Fig 1.
Average connectivity matrices from all subjects for each scanning session (Time 1 and 2 in Scanner A represent measures from the same MRI scanner in different time points, and Time 1 in Scanner B represents a third measure from a different MRI scanner).
Each matrix element represents the weighted connectivity between the ROIs indicated by the column and by the row. The color bars indicate log(weighted connectivity).
Fig 2.
Each matrix entry represents the ICC observed for the white matter link between the gray matter ROI in the row and the gray matter ROI in the column.
Fig 3.
This figure demonstrates each connectome link represented by a line corresponding to the center of mass of the bundle of fibers associated with that link (estimated from deterministic tractography).
Each link is color-coded based on its reproducibility per tractography approach and scanner usage. The colorbars indicate the link-wise ICC.
Fig 4.
This figure demonstrates the association between the anatomical properties of each link and link-wise reproducibility.
The anatomical properties are Euclidian distance between connected gray matter ROIs, sum of the volume of the connected ROIs and the ratio of the volumes between the connected ROIs. Link-wise reproducibility is determined by ICCs. The scatter plots demonstrate each anatomical property in the y-axis, and the ICCs in the x-axis. The statistical relationship between these measures is defined by a correlation coefficient, whose details are displayed below each scatter plot.
Fig 5.
The scatter plots demonstrate the relationship between link-wise graph theory metrics obtained from connectomes calculated from scanning session in time 1 (x-axis) and in time 2 (y-axis) within the same MRI scanner.
The scale set for the x-axis is the same as for the y-axis for all graphs. The ICC between each pair of measurements is displayed below each scatter plot. Of note, the relationship between degrees was not assessed for probabilistic tractography given the low sparsity of networks generated from probabilistic methods, therefore leading to a ceiling degree effect.
Fig 6.
The scatter plots demonstrate the relationship between link-wise graph theory metrics across different scanners (Time 1, Scanner in x-axis and Time 1 Scanner B in y-axis).
The ICC between each pair of measurements is displayed below each scatter plot. Similarly, the relationship between degrees was not assessed for probabilistic tractography given the low sparsity of networks generated from probabilistic methods, therefore leading to a ceiling degree effect.