Department of Psychophysiology, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1-1, Ogawahigashi, Kodaira, Tokyo, 187-8551, Japan.
Lundbeck Japan, Minato, Tokyo, 105-0001, Japan.
Hum Brain Mapp. 2017 Oct;38(10):5274-5291. doi: 10.1002/hbm.23734. Epub 2017 Jul 19.
Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc.
近红外光谱（NIRS）是一种便捷且安全的脑映射工具。然而，它不可避免地与大脑以外的血液动力学反应产生混淆，尤其是在前额颞部。一些研究人员试图通过与功能磁共振成像（fMRI）的同步测量来验证 NIRS 信号，但出人意料的是，NIRS 信号很少与 NIRS 通道中的局部 fMRI 信号相关，尽管这两种映射技术都应该测量相同的血红蛋白浓度。在这里，我们测试了一个新的假设，即头皮和脑组织内的不同体素可能具有明显不同的近红外光血红蛋白吸收率，这可能会导致通道之间的 NIRS 信号产生差异。因此，我们新应用了一种多变量方法，即偏最小二乘回归，用大脑和头部软组织内的 fMRI 的多体素信息来解释 NIRS 信号。我们同时在 9 名健康人类被试进行 n-back 任务时获取 fMRI 和 NIRS 信号。多元 fMRI 模型通过交叉验证非常成功地能够预测 NIRS 信号（组内相关系数 = ∼0.85）。这一结果证实了 fMRI 和 NIRS 确实测量了相同的血红蛋白浓度。蒙特卡罗置换检验的附加应用证实，该模型确实反映了时间和空间血液动力学信息，而不是随机噪声。在进行了彻底验证之后，我们计算了脑和软组织血液动力学对 NIRS 信号的贡献比例，发现实际上不同 NIRS 通道的贡献比例存在很大差异，这可能是因为额颞区域的结构复杂性。人类大脑映射 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc.
