I guess as long as the signal drop-out cuts just a small part of the brain, it is a consequence of susceptibility distortion that can be corrected in susceptibility distortion correction. However in a dataset gathering bad examples, I could witness some extreme signal drop-out cutting a significant part of the brain. Hence my interest to add it to the artifact list.
Head motion is manifesting in several ways, so I think distinguishing those could help retrieve more precise description of the reason of exclusion, when coming back to the dataset later. Furthermore, it could help us find more easily examples of specific artifacts we and others want to showcase or retrieve.
Peaks in slice-wise noise average may be more a consequence of an artifact that an artifact in itself I reckon.
Based on my observations in the bad quality dataset, I would like to propose some modifications of the list of artifacts that can be selected.
cc @oesteban