Fig. 6: Relationship between edge strength of subgraph 4 and univariate task activations.
From: Functional brain network reconfiguration during learning in a dynamic environment
a Relationship between the activation for CPP and the edge strength of subgraph 4. We calculated the Pearson correlation coefficient between the z-statistic for CPP from McGuire et al. (2014) and the edge strength across nodes in subgraph 4. Each data point represents an ROI. The edge strength for each ROI was calculated as the column sum of that ROI’s edges to other ROIs, reflecting the summed interactions between that ROI and all others. The edges were normalized into the scale between 0 and 1. A significantly positive correlation was observed. The red line represents the regression line and the shaded area represents the 95% confidence interval. b Relationship between the activation for RU and the edge strength of subgraph 4. We observed a significant positive correlation between the z-statistic for RU from McGuire et al. (2014) and the edge strength across nodes in subgraph 4. The red line represents the regression line and the shaded area represents the 95% confidence interval. Source data of a, b are provided as a Source Data file. c Whole-brain thresholded activation maps for CPP and RU from McGuire et. al (2014) and whole-brain maps for edge strength of subgraph 4 in the current study.
