tab of this plugin allows to create different
motion confound models based on the motion parameters estimated during
motion correction. Please note that all models, but the design matrix with
the spike predictors, are z-transformed before saved to disk.
In addition, two plots can be generated per functional run:
- a line plot showing the estimated motion parameters

- a line plot showing the detrended motion parameters as well
as the motion spike detection threshold and the detected spikes

References
Power, J.D., Mitra, A., Laumann, T.O., Snyder, A.Z., Schlaggar, B.L.,
and Petersen, S.E. (2014). Methods to detect, characterize, and remove
motion artifact in resting state fMRI. Neuroimage 84, 320–341.
Satterthwaite, T.D., Elliott, M.A., Gerraty, R.T., Ruparel, K.,
Loughead, J., Calkins, M.E., Eickhoff, S.B., Hakonarson, H., Gur,
R.C., Gu,r R.E., and Wolf, D.H. (2013). An improved framework for
confound regression and filtering for control of motion artifact in
the preprocessing of resting-state functional connectivity data.
NeuroImage 64, 240-256.