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For general tips on using FsFast, download this powerpoint: For general tips on using FsFast, download this [[http://surfer.nmr.mgh.harvard.edu/pub/docs/freesurfer.fsfast.ppt|FS-FAST powerpoint]]
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  [[http://surfer.nmr.mgh.harvard.edu/pub/docs/freesurfer.fsfast.ppt|Using FS-FAST]] This walkthrough demonstrates how to run a functional connectivity analysis on resting state fMRI data.
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*STEP 1: Unpack Data into the FSFAST Hierarchy using "unpackscmdir" *STEP 1: Unpack Data into the FSFAST Hierarchy using [[https://surfer.nmr.mgh.harvard.edu/fswiki/unpacksdcmdir|unpacksdcmdir]]
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[[https://surfer.nmr.mgh.harvard.edu/fswiki/unpacksdcmdir|unpacksdcmdir]] Ex:
unpacksdcmdir -src dicomdir/subject/ALLDICOMS -targ fcMRI_dir/subject -cfg subject_config.txt -fsfast -unpackerr

In this example command...
                   *Have all fMRI dicoms linked into "ALLDICOMS" directory
                   *Arguement for "-targ" specifies output directory
                   *subject_config.txt is a configuration text file you create (format below)
                   *Use "-fsfast" to generate fsfast hierarchy

subject_config.txt format:

28 bold nii f.nii
29 bold nii f.nii

Col.1: scan acquisition number
Col.2: output dir name will be created within "fcMRI_dir/subject"
Col.3: output file format - this example is nifti format
Col.4: output filename. In this example, 2 files will be created:
  fcMRI_dir/subject/028/f.nii
  fcMRI_dir/subject/029/f.nii
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*STEP 2: Reconstruction Anatomical data using "recon-al -all" *STEP 2: Reconstruction Anatomical data using [[https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all| recon-all]]
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1.Set SUBJECTS_DIR Ex:
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setenv SUBJECTS_DIR /path/to/recon_dir/
recon-all -s subject_dirname -all -i pathtoT1dicom_scan1.dcm -i pathtoT1dicom_scan2.dcm

In this example command...
                   *set your SUBJECTS_DIR variable to your FreeSurfer subject recon directory
                   *set the subject's directory name with "-s" ... the arguement you provide will become the directory name within $SUBJECTS_DIR
                   *use "-i" to supply the dicoms to reconstruct. Use one "-i" per T1 acquisition.
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 * D - Check hierarchy of reconstructed anatomical data [[https://surfer.nmr.mgh.harvard.edu/fswiki/recon-all| recon-all]]  * D - Check hierarchy of reconstructed anatomical data
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1.Make FSFAST basic hierarchy (only if data are not unpacked in FSFAST hierarchy)
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2.Link to FreeSurfer anatomical analysis 1.Double-check for FSFAST basic hierarchy
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A - Make subjectname’ file in the session directory to link a subject's functional & structural data {{attachment:fsfast-hierarchy.jpg}}

2.Link to FreeSurfer anatomical analysis:

A - Create "subjectname" text file in the session directory. Write in it the subject's recon directory name (found within $SUBJECTS_DIR).
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4.Create a Stimulus Schedule (Paradigm file) in bold folder (A "paradigm" file is a record of which stimulus was presented when & for how long.
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Each paradigm file has four columns: *STEP 3: Pre-process your bold data using preproc-sess [[http://surfer.nmr.mgh.harvard.edu/fswiki/preproc-sess|preproc-sess]]
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A - Stimulus onset time (sec) preproc-sess -s <subjid> -fwhm <#>
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B - Condition ID code (0, 1, 2, ...) 1.By default this will do motion correction, smoothing & brain masking
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C - Stimulus Duration (sec) 2.Quality Check (plot-twf-sess) 3.Examine additions to FSFAST hierarchy (in each run of bold dir):
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D - Stimulus Weight (usually 1)   ||f.nii || (Raw fMRI data) ||
  ||fmc.nii || (Motion corrected-MC)||
  ||fmcsm5.nii|| (MC & smoothed)||
  ||fmc.mcdat|| (Text file with the MC parameters (AFNI))||
  ||brain.mgz ||(Binary mask of the brain)||
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*STEP 3: Pre-process your bold data using preproc-sess [[http://surfer.nmr.mgh.harvard.edu/fswiki/preproc-sess| preproc-sess]]
# Preprocessing of fMRI Data ()
preproc-sess -s <subjid> -fwhm <#>
1.By default this will do motion correction, smoothing & brain masking
2.Quality Check (plot-twf-sess)
3.Examine additions to FSFAST hierarchy (in each run of bold dir):
 f.nii (the raw data)
 fmc.nii (motion corrected-MC)
 fmcsm5.nii (MC & smoothed)
 fmc.mcdat - text file with the MC parameters (AFNI)
 mcextreg.bhdr - binary mask of the brain 		# Function-Structure Registration View unregistered:
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# Function-Structure Registration View unregistered
tkregister-sess -s <subjid> -regheader)
Run automatic registration spmregister-sess -s <subjid>
Check automatic registration tkregister-sess -s <subjid> 		 . [[http://surfer.nmr.mgh.harvard.edu/fswiki/tkregister-sess|tkregister-sess]] -s <subjid> -regheader)
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A - Make edits if needed using scale as the last resort Check talairach registration tkregister2 --s <subjid> --fstal --surf Run automatic registration:

