Papers of the Week

Head motion is a major confounding factor impairing the quality of functional magnetic resonance imaging (fMRI) data. In particular, head motion can reduce analytical efficiency, and its effects are still present even after preprocessing. To examine the validity of motion removal and to evaluate the remaining effects of motion on the quality of the preprocessed fMRI data, a new metric of group quality control (QC), dissimilarity of functional connectivity, is introduced. Here, we investigate the association between head motion, represented by mean framewise displacement, and dissimilarity of functional connectivity by applying four preprocessing methods in two independent resting-state fMRI datasets: one consisting of healthy participants (N = 167) scanned in a 3T GE-Discovery 750 with longer TR (2.5 s), and the other of chronic back pain patients (N = 143) in a 3T Siemens Magnetom Prisma scanner with shorter TR (0.555 s). We found that dissimilarity of functional connectivity uncovers the influence of participant's motion, and this relationship is independent of population, scanner, and preprocessing method. The association between motion and dissimilarity of functional connectivity, and how the removal of high-motion participants affects this association, is a new strategy for group-level QC following preprocessing.