800 subjects had a valid Noise_Comp measure.
Multivariate prediction (GLM-based, automatic feature selection, leave-one-family-out prediction)
Original data space: r=0.31 CoD=0.08 Deconfounded space: r=0.25 CoD=0.04
Scatterplot shows predicted-Noise_Comp vs measured-Noise_Comp (in original and deconfounded data space).
Univariate regression (regressing each netmat element independently against Noise_Comp, correcting for multiple comparisons across elements, using PALM permutation testing, taking into account family structure).
Number of significantly correlated edges at p<0.05 (two-tailed, FWE corrected) = 4 (minimum corrected p = 0.0032)
Number of significantly correlated edges at p<0.05 (two-tailed, uncorrected) = 463 (248 expected by chance)
Image shows edges (node-pairs) whose connection most strongly correlates with Noise_Comp (in decreasing order), with t-statistic listed at the top of each node-pair.
