In many studies, diffusion tensor imaging (DTI) measures, such as fractional anisotropy (FA), of white matter structures are compared between groups, such as different age groups or healthy controls vs patients. The observed differences in these measures, however, may not always be due to biologically related processes, but may originate from group differences in physiological characteristics during acquisition, something already well-studied in the fMRI society [1]. While for diffusion MRI several processing steps have been optimized [2] [3], a recent study with real data showed that FA group differences could still be observed simply based on differences in subject motion between the groups [4]. In this simulation study, we explored whether this confound can be explained by the concomitant change in distribution of diffusion gradient orientations due to the required “B-matrix rotation” during subject motion [5]. We also investigated how the introduced angular bias due to subject motion compares to another well-known confound, the noise bias. Subject motion trajectories were simulated along all three coordinate axes to mimic the slow drift of head motion. These trajectories were defined as described previously in [5], where the average absolute angular difference (represented by D), a measure that quantifies the amount of subject motion (rotation only), was varied from 0° (i.e., no subject motion) to 5° (typically considered as a lot of subject motion) and subsequently quantified in steps of 0.5° (500 trajectories per step and per axis). Other simulation settings were defined in line with current acquisition settings for typical DTI studies: 60 diffusion gradient directions distributed isotropically on the unit half-sphere [6]; the mean diffusivity (MD) of the diffusion tensor is 0.7×10-3 mm2/s; the FA was set between 0.2 to 0.8; and the b-value was set at 1000 s/mm2. For each motion trajectory, Rician noise was added (100 instances) with SNR levels equal to 10, 20, 30, 40, and 50. To investigate the relative contribution of the noise bias with respect to the angular bias induced by subject motion, we also simulated diffusion signals as described above, but then without adding this angular bias (i.e., as if there was no subject motion). Mean, standard deviation, coefficient of variation (COV), and percentage difference of FA estimates are computed and evaluated as function of SNR level and amount of subject motion (D).Figure 1 shows that for a small amount of subject motion (average D = 1°), the introduced angular bias does not add significantly to the noise bias, even at high SNR levels. By contrast, for higher degrees of subject motion (average D = 4°) the angular bias becomes more apparent (Figure 2), especially at higher SNR levels (e.g., see Figure 2a and 2d). Figure 3 shows the estimated FA percentage difference as a function of D for a simulated diffusion tensor with FA = 0.8. One can clearly appreciate that for higher amounts of subject motion, the angular bias becomes more dominant, with a net result of nearly 2% difference for the largest values of D compared to the case without subject motion. Figure 4 shows the COV of the FA percentage difference demonstrating the difference in relative variability between the estimated FA values with and without the induced angular bias. Our main finding is that the underestimation and variance of FA due to motion depends on the underlying FA value and the SNR level. At low SNR levels, the noise will swamp the effects of diffusion gradient imperfections, whereas at higher SNR levels, these disturbances become more apparent and will act as a confounding factor by introducing an additional increase in bias and variability, becoming more dominant with larger amounts of subject motion. Note that this finding is in line with a similarly observed underestimation of FA as reported in work on non-perfect gradient distributions [7]. Our study demonstrates that confounds in FA can be explained by associated changes in the distribution of diffusion gradient orientations due to subject motion.