ddmra.analysis.highlow_analysis

highlow_analysis(mean_qcs, corr_mats)[source]

Perform high-low QC analysis.

Parameters

  • mean_qcs (numpy.ndarray of shape (n_subjects,)) – QC measure (typically mean framewise displacement) across participants.

  • corr_mats (numpy.ndarray of shape (n_subjects, n_edges)) – Z-transformed correlation coefficients for ROI-ROI pairs. n_edges is the unique ROI-to-ROI edges, not including self-self edges. These coefficients must be sorted according to ascending distance along the second axis.

Returns

hl_corr_diff (numpy.ndarray of shape (n_edges,)) – ROI-ROI pair difference scores.

Notes

The basic process for the high-low analysis is:

  1. Average QC values within each participant.

  2. Split the participants into high-QC and low-QC groups using a median split.

  3. Calculate the average z-transformed correlation coefficient for each group.

  4. Subtract the low group’s value from the high group’s value, for each ROI-ROI pair.