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. Author manuscript; available in PMC: 2018 Jan 15.
Published in final edited form as: Neuroimage. 2016 Mar 23;145(Pt B):365–376. doi: 10.1016/j.neuroimage.2016.03.038

Figure 2.

Figure 2

Plot used to parameterize the simulation. This shows the relationship between final Measured Correlation, Power-Ratio (PR) and correlation between artificial signals. The plot uses two different time-courses: TC1 and TC2. These time-courses were extracted from fMRI data for two different RSNs using space-time-regression. The two time courses exhibit low correlation value. Two signals, S1 and S2, are algorithmically generated to have an artificial correlation Art.Corr[S1,S2] with different values 1.0, 0.5, 0.2 and 0.1. Signals and time courses are mixed and the measured correlation corr[TC1+S1, TC2+S2] is plotted for different, PR = (var[S]/var[TC]). After 0dB, Art.Corr dominates the measured correlation, but below −12dB its influence is minimal. The simulation was performed with PR = −9dB, aiming at minimizing changes in the characteristics of original time courses TC1 and TC2, but allowing a significant correlation level of 0.2. In our data, significant correlations (p<0.05) are those surpassing the threshold of 0.16.