用一致性来量化感觉运动半球的独立性。在具体目标 4 中，我们将研究受试者在安装在跑步机上的狭窄平衡木上行走，以确定维持和监控平衡所涉及的皮层电过程。这项研究的结果将增进我们对与人类行走控制相关的皮层动力学的理解，并将引发探索神经步态损伤机制的新研究。这些发现还可以促进用于控制机器人矫形器或假肢的新脑机接口技术。