Step by step instructions for analyzing fMRI data with BOLDfold and AFNI

The following step-by-step guide represents our current (2002) standard approach to fMRI data analysis for data acquired in a repeated event-related experimental design. As the fMRI research program grows at the U of S, other methods for data analysis will be adopted.

The following guide was written by Ben Norris and Greg Kraushaar in the Summer of 2002. For a fairly detailed idea of what you want to generate with the analysis, see the Example Results web page

  1. Following the procedures given on the data acquisition and storage page, make a copy of your data for analysis following the project/subject directory structure organization.

  2. Make sure that the appropriate "*.std" files are in their corresponding folder, as well as any anatomical BRIK and HEAD files, or functional BRIK and HEAD files. If there are no anatomical BRIK or HEAD files, you will need to make anatomical AFNI datasets from the corresponding *.sdt files, using the program "image". Rename all your files to include the participant's ID number (see the Example Naming page for an example on how to rename your files for an experimental design that is multi-factorial with respect to the given tasks). It is also a good idea to include in your filenames the specific condition that the participant was performing. For instance, if participant 23 completed a task that involved a High level of electric shock, accompanied with a Happy mood, you would name the file something along the lines of HighHappy23.sdt.

  3. Run Gord's super-cool imaging program, by typing "image" at the command prompt. Use menu #23 (fMRI) and then the motion correction option (#7) to align all functional volumes. It is recommeded that you align your datasets to volume 5 or above; never align on volume 1 since that volume's spin data are not yet in the steady state caused by the imaging repetitions (TR). The file name to enter is the functional file prefix, without extension (e.g. HighHappy23). Once you are finished, exit the Image program. You should now have a new set of sdt files, with an "F" suffix added. These are the motion corrected files (e.g. HighHappy23F.sdt).

  4. Run the BOLDfold program, by typing "bfold" at the command prompt. You must be in the directory where your files are contained to do this. BOLDfold will ask you what file you want to run the calculations on. You will want to run the BOLDfold transformations on both your motion corrected, as well as your uncorrected data. BOLDfold will then prompt you to enter certain design specifications, so make sure to have them handy. Refer to the BOLDfold steps manual. The BOLDfold program will produce an output of various "sdt" _BF maps, each with different statistic values stored at each voxel, as well as one _BF map in AFNI format (per task). It is your responsibility to ensure that all tasks that each participant completed are BOLDfolded.

  5. Using the online guide to help you out, write all AFNI anatomical and functional datasets to Talairach orientation (+tlrc). The online guide can be found on the AFNI documentation web page under the "How to make an Average Brain" section (Step 1 only).

  6. From here, you will need to prepare the BoldFold files for AFNI's 3dANOVA2 program if your experimental design requires an ANOVA comparison of stimulus (task) conditions. To do this, you will need to censor, blur, and clip your data. Refer to ANOVA steps on how to go about preparing your data and running the ANOVA program. For other experminetal designs you may want to do a t-test or a simple subtraction or quantify the hemodynamic response in pre-specified regions of interest. For those experimental designs, a perusal of the AFNI documentation should help you to set a method of analysis.

  7. Proceed to do cluster average time courses for each of the clusters in the brain, at each eta cutoff. For how to do this, see Cluster Steps web page. For guides on how to use AFNI, see the AFNI documentation webpage. Once you have saved an average time course of all the clusters in the brain, now would be a good time to decide which are due to noise and which are due to actual activation. Find the center of mass for each cluster, and go back to AFNI's GUI to report the Anatomical and Brodmann areas for each cluster. Be aware that the report is only approximate, because when you Talairached your anatomical dataset, this was only a "rough" anatomical dataset, and the "Where Am I?" program uses mm from origin as a guide to where in the brain you are. Since each brain is highly variable in its anatomy, when you report a cluster at, say 22mm from the origin, this may not correspond exactly to the reported structure in the Talairach atlas.

  8. Go get yourself a Coke or Mellow Yellow slush at the Cove for all of your hard work. Well done!