Nambu Isao, Osu Rieko, Sato Masa-aki, Ando Soichi, Kawato Mitsuo, Naito Eiichi
ATR Computational Neuroscience Laboratories, Kyoto, Japan.
Neuroimage. 2009 Aug 15;47(2):628-37. doi: 10.1016/j.neuroimage.2009.04.050. Epub 2009 Apr 22.
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.
近红外光谱(NIRS)最近已被用于测量人类运动皮层的激活情况,从而能够对感觉运动事件的内容进行分类,比如判断使用的是左手还是右手。在此,我们通过展示从单次试验的NIRS信号中对多个感觉运动事件进行定量估计,推进了这种NIRS应用。众所周知,产生不同的手部/手指力量水平需要不同程度的感觉运动激活。因此,我们使用一种稀疏线性回归方法,研究是否可以从NIRS信号中重建不同力量水平的时间变化。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,在此期间参与者用拇指和食指进行等长捏力产生,通过反复施加三种目标力(最大自主收缩的25%、50%或75%)之一,持续12秒。为了重建所产生的力量,我们从训练数据集中确定回归参数,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,三种不同水平的所产生力量以及基线静息状态的时间变化也能够被重建。当仅使用主要位于对侧感觉运动皮层的选定NIRS通道,并伴有4秒的血液动力学延迟时,实现了最佳重建。这些数据证明了使用NIRS从人类大脑内部负荷(激活)重建不同水平的外部负荷(力量)的潜力。