Registration in this context is the processes of computing a linear (affine) transformation matrix to map between the individual's functional data and his/her FreeSurfer structural/anatomical data (namely, the orig.mgz volume in the FreeSurfer mri directory). Before computing the registration, FS-FAST needs to know what the name of the subject is in the $SUBJECTS_DIR. You do this by creating a file in the functional directory called "subjectname". Eg:

cd bert-functional br echo "bert" > subjectname br

Then there must be FreeSurfer data for bert under $SUBJECTS_DIR/bert. FS-FAST will then get the name of the subject from this file and automatically know where to find the anatomicals. This registration is used both for mapping to the standard volume space (talairach) and the standard surface space (fsaverage). When mapping to talairach space, the mri/transforms/talairach.xfm is used. Note that the raw functional data is not mapped. Rather, the GLM analysis is done in native space, and the regression coefficients are mapped to the higher level.

By default, FS-FAST will use the first-volume of the first run as the functional template for registration. It is important that this template be the same one used for motion correction (which will be done by default).

There are 2 options for automatically registering to the structural:

  1. ["spmregister-sess"] -s <subject> -df sesspar

  2. ["autoreg-sess"]

Regardless of which method you use, you should manually inspect/tune the registration with ["tkregister-sess"].

With either method, a registration file will be created in bold/register.dat. This is a simple text file with the name of the subject, some parameters, and the registration matrix.

spmregister-sess uses the registration program in SPM (http://www.fil.ion.ucl.ac.uk/spm). It registers directly from the functional to the anatomical (so you do not need to collect an anatomical during your functional session if you don't want to). spmregister-sess also uses matlab "under-the-hood", but that's only important if you don't have matlab. Finally, there have been some troubles as of spring 2006 in running this on 64-bit machines. We have found this method to be quite reliable and robust, and it is the preferred method.

autoreg-sess requires a same-session anatomical (eg, MP-RAGE) to be collected and stored in a directory called "3danat/RRR" within the functional directory (RRR is the run number). This anatomical is then registered with the FreeSurfer anatomical. It is assumed that the subject did not move his/her head between the same-session anatomical and the functional template used for motion correction (thus allowing a registration to be computed based on scanner coordinates). This two registrations are then concatenated to give a registration from the functional to the FreeSurfer anatomical. This method uses MINC (www.bic.mni.mcgill.ca/software/minc) to perform the registration.

Finally, you should *always* check the registration with "tkregister-sess -s sessid ...". This will bring up a control panel and a window with a brain image. The brain image window should also have a green outline of the cortical surface. When you hit the "Compare" button, the display will toggle between the FreeSurfer anatomical and the functional. The cortical surface will always be there and can be used to judge how good the registration is. There are three buttons that can be used to change the view (Horizontal, Coronal, Sagittal). Manual registration can be a difficult task. When judging the quality of the registration, use cortical landmarks (try to avoid using the outline of the brain or the ventricals except for gross registration). Use areas away from B0 distortion (eg, inter-parietal, calcarine, central, lateral sylvian). See tkregister2 --help for more info.