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:10377086
- 负责人:
- 金额:$ 7.27万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2021
- 资助国家:美国
- 起止时间:2021-01-01 至 2023-03-31
- 项目状态:已结题
- 来源:
- 关键词:AnkleAnteriorAreaBalance trainingBasic ScienceBehaviorBiomechanicsBrainBrain imagingCerebellumCerebral DominanceCognitionConsensusDataDiagnosisElectrodesElectroencephalographyEquilibriumExcisionFunctional Magnetic Resonance ImagingGaitGait speedGoalsHeadHumanImageImaging technologyLaboratoriesLeadLegLimb structureLiteratureLocomotionLocomotor adaptationMeasuresModelingMonitorMorphologic artifactsMotionMotorMotor CortexMovement DisordersNervous System TraumaNoisePaperParietal LobePeer ReviewPerformanceProcessPublishingResearch PersonnelRoboticsRunningSignal TransductionSomatosensory CortexSpeedSystemTechnologyTestingTrainingUnited States National Institutes of HealthUpper ExtremityVisualWalkingWorkbaseblood oxygen level dependentbrain computer interfacecingulate cortexdata repositorydensitydisabilityexoskeletonfoothuman subjectimaging modalityimprovedinnovationinsightlocomotor controllocomotor tasksmind controlnovelpublic health relevancerelating to nervous systemrobot exoskeletonsignal processingsomatosensorytemporal measurementtreadmillwalking 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
人体运动适应的脊椎上控制
摘要
脑电描记技术的发展使脑电动力学的研究成为可能
在人类的步态中。有源电极、新颖的信号处理方法和受试者特异性反向电学特性
头部模型让我们对人类大脑如何控制运动有了前所未有的了解。思进
在基于脑电图的移动的脑成像中,
在真实的世界情况下,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型的噪声消除EEG系统,可以大大改善
脑电信号信噪比我们建议使用我们的新型脑电系统来研究人类的运动
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
上肢运动适应的脊髓上控制或想象的人类行走,但这些的时间尺度
成像模态不允许识别相对于步态周期的生物力学的脑活动。我们
建议使用我们的新型EEG系统来记录参与运动适应的大脑区域。具体地说,
我们将量化步态周期内的大脑活动频谱波动,
运动适应我们认为大脑的多个区域,包括前扣带回,小脑,
躯体感觉皮层和运动皮层可能参与行走的控制和适应。我们也
预计参与运动适应的区域将随着改善而减少光谱功率波动
在具有挑战性的步态任务中的运动表现。我们将调查的具体任务是步行
不同的速度,在分裂带跑步机上行走,用单侧机器人踝关节外骨骼行走,
在平衡木上用视觉干扰。EEG的高时间分辨率提供了特别有价值的
了解步态周期内大脑活动的幅度和时间。我们的初步数据显示,
控制人类行走所涉及的皮层区域比文献中通常认识到的要多。
这些研究结果将增加我们对人类脊髓上控制的基础科学认识
运动适应,并应导致脑电图移动的脑成像技术的进一步发展。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Daniel P Ferris其他文献
Daniel P Ferris的其他文献
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{{ truncateString('Daniel P Ferris', 18)}}的其他基金
Supraspinal Control of Human Locomotor Adaptation
人类运动适应的脊髓上控制
- 批准号:
10426056 - 财政年份:2018
- 资助金额:
$ 7.27万 - 项目类别:
Supraspinal Control of Human Locomotor Adaptation
人类运动适应的脊髓上控制
- 批准号:
10671884 - 财政年份:2018
- 资助金额:
$ 7.27万 - 项目类别:
Supraspinal Control of Human Locomotor Adaptation
人类运动适应的脊髓上控制
- 批准号:
10667742 - 财政年份:2018
- 资助金额:
$ 7.27万 - 项目类别:
Supraspinal Control of Human Locomotor Adaptation
人类运动适应的脊髓上控制
- 批准号:
9531486 - 财政年份:2018
- 资助金额:
$ 7.27万 - 项目类别:
Electrical Neuroimaging of Brain Processes during Human Gait
人类步态期间大脑过程的电神经成像
- 批准号:
8727116 - 财政年份:2011
- 资助金额:
$ 7.27万 - 项目类别:
Electrical Neuroimaging of Brain Processes during Human Gait
人类步态期间大脑过程的电神经成像
- 批准号:
8532061 - 财政年份:2011
- 资助金额:
$ 7.27万 - 项目类别:
Electrical Neuroimaging of Brain Processes during Human Gait
人类步态期间大脑过程的电神经成像
- 批准号:
8236146 - 财政年份:2011
- 资助金额:
$ 7.27万 - 项目类别:
Electrical Neuroimaging of Brain Processes during Human Gait
人类步态期间大脑过程的电神经成像
- 批准号:
8322574 - 财政年份:2011
- 资助金额:
$ 7.27万 - 项目类别:
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