DySCo: A general framework for dynamic functional connectivity
Fig 6
Application of DySCo to HCP dataset (all subjects).
A: i) The task structure (gray line), and the HRF convolved task timecourse, in orange (see HCP task fMRI data). ii) Shows the mean reconfiguration speed (green) standard error (shaded) calculated from the obtained eigenvalues across 100 subjects with a window size of 21. The dashed line again shows the task timecourse of the HCP n-back task (r = –0.46, p < 0.001). iii) Shows the mean von Neumann Entropy (blue) standard error (shaded) calculated from the obtained eigenvalues across 100 subjects. The dashed line shows the Task timecourse of the HCP n-back task (r = 0.76 , p < 0.001). iv) Shows the FCD matrix averaged across all subjects. The entry ij of the FCD matrix (see Distances between dFC operators) represents the distance 2 between the dFC matrix at time and the dFC matrix at time
. B: To give an example of evolution in time of the sliding window correlation matrices, we show them by using their first 3 eigenvectors (averaged across all subjects). We display the first half of the recording to maximise space for brain rendering.