Par-Files

Paradigm files, oir "par-files" are tab-delimited plain-text files that specify to Freesurfer's FS-FAST program when different experimental conditions occurred within each functional run. They have a very straightforward structure, with one line per event or block. The files have between two and four columns according to various sources, though this documentation has changed with different releases of Freesurfer. What seems to work for our release is the following column structure:

Cumulative_Onset     Condition_Number_Code     Duration     Weight

The cumulative onset is specified in seconds and assumes that the first volume onset is at t=0 seconds. If initial volumes have been truncated from the 4D time series, adjust the onsets accordingly, depending on your TR. For example, if your TR is 2 seconds, and you drop the first 4 volumes of a 100-volume series, your resulting data will contain only 96 volumes, and the first event will appear 4*2=8 seconds earlier in the series.

The following is a snippet from a par file for an experiment with a fixed schedule (i.e., all participants had the same experimental timings, rather than a self-paced experiment):

12.000     6     2     1
16.813     3     2     1
21.626     3     2     1
26.038     3     2     1
30.048     3     2     1
34.059     3     2     1
38.470     6     2     1
42.481     4     2     1
46.492     4     2     1
51.305     1     2     1

Here, the experiment starts with the first event happening 12 seconds into the run. It is event condition 6, and the duration of this trial (and all others) is 2 seconds. All trials are given a weight of 1 in the analysis (weights of 0 might be assigned if, for example, you want to discount activity associated with error trials).

An important thing to note: all .par files associated with a particular analysis must have the same filename. This is possible because each .par file is stored in the same directory as the fMRI data that it corresponds to, and the fMRI data for each run is kept in its own directory. For example, you might have the following directory structure:

• FS_T1_501
  • bold
    • 001
      • f.nii
      • booth.par
    • 002
      • f.nii
      • booth.par

When analyzing a fixed-schedule experiment, you should be able to simply copy the appropriate pre-existing par-file for that run from a source directory. For example, the par-files associated with the Booth data can be found in the par_files directory, in subdirectories corresponding with their Reading_Experiment_IDs.

When analyzing data from a self-paced experiment, each participant will have a unique par-file that will have to be generated from his/her MATLAB experimental data file.