Pearson’s linear correlation (Spearman’s rank correlation in parentheses) coefficient tables (5 × 5 matrix each) were constructed for histological variables, the Nissl-positive neuron density, TH-positive neuron density, NM density, and iron pigment density, for the ROI-whole SN using the MATLAB Statistics Toolbox (The Mathworks Inc., USA) for each subject. Pearson’s linear partial correlation (Spearman’s rank partial correlation in parentheses) coefficients were also obtained to measure the degree of association between T2* values and each single histological variable with the effects of the other histological variables removed (NM with the effect of iron pigments removed in ROI-SNc, iron pigments with the effect of NM removed in ROI-whole SN, ROI-SNc, and ROI-SNr) using the MATLAB Statistics Toolbox. The coefficients of multiple correlations were calculated for each subject to study the association between the T2* values and all histological variables from the above correlation coefficient tables. From our multiple correlations study, we found that more than one variable, including the Nissl-positive neuron density, TH-positive neuron density, and NM density did not improve the coefficient of multiple correlations due to very high correlations among these three variables (see Supplementary Table S1). Therefore, only three variables (T2* value, NM density, and iron pigment density) were used for this study. Furthermore, to measure the independent contribution of iron and NM in T2* contrast, multiple regression β values for each subject were calculated with y = β0 + β1x1 + β2x2, where y, x1, and x2 correspond to is T2* values, NM, and iron density values, respectively.