I’m currently very new to fMRI and still trying to figure out the basics. Neverthless, my thesis project calls for high resolution data to look at subcortical structures. We are trying some highly exploratory sequences to maximize our imaging capacity (especially at the anatomical level). I’ve got the following files: Anatomical
t1w mprage image with nonlinear gradient correction
t1w mprage image without nonlinear gradient correction
t2star megre image
multi-echo t2star megre image
multi-echo t2star megre phase images
Field Maps
b1 flip angle map (flip angle 90)
b1 anatomical map (flip angle 90)
b1 flip angle map (flip angle 10)
b1 anatmical map (flip angle 10)
mbep2d_SE 1.4mm (direction AP)
mbep2d_SE 1.4mm (direction PA)
mbep2d_SE 1.9mm (direction AP)
mbep2d_SE 1.9mm (direction PA)
gre field mapping (phase only)
I’m not really sure what the main differences are between these files are, and I don’t know whether fMRIPrep handles them or how. I’m hoping maybe someone can shed light on the following:
What are the main differences between these different files wnad why are they useful?
Does fMRIPrep handle all of these file types?
How should they be properly formatted in BIDS so that fMRIPrep can read the necessary information for the relevent files.
Are there are specific things I need to do within .json files or within the fMRIPrep input script to account for these different file types?
What kinds of outputs should I expect to see if they are being used correctly? Are there any QA measures that would be generated?
Any information on any of these questions would be so appreciated. Thanks again!
I would use the gradient corrected T1, see here for anatomical naming conventions: Magnetic Resonance Imaging - Brain Imaging Data Structure 1.10.0. I am not a multi-echo expert, but I believe that fmriprep can do something with the multi-echo t2star images. Perhaps someone else can chime in.
For fmap quality assurance, you would check that the distortion correction is actually improving geometric correspondance between anat and BOLD images, which is included in the HTML report at the end.
Newbie here. I have several field maps that were collected for many different runs. All the field maps have somewhat different parameters. For example, I have b1 field maps with different flip angles, fmri field maps with different dir and mm sizing. I also have a gre file for phase (but no magnitude).
Is there any way to parse which field maps go with which files in the IntendedFor slot of a .json? Can all fmri field maps be intended for all functional runs in a given session, irrespective of differences in mm size, TR, dir, etc.? Any information would be much appreciated. Thanks again!
Each BOLD run should only have one fieldmap associated with it. But a fieldmap can be associated to mutiple BOLD files. Typically, as long as both fieldmaps are good quality, which ever BOLD file it was collected closest to in time.
I have pairs of fmaps that are seemingly taken one after the other:
1.4 slice, dir-PA
1.4 slice, dir-AP
Then another pairing:
1.9 slice, dir-AP
1.9 slice, dir-PA
I also have the majority of my functional scans split up as either 1.4mm and 1.9mm. Does this mean the 1.4 functionals should go with the 1.4 field map, even if the 1.9 is slightly closer in time? Can I have both PA and AP associated with the functional files, or should I be choosing one?
Without having designed your protocol, I cannot say for sure why these fmaps have different resolutions. Perhaps the 1.4mm fmaps are meant to be associaled with 1.4 mm BOLD. Probably a safe bet.
Both of the pair (that is, AP+PA) must be associated for the fmap to work.