Table 2. Performance metrics for predictive models, predicting cognitive abilities from the 45 sets of neuroimaging features in the baseline data.

The metrics were averaged across test sites with standard deviations in parentheses.

Features	Correlation	$R^2$	MAE	RMSE
Neuroimaging	0.539 (0.073)	0.291 (0.082)	0.658 (0.039)	0.839 (0.05)
ENback 2back vs 0back	0.393 (0.048)	0.147 (0.042)	0.661 (0.038)	0.841 (0.045)
ENback 2back	0.367 (0.06)	0.128 (0.048)	0.667 (0.036)	0.848 (0.043)
rsfMRI temporal variance	0.3 (0.094)	0.09 (0.054)	0.728 (0.04)	0.921 (0.045)
rsfMRI cortical FC	0.299 (0.055)	0.088 (0.034)	0.734 (0.027)	0.929 (0.032)
ENback emotion	0.277 (0.06)	0.07 (0.041)	0.689 (0.031)	0.876 (0.035)
Cortical thickness	0.265 (0.1)	0.072 (0.055)	0.756 (0.026)	0.96 (0.03)
T2 gray matter avg intensity	0.264 (0.106)	0.069 (0.064)	0.752 (0.032)	0.953 (0.035)
T1 gray matter avg intensity	0.263 (0.103)	0.063 (0.071)	0.761 (0.033)	0.965 (0.039)
ENback 0back	0.261 (0.058)	0.061 (0.038)	0.688 (0.031)	0.878 (0.035)
T1 white matter avg intensity	0.26 (0.103)	0.067 (0.063)	0.76 (0.029)	0.963 (0.035)
rsfMRI subcortical-network FC	0.258 (0.083)	0.066 (0.043)	0.743 (0.033)	0.94 (0.035)
ENback place	0.239 (0.065)	0.049 (0.041)	0.695 (0.032)	0.886 (0.038)
T2 white matter avg intensity	0.238 (0.103)	0.056 (0.056)	0.756 (0.03)	0.96 (0.031)
T2 normalised intensity	0.236 (0.082)	0.057 (0.041)	0.755 (0.021)	0.96 (0.024)
DTI	0.23 (0.074)	0.042 (0.048)	0.762 (0.027)	0.967 (0.029)
Cortical volume	0.228 (0.095)	0.053 (0.044)	0.767 (0.02)	0.971 (0.024)
MID Small Rew vs Neu anticipation	0.223 (0.049)	0.048 (0.022)	0.743 (0.017)	0.938 (0.02)
Cortical area	0.218 (0.101)	0.049 (0.046)	0.768 (0.021)	0.973 (0.025)
T1 normalised intensity	0.215 (0.109)	0.047 (0.049)	0.769 (0.022)	0.974 (0.028)
MID Reward vs Neutral anticipation	0.214 (0.062)	0.043 (0.028)	0.745 (0.022)	0.944 (0.024)
MID Loss vs Neutral anticipation	0.214 (0.075)	0.043 (0.034)	0.745 (0.025)	0.944 (0.028)
MID Small Loss vs Neu anticipation	0.203 (0.073)	0.038 (0.03)	0.747 (0.026)	0.945 (0.026)
MID Pos vs Neg Punishment Feedback	0.202 (0.066)	0.037 (0.027)	0.745 (0.021)	0.945 (0.026)
T1 subcortical avg intensity	0.2 (0.087)	0.037 (0.043)	0.773 (0.023)	0.979 (0.026)
MID Large Rew vs Neu anticipation	0.2 (0.072)	0.037 (0.03)	0.747 (0.021)	0.946 (0.024)
MID Pos vs Neg Reward Feedback	0.198 (0.05)	0.036 (0.02)	0.748 (0.022)	0.945 (0.028)
T1 summations	0.196 (0.08)	0.009 (0.059)	0.784 (0.029)	0.992 (0.033)
Sulcal depth	0.18 (0.095)	0.032 (0.039)	0.777 (0.02)	0.984 (0.026)
MID Large Loss vs Neu anticipation	0.173 (0.066)	0.026 (0.026)	0.749 (0.022)	0.95 (0.025)
subcortical volume	0.17 (0.078)	0.028 (0.029)	0.775 (0.018)	0.982 (0.021)
SST Any Stop vs Correct Go	0.164 (0.065)	0.022 (0.025)	0.736 (0.038)	0.935 (0.043)
T2 subcortical avg intensity	0.158 (0.057)	0.023 (0.023)	0.77 (0.018)	0.977 (0.02)
ENback Face vs Place	0.148 (0.076)	0.014 (0.028)	0.712 (0.027)	0.904 (0.034)
SST Incorrect Stop vs Correct Go	0.147 (0.059)	0.017 (0.02)	0.738 (0.035)	0.937 (0.04)
SST Correct Stop vs Correct Go	0.145 (0.056)	0.017 (0.018)	0.739 (0.033)	0.936 (0.038)
SST Correct Go vs Fixation	0.145 (0.053)	0.017 (0.017)	0.74 (0.033)	0.938 (0.036)
MID Large Rew vs Small anticipation	0.133 (0.05)	0.015 (0.014)	0.757 (0.022)	0.956 (0.025)
T2 summations	0.114 (0.053)	0.008 (0.022)	0.777 (0.018)	0.984 (0.016)
SST Incorrect Go vs Correct Go	0.11 (0.061)	0.008 (0.015)	0.744 (0.034)	0.94 (0.038)
SST Correct Stop vs Incorrect Stop	0.096 (0.068)	0.005 (0.018)	0.744 (0.033)	0.943 (0.036)
MID Large vs Small Loss anticipation	0.093 (0.063)	0.006 (0.014)	0.756 (0.024)	0.96 (0.026)
SST Incorrect Go vs Incorrect Stop	0.061 (0.039)	0 (0.008)	0.744 (0.032)	0.943 (0.036)
ENback Positive vs Neutral Face	0.024 (0.06)	–0.007 (0.012)	0.716 (0.027)	0.908 (0.034)
ENback Emotion vs Neutral Face	0.019 (0.058)	–0.007 (0.01)	0.716 (0.026)	0.908 (0.033)
ENback Negative vs Neutral Face	0.002 (0.058)	–0.007 (0.009)	0.718 (0.024)	0.911 (0.03)

R²=coefficient of determination; MAE = mean-absolute error; RMSE = root mean square error.