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. Author manuscript; available in PMC: 2019 May 1.
Published in final edited form as: Neuroimage. 2018 Jan 4;171:148–164. doi: 10.1016/j.neuroimage.2018.01.002

Figure 9. Predicting Individual Differences in Performance.

Figure 9

Results of the leave-one-subject-out multiple linear regression analysis. (a) Pearson’s r correlation coefficient between the measured and predicted d′ score as a function of the number of features (connections) used in the model. (b) Scatterplot showing the relationship between the measured and predicted d′ scores for all 140 participants in the 18-feature regression model. (c). Figure showing the 25 connections selected at least once between the 10 nodes of the PPA, DMN, and DAN ROIs, and the VTC in the 18-feature regression model. The color and weight of the connection show the number of folds that each of the connections was selected as a feature in the prediction model (max = 140 folds).