- Input
- Any _3DMC.sdm file or for batch processing a _3DMC.mdm file that lists all _3DMC.sdm files of interest. Please note that the resulting files are saved in the same directories as the original _3DMC.sdm files. The time course data in the MDM is ignored.
- Spikes
- This option detects time points in the data series that show spikes
in the motion pattern, calculated based on the unmodified motion
parameters. A design matrix is created with stick predictors at the
time points of the motion spikes. For motion spike detection the root
mean square displacement from one volume to the next volume is
calculated. The detected spikes in the motion parameters are dependent
on the relative RMS displacement threshold (or spike detection
threshold), which can be defined by the user.
Result: OriginalSDMName_3DMC_spikes.sdm
- Detrended
- This option creates a set of detrended motion parameters and saves
them to a new design matrix file.
Result: OriginalSDMName_3DMC_detr.sdm
- Detrended Derivative
- This option creates the temporal derivative of each motion parameter
and saves them to a new design matrix file. The average of the
parameter change with respect to the previous and to the next volume
is taken as the derivative.
Result: OriginalSDMName_3DMC_deriv.sdm
- Detrended Squared
- A new set of motion regressors is created representing the quadratic
term of the detrended original parameters.
Result: OriginalSDMName_3DMC_sqr.sdm
- Detrended Delayed 1TR
- A new set of motion regressors is created representing the original
motion parameters shifted 1 TR.
Result: OriginalSDMName_3DMC_t1.sdm
- Detrended Delayed 2 TRs
- A new set of motion regressors is created representing the original
motion parameters shifted 2 TRs.
Result: OriginalSDMName_3DMC_t2.sdm
- Detrended Delayed 1TR Squared
- A new set of motion regressors is created representing the original
motion parameters shifted 1 TR and squared.
Result: OriginalSDMName_3DMC_t1sqr.sdm
- Detrended Delayed 2TRs Squared
- A new set of motion regressors is created representing the original
motion parameters shifted 2 TRs and squared.
Result: OriginalSDMName_3DMC_t2sqr.sdm
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.
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.