Time-dependent cortical activation in voluntary muscle contraction.

Q4 Medicine Open Neuroimaging Journal Pub Date : 2011-01-01 Epub Date: 2011-12-23 DOI:10.2174/1874440001105010232
Qi Yang, Xiaofeng Wang, Yin Fang, Vlodek Siemionow, Wanxiang Yao, Guang H Yue
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引用次数: 6

Abstract

This study was to characterize dynamic source strength changes estimated from high-density scalp electroencephalogram (EEG) at different phases of a submaximal voluntary muscle contraction. Eight healthy volunteers performed isometric handgrip contractions of the right arm at 20% maximal intensity. Signals of the handgrip force, electromyography (EMG) from the finger flexor and extensor muscles and 64-channel EEG were acquired simultaneously. Sources of the EEG were analyzed at 19 time points across preparation, execution and sustaining phases of the handgrip. A 3-layer boundary element model (BEM) based on the MNI (Montréal Neurological Institute) brain MRI was used to overlay the sources. A distributed current density model, LORETA L1 norm method was applied to the data that had been processed by independent component analysis (ICA). Statistical analysis based on a mixed-effects polynomial regression model showed a significant and consistent time-dependent non-linear source strength change pattern in different phases of the handgrip. The source strength increased at the preparation phase, peaked at the force onset time and decreased in the sustaining phase. There was no significant difference in the changing pattern of the source strength among Brodmann's areas 1, 2, 3, 4, and 6. These results show, for the first time, a high time resolution increasing-and-decreasing pattern of activation among the sensorimotor regions with the highest activity occurs at the muscle activity onset. The similarity in the source strength time courses among the cortical centers examined suggests a synchronized parallel function in controlling the motor activity.

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随意肌收缩的时间依赖性皮层激活。
本研究的目的是通过高密度头皮脑电图(EEG)在亚最大随意肌收缩的不同阶段估计动态源强度的变化。8名健康志愿者以20%的最大强度进行右臂等距握力收缩。同时采集手部握力、手指屈伸肌肌电图和64通道脑电图信号。在握力准备、执行和维持阶段的19个时间点分析脑电图的来源。采用基于MNI (montr神经学研究所)脑MRI的3层边界元模型(BEM)对源进行叠加。对独立分量分析(ICA)处理后的数据采用LORETA L1范数法建立分布式电流密度模型。基于混合效应多项式回归模型的统计分析表明,在握把的不同阶段,源强度呈显著且一致的随时间变化的非线性变化模式。源强度在预备阶段增大,在力起作用时间达到峰值,在持续阶段减小。Brodmann’s区1、2、3、4、6的源强度变化规律无显著差异。这些结果首次表明,在肌肉活动开始时,在最高活动的感觉运动区域之间出现了高时间分辨率的激活增减模式。在被检查的皮质中心之间的源强度时间过程的相似性表明在控制运动活动方面有同步的平行功能。
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来源期刊
Open Neuroimaging Journal
Open Neuroimaging Journal Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
0.70
自引率
0.00%
发文量
3
期刊介绍: The Open Neuroimaging Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, and letters in all important areas of brain function, structure and organization including neuroimaging, neuroradiology, analysis methods, functional MRI acquisition and physics, brain mapping, macroscopic level of brain organization, computational modeling and analysis, structure-function and brain-behavior relationships, anatomy and physiology, psychiatric diseases and disorders of the nervous system, use of imaging to the understanding of brain pathology and brain abnormalities, cognition and aging, social neuroscience, sensorimotor processing, communication and learning.
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