## 4 Discussion  
Finger-tapping tasks are widely utilized in neuroimaging studies to investigate somatosensory and motor functions. This choice is primarily due to the higher amplitude of cerebral activations observed during finger tapping compared to other paradigms, such as cognitive tasks. Additionally, the spatial distribution of cerebral activations elicited by finger tapping is well established and reproducible. Firstly, creating a functional-ROI, in contrast to using structural-ROI, is based on anatomy to mask the background signals that are mixed with external layers (skull and scalp). The results presented here demonstrate that applying functional-ROI to DOT volumes enables the attainment of precise cerebral activation information at the level of the gyri. This approach effectively eliminates extracerebral signals and does not rely on structural anatomy, which can be particularly challenging in situations where MRI devices are unavailable. A functional-ROI analysis may reveal shared neurovascular coupling mechanisms involved in both synchronized spontaneous and task-related activities. Here, we demonstrate the strong reliability of functional-ROI analysis when applied to DOT volumes by comparing it with fMRI volumes. As we expected, the outcomes obtained from the GLM analysis using a structural-ROI (Figure 1) align with previous research conducted on both fMRI and DOT datasets [4]. These studies have specifically focused on the sensory-motor cortices, namely the pre- and post-central gyri. Furthermore, the functional-ROI analysis (Figure A2) also aligns with previous fMRI studies [17; 19] that have investigated sensorimotor areas during finger movements. Secondly, the results obtained from the GLM analysis using a functional-ROI reveal detailed cortical activation patterns in the pericentral motor and somatosensory cortices during task performance (Figure 5). Previous fMRI studies have demonstrated that these func  
Figure 5: T-contrast maps measured by DOT and fMRI devices in a subject group (N = 9) on the left hemisphere localized on the postcentral gyri (**upper** figure) and the precentral gyri (**bottom** figure). All results were mapped onto a standard space (MNI) and statistically analyzed by GLM using a structural-ROI (**left** images) and GLM using a functional-ROI (**right** images). FWER threshold \(p<0.05\) at the voxel level for motor execution > rest contrast. BOLD (green), HbR (blue) and HbO (red) signals are displayed in coronal view. tional maps bear striking similarity to [PERSON]'s electrophysiological maps, suggesting that non-invasive techniques can access the homuncular organization in healthy adults [20, 21]. The findings presented in this study validate similar approaches utilizing high-density optical imaging [18]. By combining a functional-ROI approach with a model-driven analysis (GLM), it becomes possible to accurately localize major cerebral activations in the pre- and postcentral gyri across a group of subjects while they perform contralateral movements, using both neuroimaging technologies. This methodology yields a spatial distribution of activations that aligns with the anatomical homuncular organization in the pre- and postcentral gyri. It is important to note that in this study, individual finger movements cannot be distinguished. However, the results demonstrate the spatial localization of general finger movements, which is consistent with a recent study presenting an integrated-isolate model of action and motor control [22]. A notable inconsistency in this study is the dissimilarity in spatial distribution patterns between DOT and fMRI, which exhibit differences in voxel activation. These inconsistencies in hemodynamic behavior are explained by the neurovascular coupling. Initially, when neuronal activity begins, there is an increase in HbR due to the initial consumption [23] of oxygen.