The general consistency between NIRS signals and blood oxygenation level dependent signals has been shown in studies on task-evoked brain activation and resting-state functional connectivity,24–26 validating NIRS as a neuroimaging tool. However, a major issue for NIRS is to what extent the deep tissue (such as cerebral tissue), as opposed to shallow-tissue (extracerebral tissue, such as the scalp), contributes to the measured signals of oxygenated and deoxygenated hemoglobin (oxy- and deoxy-Hb). Task-evoked and/or spontaneous changes in skin blood flow due to systemic effects can mask changes in cerebral oxygenation in relation to neural activation.27–31 Previous studies have examined the effects of the shallow tissue on NIRS signals in adults by means of additional channels with short source-detector (S-D) distances under the assumption that the short distance channels measure signals only from the shallow tissue.32,33 Time-domain NIRS has also been used to separate deep- from shallow-tissue signals.34,35 Simultaneous recordings of NIRS with cutaneous laser-Doppler blood flow have shown that the scalp blood flow contributes to the changes in NIRS signals.29,36 The separation of deep- from shallow-tissue signals has also been performed by time-series analysis, such as adaptive filtering37 or independent component analysis (ICA).38 Most of the aforementioned studies assumed either the spatially homogeneous properties of systemic effects on the shallow tissues or the independence of temporal evolution of the deep and shallow signals. However, the assumptions might be violated if the systemic effects induced by tasks can locally affect the blood flow and oxygenation in both deep- and shallow tissues. Kirilina et al.39 used NIRS, functional magnetic resonance imaging (fMRI), MR-angiography, blood pressure, heart rate, skin conductance, and skin blood flow to study activation in the frontal cortex during a cognitive task and demonstrated that cognitive tasks strongly affect the blood volume of veins draining the scalp and that NIRS signals contain the task-evoked systemic artifacts. Funane et al.40 proposed a method to discriminate between the deep- and shallow-tissue effects on the NIRS signal using multiple-distant (MD) probes and an ICA.41,42 Importantly, the MD-ICA method can be used to decompose NIRS signals even when the cerebral and extracerebral signals correlate.