## 4 Discussion  
[PERSON] et al. [46] showed that the performance of spectroscopic analysis can be improved by increasing the number of wavelengths of illumination. The results of our study are consistent with [PERSON] et al. 's results; see Figure 6. The simulation-based method presented in this paper aimed to identify the optimal spectral combination of our hyperspectral camera for the brain hemodynamic and metabolic monitoring. When the spectral bands are corrected, the optimal spectral configuration is composed of 21 and 22 spectral bands; see Figure 7. This configuration could be however reduced from 10 to 12 spectral bands while keeping fairly constant performances. We can observe a plateau in the quantification errors of \(\Delta C_{HbO_{2}}\) when 10 or more spectral bands are used. We also can observe a plateau in the quantification errors in \(\Delta C_{Hb}\) and \(\Delta C_{oxCCO}\) when 12 or more spectral bands are used; see Figure 6. This reduction of the number of the spectral bands could be interesting for the real-time computation of hemodynamic and metabolic brain maps in the operative room using commercial hyperspectral cameras and for the conception of dedicated cameras used in functional brain mapping studies. In this study, the optimal spectral configurations were obtained by searching the three chromophores deconvolution systems that minimize the quantification errors in \(\Delta C_{HbO_{2}}\), \(\Delta C_{Hb}\), and \(\Delta C_{oxCCO}\). Therefore, three different spectral configurations were obtained for the deconvolution of the three chromophores. These spectral configurations, as well as the reference configuration identified by [PERSON] et al. [23] and [PERSON] et al [27] are represented in Figure 14.  
The comparison between the spectral configuration identified by [PERSON] and al. and ours is not trivial since our hyperspectral camera does not acquire exactly the same wavelengths; see Figure 2. There are some similarities between the wavelengths used in our system and in the system of [PERSON] et al. Indeed, between 780 nm and 900 nm, some wavelengths correspond. Our system also used others wavelengths inferior to 780 nm (703, 754, and 767 nm) and superior to 900 nm (916, 929, 937, 947, 953, and 958 nm). The quantification of \(\Delta C_{HbO_{2}}\), \(\Delta C_{Hb}\), and \(\Delta C_{oxCCO}\) computed with the optimal spectral bands of our hyperspectral camera are consistent with those computed with 121 wavelengths included between 780 nm and 900 nm [23] and with those computed with the eight wavelengths identified by [PERSON] et al. [27]. For a two-chromophore deconvolution system, the quantification error in \(\Delta C_{HbO_{2}}\) measured with our system is equivalent to those measured with 121 wavelengths. However, the choice of our spectral bands aims to reduce the quantification error in \(\Delta C_{Hb}\); see Figure 10. For a three-chromophore deconvolution system, the quantification errors measured with our system are a little higher than those measured with 121 wavelengths or with [PERSON] et al. 's wavelengths; see  
Figure 14: Peaks of spectral bands that minimize the quantification errors in \(\Delta C_{HbO_{2}}\), \(\Delta C_{Hb}\) and \(\Delta C_{oxCCO}\). The spectral configuration identified by [PERSON] et al. [23] and [PERSON] et al. [27] are also indicated. Figure 12. This difference may be explained because the illumination and the acquisition of the 121 wavelengths of reference, as well as the eight wavelengths identified by [PERSON] et al. were simulated as ideal sources and detectors. This means that for these simulations, the term \(D\times S\) in Equation (7) is equal to one. To efficiently compare our spectral configuration with these spectral configurations of reference, the spectral sensitivities of the detectors and the illumination sources have to be considered. However, the acquisition condition is different since we acquired the intrinsic signal of an exposed cortex, whereas the wavelengths identified in [PERSON] et al. 's and [PERSON] et al.