top | previous | FSFAST Tutorial Top

Preprocessing in FS-FAST

1. Introduction to FSFAST Preprocessing

Once the data have been arranged in the proper directory structure and naming convention, they are ready to be preprocessed. Preprocessing includes

  1. Template Creation
  2. Brain Mask Creation
  3. Registration with FreeSurfer Anatomical

  4. Motion Correction
  5. Slice Timing Correction (if using)
  6. Spatial Normalization
  7. Masking
  8. Spatial Smoothing

In FS-FAST, it is assumed that each data set will be analyzed in three normalization spaces:

You will need to decide how much to smooth the data and whether you want to do slice-timing correction. In this analysis, we will smooth the data by 5mm Full-Width/Half-Max (FWHM) and correct for slice timing. The slice-timing for this particular data set was 'Ascending', meaning that the first slice was acquired first, the second slice was acquired second, etc. To preprocess the data, run:

preproc-sess -s sess01 -fsd bold -stc up -surface fsaverage lhrh -mni305 -fwhm 5 -per-run 

This data has already been preprocessed, so it should just verify that it is up-to-date, finishing in a few seconds. This command has several arguments:

This command does a lot, and it can take quite a long time to run, especially for many subjects. Look at the contents of one of the run directories:

ls $FSFTUTDIR/sess01/bold/001

You will see many files there, but there are three important ones:

These are time series data, and their names indicate what has been performed on them:

To learn more about the details see PREPROC DETAILS below.

2. Quality Assurance

2.1. Motion Correction

The motion plots can be viewed with:

plot-twf-sess -s sess01 -fsd bold -mc 

This gives the vector motion at each time point for each run. Note that it is always positive because this is a magnitude. It is also 0 at the middle time point because the middle time point is used as the reference.

There are no rules for how much motion is too much motion. Generally speaking, sudden motions are the worst as are task-related motion.

2.1.1. Functional-Anatomical Cross-modal Registration

You can get a summary of registration quality using the following command:

tkregister-sess -s sess01 -fsd bold -per-run -bbr-sum

This prints out a value for each run that indicates the quality of the registration with the anatomical.This will be a number between 0 and 1, with 0 being perfect and 1 being terrible. Actual values depend upon exactly how you have acquired your data. Generally, anything over 0.8 indicates that something is probably wrong.

You can view problematic registrations using the following command:

tkregister-sess -s sess02 -fsd bold -per-run

This will display each of the runs. Quit out of tkregister when you have glanced at the registration