# Assessment of fNIRS Signal Processing Pipelines: Towards Clinical Applications
## 4 Discussion
When performing an assessment protocol in the context of a rehabilitation program, the activation of additional cortical areas as a supporting brain source to execute a task is the actual matter of research [59]. Emerging from our results (Section 3.5), the block-average response over the motor areas and the respective SNR across all subjects did not produce substantial differences among the different pipelines. This effect is mainly related to the correspondence between the functional task (i.e., motor grasping task) and expected elicited brain areas. In addition, these limited differences are mainly related to amplitude variations, which are not the principal purpose of the CW-fNIRS. Conversely, addressed features such as the temporal course, SNR, and statistical significance are seemingly not affected. Nevertheless, we suggest adopting preprocessing algorithms for MA reduction that present a channel-wise approach, such as SC-MARA, HybridMARA, TDDR, and Wavelet methods. Indeed, MC variants exert a more invasive interpolation over MA tracts, which may eliminate useful signals if occurring at high rates throughout the whole recording. SC-MARA and HybridMARA methods provide a higher SNR of block-averaged responses compared to TDDR and Wavelet over cerebral areas where we expect to have a significant activation. However, the TDDR and Wavelet methods have the advantage of requiring fewer input parameters and no adoption of user-defined thresholds compared with the SC-MARA and HybridMARA methods, hence promoting reproducibility of results. Therefore, when adopting SC-MARA and HybridMARA methods, which have comparable metrics to TDDR and Wavelet, researchers must clearly state their experimental set-up and adopted parameters [29]. The central issue concerning the adoption of different processing algorithms, especially for MAs, arises when inferring cortical activation over supplementary areas, here represented by non-motor areas. Indeed, while for HYA we could expect a correspondence between the task proposed and the activated areas, when pathological conditions occur, such a coherence is not assured and even not predictable. Another fascinating insight that emerged from our results is related to the ipsilateral hemodynamic response observed during the hand grasping. In ipsilateral motor areas, \(HbR\) remained stable at its baseline level, whereas the \(HbO_{2}\) level decreased (Figure 8). This phenomenon has already been observed in fMRI as Negative BOLD Responses (NBRs), but it is still debated and not fully understood, making such a mechanism not always directly interpretable. Recent studies have shown that multimodal integration could provide a complete perspective on this phenomenon [60]. Optical techniques could lead to a more comprehensive understanding of NBRs, even if such an approach is still limited in its methodological application [61]. This study presents some limitations that could be addressed with future methodological assessments. Namely, a further refined methodological approach will necessarily require the assessment of these algorithms through simulation of HRF superimposed on resting-state data [34]. A statistical comparison of activation maps concerning regression with short-separation channels will also give additional insights into the actual imbalance between proposed algorithms.