Figure 4

(a) Examples of principal component analysis (PCA) derived scatter plots that show significant clustering between control-like and hypoactive and control-like and hyperactive behaviors from metal combination inputs of Cr, Mn, Fe, Se, Cd, Sb, Ba, Pb, & U (combination 162) and Fe, Ni, Cu, Se, Pb, & U (combination 3921) respectively. (b) Dot plot representing the percent prevalence of a given metal in mixtures that resulted in significant clustering between control-like and hyperactive (red) as well as control-like and hypoactive (blue) behavior. (c) Bar graphs representing the top 15 combinations of two or three metals within mixture subsets that resulted in significant clustering between control-like and hypoactive and control-like and hyperactive behavior. Clusters were created via PCA and an F-statistic was calculated to determine significance, p value < 0.005.