This plugin creates different maps showing
the displacement of each voxel during motion correction. These maps can
visualize the regional heterogeneity of the effect of head motion.
The calculation of the displacement is based on the motion parameters
estimated during motion correction, i.e. Translation X, Translation Y,
Translation Z, Rotation X, Rotation Y, Rotation Z. The displacement is
expressed in units of mm.
- FMR Intensity Threshold
- Only voxels above a certain FMR intensity threshold are taken into
account for the computation of the maps. The default threshold is set
to 100, which is the same default threshold used by BrainVoyager for
GLM calculation.
- Max Absolute Displacement
- Shows the maximum voxel displacement over all volumes to the
reference volume (over all directions: x, y, z).
Result: OriginalSDMName_3DMC_MaxAbsolute.map
- Mean Absolute Displacement
- Shows the mean voxel displacement over all volumes to the reference
volume (over all directions: x, y, z).
Result: OriginalSDMName_3DMC_MeanAbsolute.map
- Maximum Relative Displacement
- Shows the maximum voxel displacement from one volume to the next
volume (over all directions: x, y, z).
Result: OriginalSDMName_3DMC_MaxRelative.map
- Mean Relative Displacement
- Shows the mean voxel displacement from one volume to the next volume
(over all directions: x, y, z).
Result: OriginalSDMName_3DMC_MeanRelative.map
- Max Absolute Displacement X
- Shows the maximum voxel displacement over all volumes to the
reference volume in the x direction (left - right for axial slices).
Result: OriginalSDMName_3DMC_MaxAbsoluteX.map
- Max Absolute Displacement Y
- Shows the maximum voxel displacement over all volumes to the
reference volume in the y direction (inferior - superior for axial
slices).
Result: OriginalSDMName_3DMC_MaxAbsoluteY.map
- Max Absolute Displacement Z
- Shows the maximum voxel displacement over all volumes to the
reference volume across slices (anterior - posterior for axial
slices).
Result: OriginalSDMName_3DMC_MaxAbsoluteZ.map
References
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.