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首页> 外文期刊>NeuroImage >Single-trial reconstruction of finger-pinch forces from human motor-cortical activation measured by near-infrared spectroscopy (NIRS).
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Single-trial reconstruction of finger-pinch forces from human motor-cortical activation measured by near-infrared spectroscopy (NIRS).

机译:通过近红外光谱(NIRS)测量的人类运动皮层激活对手指捏力的单次尝试重建。

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Near-infrared spectroscopy (NIRS) has recently been used to measure human motor-cortical activation, enabling the classification of the content of a sensory-motor event such as whether the left or right hand was used. Here, we advance this NIRS application by demonstrating quantitative estimates of multiple sensory-motor events from single-trial NIRS signals. It is known that different degrees of sensory-motor activation are required to generate various hand/finger force levels. Thus, using a sparse linear regression method, we examined whether the temporal changes in different force levels could be reconstructed from NIRS signals. We measured the relative changes in oxyhemoglobin concentrations in the bilateral sensory-motor cortices while participants performed an isometric finger-pinch force production with their thumb and index finger by repeatedly exerting one of three target forces (25, 50, or 75% of the maximum voluntary contraction) for 12 s. To reconstruct the generated forces, we determined the regression parameters from the training datasets and applied these parameters to new test datasets to validate the parameters in the single-trial reconstruction. The temporal changes in the three different levels of generated forces, as well as the baseline resting state, could be reconstructed, even for the test datasets. The best reconstruction was achieved when using only the selected NIRS channels dominantly located in the contralateral sensory-motor cortex, and with a four second hemodynamic delay. These data demonstrate the potential for reconstructing different levels of external loads (forces) from those of the internal loads (activation) in the human brain using NIRS.
机译:近红外光谱(NIRS)最近已用于测量人体运动皮层激活,从而能够对感觉运动事件的内容进行分类,例如使用左手还是右手。在这里,我们通过展示来自单次试验NIRS信号的多个感觉运动事件的定量估计来推进此NIRS应用程序。已知需要不同程度的感觉运动来产生各种手/手指力水平。因此,使用稀疏线性回归方法,我们检查了是否可以从NIRS信号中重构不同力水平下的时间变化。我们测量了双侧感觉运动皮层中氧合血红蛋白浓度的相对变化,而参与者通过反复施加三个目标力之一(最大,最大25%,50%或75%),用拇指和食指进行了等轴测捏动作自愿收缩12秒钟。为了重建生成的力,我们从训练数据集中确定了回归参数,并将这些参数应用于新的测试数据集,以验证单次试验重建中的参数。即使对于测试数据集,也可以重建三种不同级别的生成力的时间变化以及基线静止状态。仅使用主要位于对侧感觉运动皮层的选定NIRS通道,并具有四秒钟的血流动力学延迟时,才能获得最佳的重建效果。这些数据证明了使用NIRS从人脑内部负荷(激活)的水平重建不同水平的外部负荷(力)的潜力。

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