X |
Wide numeric data matrix (T observations by V variables , T << V ).
For example, if X represents an fMRI run, T should be the number
of timepoints and V should be the number of brainordinate vertices/voxels.
Or, a 4D array or NIFTI or file path to a NIFTI (I by J by K by T
observations), in which case ROI_data must be provided.
(The vectorized data will be T timepoints by V_{in-mask} voxels )
Or, a ciftiTools "xifti" object or a file path to a CIFTI
(The vectorized data will be T timepoints by V_{left+right+sub} grayordinates ).
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ROI_data |
Indicates the data ROI. Allowed arguments depend on X :
If X is a matrix, this must be a length V logical vector, where
the data ROI is indicated by TRUE values. If "infer" (default), all
columns of X will be included in the data ROI (rep(TRUE, V) ).
If X is an array or NIFTI, this must be either a vector of values
to expect for out-of-mask voxels in X , or a (file path to a) 3D NIFTI.
In the latter case, each of the volume dimensions should match the first
three dimensions of X . Voxels in the data ROI should be indicated by
TRUE and all other voxels by FALSE . If "infer" (default),
will be set to c(0, NA, NaN) (include all voxels which are not constant
0 , NA , or NaN ).
If X is a "xifti" this must be the brainstructures
argument to read_cifti . If "infer" (default),
brainstructures will be set to "all" (use both left and right
cortex vertices, and subcortical voxels).
If NULL , the data ROI will be empty. This is useful for obtaining just
the noise ROI, if the data and noise are located in separate files.
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ROI_noise |
Indicates the noise ROIs for aCompCor. Should be a list where
each entry corresponds to a distinct noise ROI. The names of the list should
be the ROI names, e.g. "white_matter" and "csf" . The expected
formats of the list entries depends on X :
For all types of X , ROI_noise entries can be a matrix of noise
ROI data. The matrix should have T rows, with each column being a
data location's timeseries.
If X is a matrix, entries can also indicate a noise ROI within X .
These entries must be a length V logical vector with TRUE values
indicating locations in X within that noise ROI. Since the ROIs must
not overlap, the masks must be mutually exclusive with each other, and with
ROI_data .
If X is an array or NIFTI, entries can also indicate a noise ROI within X .
These entries must be a logical array or (file path to) a 3D NIFTI with the
same spatial dimensions as X , and with TRUE values indicating
voxels inside the noise ROI. Since the ROIs must not overlap, the masks must
be mutually exclusive with each other, and with ROI_data .
(If X is a "xifti" , entries must be data matrices, since no
grayordinate locations in X are appropriate noise ROIs).
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