Figure 1:

The fMRI missing ness problem. The standard approach in fMRI group statistics is to omit voxels from tests that do not contain observations from every subject. Omitting partial datasets from analysis is costly to spatial coverage, particularly along edges of the brain. In cross-sectional views (columns: axial, sagittal, and coronal planes), group-level statistics would be affected by missing data across subjects. A) Observed cases (top row) and B) missing cases (bottom row) show the number of individuals with data in each voxel after spatially normalizing an fMRI dataset. The colour scale and labelled contour lines indicate the number of (A) observed or (B) missing cases for each voxel, from a sample of 49 total study participants. Most missing data was due to susceptibility artefact and scanner operators who were inconsistent in their placement of an image acquisition bounding box that had limited brain coverage.