Optical neuromonitoring provides insight into neurovascular physiology and brain structure and function. These methods rely on spectroscopy to relate light absorption changes to variation of concentrations of physiologic chromophores such as oxy- and deoxyhemoglobin. In clinical or preclinical practice, data quality can vary significantly across wavelengths. In such situations, standard spectroscopic methods may perform poorly, resulting in data loss and limiting field-of-view. To address this issue, and thereby improve the robustness of optical neuromonitoring, we develop, in this manuscript, novel methods to perform spectroscopy even when data quality exhibits wavelength-dependent spatial variation. We sought to understand the impact of spatial, wavelength-based censoring on the physiologic accuracy and utility of hemoglobin spectroscopy. The principles of our analysis are quite general, but to make the methodology tangible we focused on optical intrinsic signal imaging of resting-state functional connectivity in mice. Starting with spectroscopy using four sources, all possible subset spectroscopy matrices were assessed theoretically, using simulated data, and using experimental data. These results were compared against the use of the full spectroscopy matrix to determine which subsets yielded robust results. Our results demonstrated that accurate calculation of changes in hemoglobin concentrations and the resulting functional connectivity network maps was possible even with censoring of some wavelengths. Additionally, we found that the use of changes in total hemoglobin (rather than oxy- or deoxyhemoglobin) yielded results more robust to experimental noise and allowed for the preservation of more data. This new and rigorous image processing method should improve the fidelity of clinical and preclinical functional neuroimaging studies.

光学神经监测提供对神经血管生理学和大脑结构和功能的洞察。这些方法依靠光谱学将光吸收变化与生理生色团（如氧和脱氧血红蛋白）浓度的变化联系起来。在临床或临床前实践中，不同波长的数据质量可能会有很大差异。在这种情况下，标准光谱方法可能表现不佳，导致数据丢失和视野受限。为了解决这个问题，从而提高光学神经监测的稳健性，我们在这份手稿中开发了执行光谱学的新方法，即使数据质量表现出与波长相关的空间变化。我们试图了解空间、基于波长的审查对血红蛋白光谱的生理准确性和效用的影响。我们的分析原理非常笼统，但为了使该方法切实可行，我们专注于小鼠静息状态功能连接的光学固有信号成像。从使用四个来源的光谱学开始，使用模拟数据和实验数据在理论上评估了所有可能的子光谱矩阵。将这些结果与使用完整光谱矩阵进行比较，以确定哪些子集产生了稳健的结果。我们的结果表明，即使对某些波长进行审查，也可以准确计算血红蛋白浓度的变化和由此产生的功能连接网络图。此外，我们发现，使用总血红蛋白（而不是氧或脱氧血红蛋白）的变化产生的结果对实验噪声更加稳健，并允许保存更多数据。这种新的和严格的图像处理方法应该提高临床和临床前功能神经影像学研究的保真度。