## 5 Results and Discussion  
To demonstrate how the phantom shape in concurrent EEG-fMRI recording affected the induced GA that confounded the EEG data inside the MR scanner, the average contribution of the RMS voltage for each orthogonal gradients was mapped to a 2D spatial voltage representation, as shown in Figure 7. The potential map of the RL gradient of the spherical phantom showed that the frontal, fronto-central, and temporal lobe electrodes contributed to the largest negative voltages, whereas the occipital and parietal lobe electrodes contributed to the largest positive voltages, respectively. However, the potential maps of the RL gradient of the head-shaped phantom and subjects were significantly different from the spherical phantom's fronto-parietal and parietal lobe electrodes data. In the case of the AP gradient, which is one of the largest artefact-contributing gradient, as shown in previous work by one of this study's authors [15], the largest positive and negative voltages were recorded in the right and left side of the head-shaped phantom and human subjects. However, the left temporal and parietal lobes of the spherical phantom showed the largest negative voltage contribution. In the FH gradient, there were significant variations reported in previous works [15; 19; 24] due to the variation of the subjects' head positions and shapes in the MR scanner bore. In addition, the patterns of the potential maps (induced voltage distribution) of the FH gradient for the head-shaped phantom and human subjects were similar, whereas the map for the spherical phantom was significantly different (Figure 7). Although it was observed that the head-shaped phantom's spatial map was very similar to that of the subjects for each orthogonal gradient, it was necessary to quantify this similarity using a mathematical method. The SSIM variation is shown in Figure 8 for each gradient to the compare head-shaped phantom with the spherical phantom in reference to the human subjects. The SSIM was significantly higher (average value, 0.85) for the head-shaped phantom in comparison to the spherical phantom (average value, 0.68) (Figure 8). Interestingly, it was observed that the difference of potential map between the head-shaped phantom and the spherical phantom for the FH gradient was significantly high (Figure 7), but the SSIM value did not reflect this difference. This was due to the variations in the range of the potential for the spherical phantom (i.e., there were several electrodes that contributed to high positive and negative potentials); however, this did not occur for most of the electrodes. It is also important to note that the observed variations of the SSIM values reflected by the error bar in Figure 8, show that the SSIM values varied more significantly for the spherical phantom than for the head-shaped phantom. -phantom data, although the standard deviations for subjects' data re significantly higher than those of the head-shaped phantom data. This could be explained easily by considering the pulse artefacts and small involuntary movements of subjects' head during data acquisition, in addition to the brain signal. Moreover, in the different sessions, even though the subjects were set in the +4 cm axial position inside the scanner, the shape and orientation of the heads did not match completely, which, we believe, greatly contributed to the variation of the standard deviations. To mimic the variation of the orientations of human's head in different sessions, we took the head-shaped phantom out of the scanner bore and returned it to its position (+4 cm axial position) in different trials, thus slightly altering its orientation. Even though the shape of the phantom remained the same, and no PA and MA occurred in the head-shaped phantom, the observed standard deviation in the head-shaped phantom was due to the altered orientation in different trials.