  The impact of in-scanner motion on functional magnetic resonance imaging
(fMRI) data has a notorious reputation in the neuroimaging community.
State-ofthe-art guidelines advise to scrub out excessively corrupted frames as
assessed by a composite framewise displacement (FD) score, to regress out
models of nuisance variables, and to include average FD as a covariate in
group-level analyses.
  Here, we studied individual motion time courses at time points typically
retained in fMRI analyses. We observed that even in this set of putatively
clean time points, motion exhibited a very clear spatiotemporal structure, so
that we could distinguish subjects into four groups of movers with varying
characteristics
  Then, we showed that this spatiotemporal motion cartography tightly relates
to a broad array of anthropometric, behavioral and clinical factors. Convergent
results were obtained from two different analytical perspectives: univariate
assessment of behavioral differences across mover subgroups unraveled defining
markers, while subsequent multivariate analysis broadened the range of involved
factors and clarified that multiple motion/behavior modes of covariance overlap
in the data.
  Our results demonstrate that even the smaller episodes of motion typically
retained in fMRI analyses carry structured, behaviorally relevant information.
They call for further examinations of possible biases in current
regression-based motion correction strategies.
