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. 2019 Feb 11;13:21. doi: 10.3389/fncel.2019.00021

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Copyright © 2019 Savini, Pardini, Castellazzi, Lascialfari, Chard, D’Angelo and Gandini Wheeler-Kingshott.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Scatter plots representing SDMT vs. GE (CBL-DMN) for HC (left), CPMS (center), and CIMS (right). Solid black lines represent the linear regression model fit, while dashed red lines represent 95% confidence intervals. It is noteworthy that GE (CBL-DMN) predicts SDMT performance progressively better going from HC (no significant correlation) to CPMS (ρ = 0.51, p < 0.001) to CIMS (ρ = 0.87, p < 0.001). The difference between correlation coefficients for CPMS and CIMS is statistically significant (p < 0.01), as verified by applying Fisher z-transformation.