 . [[http://surfer.nmr.mgh.harvard.edu/fswiki/spmregister-sess|spmregister-sess]] -s <subjid>

Check automatic registration:

 . [[http://surfer.nmr.mgh.harvard.edu/fswiki/tkregister-sess|tkregister-sess]] -s <subjid>

A - Make edits if needed using scale as the last resort Check talairach registration:

 . [[http://surfer.nmr.mgh.harvard.edu/fswiki/tkregister2|tkregister2]] --s <subjid> --fstal --surf
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*STEP 5: Use mkanalysis-sess to setup an analysis for your FC data *STEP 5: Use  [[http://surfer.nmr.mgh.harvard.edu/fswiki/mkanalysis-sess|mkanalysis-sess]] to setup an analysis for your FC data
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*STEP 6: Use selxavg3-sess to run the subject-level analysis *STEP 6: Use  [[http://surfer.nmr.mgh.harvard.edu/fswiki/selxavg3-sess|selxavg3-sess]] to run the subject-level analysis
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*STEP 7: Use mri_glmfit or selxavg3-sess to run a group-level analysis *STEP 7: Use  [[http://surfer.nmr.mgh.harvard.edu/fswiki/mri_glmfit|mri_glmfit]] or  [[http://surfer.nmr.mgh.harvard.edu/fswiki/selxavg3-sess|selxavg3-sess]] to run a group-level analysis

work in progress...

About

Walkthrough: How to use FsFast and fcseed-sess for functional connectivity analysis including example commands.

For general tips on using FsFast, download this FS-FAST powerpoint

This walkthrough demonstrates how to run a functional connectivity analysis on resting state fMRI data.

*STEP 1: Unpack Data into the FSFAST Hierarchy using unpacksdcmdir

Ex: unpacksdcmdir -src dicomdir/subject/ALLDICOMS -targ fcMRI_dir/subject -cfg subject_config.txt -fsfast -unpackerr

In this example command...

  • Have all fMRI dicoms linked into "ALLDICOMS" directory
  • Arguement for "-targ" specifies output directory
  • subject_config.txt is a configuration text file you create (format below)
  • Use "-fsfast" to generate fsfast hierarchy

subject_config.txt format:

28 bold nii f.nii 29 bold nii f.nii

Col.1: scan acquisition number Col.2: output dir name will be created within "fcMRI_dir/subject" Col.3: output file format - this example is nifti format Col.4: output filename. In this example, 2 files will be created:

  • fcMRI_dir/subject/028/f.nii fcMRI_dir/subject/029/f.nii

1.QA Check after unpacking:

  • A - Check unpacked data (time points, # of slices ..etc)
  • B - Check FSFAST hierarchy in session folder

*STEP 2: Reconstruction Anatomical data using recon-all

Ex:

setenv SUBJECTS_DIR /path/to/recon_dir/ recon-all -s subject_dirname -all -i pathtoT1dicom_scan1.dcm -i pathtoT1dicom_scan2.dcm

In this example command...

  • set your SUBJECTS_DIR variable to your FreeSurfer subject recon directory

  • set the subject's directory name with "-s" ... the arguement you provide will become the directory name within $SUBJECTS_DIR
  • use "-i" to supply the dicoms to reconstruct. Use one "-i" per T1 acquisition.

2.QA Check:

  • A - Check talairach transformation

  • B - Check skull strip, white matter & pial surface

  • C - Re-run "recon-all" if edits are made
  • D - Check hierarchy of reconstructed anatomical data

1.Double-check for FSFAST basic hierarchy

fsfast-hierarchy.jpg

2.Link to FreeSurfer anatomical analysis:

A - Create "subjectname" text file in the session directory. Write in it the subject's recon directory name (found within $SUBJECTS_DIR).

3.Create a sessid file (text file with list of your sessions)in your Study DIR.

*STEP 3: Pre-process your bold data using preproc-sess preproc-sess

preproc-sess -s <subjid> -fwhm <#>

1.By default this will do motion correction, smoothing & brain masking

2.Quality Check (plot-twf-sess) 3.Examine additions to FSFAST hierarchy (in each run of bold dir):

  • f.nii

    (Raw fMRI data)

    fmc.nii

    (Motion corrected-MC)

    fmcsm5.nii

    (MC & smoothed)

    fmc.mcdat

    (Text file with the MC parameters (AFNI))

    brain.mgz

    (Binary mask of the brain)

# Function-Structure Registration View unregistered:

Run automatic registration:

Check automatic registration:

A - Make edits if needed using scale as the last resort Check talairach registration:

*STEP 4: Use fcseed-sess to generate time-course information for your chosen seed region (as well as nuisance variable signal).

*STEP 5: Use mkanalysis-sess to setup an analysis for your FC data

*STEP 6: Use selxavg3-sess to run the subject-level analysis

*STEP 7: Use mri_glmfit or selxavg3-sess to run a group-level analysis

FsFastFunctionalConnectivityWalkthrough (last edited 2024-01-16 14:11:01 by DougGreve)