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. Author manuscript; available in PMC: 2017 Feb 1.
Published in final edited form as: J Neurosci Methods. 2015 Nov 28;259:22–39. doi: 10.1016/j.jneumeth.2015.11.011

Figure 9. Detected disruptions across functional networks in schizophrenia differ between covariance and correlation.

Figure 9

A) Here we show altered covariance structure between large-scale associative networks in schizophrenia (SCZ), similar to recent findings (Baker et al. 2014) [t(143)=2.37, p=0.019, Cohen’s d=0.4]. B) We recently discovered elevated variance across the entire brain in chronic SCZ, which was particularly evident for associative networks (Yang et al. 2014). C) Based on this elevated non-shared variance, it follows that the difference in correlations between SCZ and healthy control subjects (HCS) across the two networks will be attenuated and no longer reveal a significant clinical effect [t(143)=1.48, p=0.14, Cohen’s d=0.25]. The equation on the bottom is presented for illustrative purposes, to highlight the importance of carefully decomposing the final correlation into variance and covariance components (Figure 3). FPCN, fronto-parietal control network; DMN, defaultmode network.