Hi all,

for a later analysis where I extract ROIs with SPM, I need to concatenate
the resting state runs and want to make sure I'm doing it correctly. SPM
extracts the first eigenvariate of a ROI, i.e. the component that explains
the most variance.

I'm using the* Resting State fMRI 1 FIX-Denoised (Extended)* and *Resting
State fMRI 2 FIX-Denoised (Extended)* datasets.  That is, the
files: rfMRI_REST1_LR_hp2000_clean.nii, rfMRI_REST1_RL
_hp2000_clean.nii asf.

I chose the following approach:

1.  z-standardize each session (each voxel timecourse), i.e. RL, LR
2. Then concatenate them
3. Run the SPM routines which will also apply a high-pass filter of about
128s on the already concatenated data (it's for the processing of a DCM
rather than functional connectivity)

I have the following questions:

1. Is this approach correct?
2. Does the order of concatenation matter? That is, (RL/LR or LR/RL) or is
it important to concatenate it in the order it was acquired in each
subject? I read that it sometimes changes between subjects such that LR
came first in one subject and RL first in another.
3. Since SPM will run a hp-filter on the concatenated data, would it be
better to hp filter each run *separately* before concatenation?
4. Is this approach also applicable to the task data (i.e. standardize and
filter separately before concatenation)?

Thanks in advance


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