Zhang Yujin, Tan Fulun, Xu Xu, Duan Lian, Liu Hanli, Tian Fenghua, Zhu Chao-Zhe
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China ; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
Biomed Opt Express. 2015 Jul 8;6(8):2786-802. doi: 10.1364/BOE.6.002786. eCollection 2015 Aug 1.
Linear regression with short source-detector separation channels (S-channels) as references is an efficient way to overcome significant physiological interference from the superficial layer for functional near-infrared spectroscopy (fNIRS). However, the co-located configuration of S-channels and long source-detector separation channels (L-channels) is difficult to achieve in practice. In this study, we recorded superficial interference with S-channels in multiple scalp regions. We found that superficial interference has overall frequency-specific and globally symmetrical patterns. The performance of linear regression is also dependent on these patterns, indicating the possibility of simplifying the S-channel configurations for multiregional fNIRS imaging.
以短源探测器分离通道(S通道)为参考的线性回归是克服功能近红外光谱(fNIRS)中来自表层的显著生理干扰的有效方法。然而,S通道和长源探测器分离通道(L通道)的共定位配置在实践中难以实现。在本研究中,我们记录了多个头皮区域中S通道的表层干扰。我们发现表层干扰具有整体频率特异性和全局对称模式。线性回归的性能也取决于这些模式,这表明简化多区域fNIRS成像的S通道配置是有可能的。