Connectivity Toolbox

The conn Functional Connectivity toolbox is a MATLAB-based program that hijacks SPM to do some data de-noising and remove potential artefacts that might skew your connectivity data. It is somewhat geared towards voxel-space analyses, but can support the surface-space analyses that we typically do in our lab. The walkthrough below is geared towards running conn on your FreeSurfer data.

Preconditions

These instructions assume that you have functional and anatomical data organized in the manner that FreeSurfer expects, and that you have completed the autorecon steps on the T1 anatomical file and have generated the surface meshes for your target participants. These instructions will also assume that you have dropped some number of initial volumes from the BOLD runs (usually the first 4) if required. If working from the raw data archived from the CTRC scanner, this will be a required step; if you are working with BOLD data that has already been analyzed, or preprocessed this may already have been done, and you will not want to drop yet another initial 4 volumes!

Because conn runs on top of SPM, you need to ensure that SPM is in your MATLAB path. Of course, conn also needs to be in your path. Check that they are using the which command in the MATLAB command window:

>> which spm
/opt/spm12/spm.m
>> which conn
/opt/conn/conn.m

If you see the paths to both .m files, you can run conn from the MATLAB command window:

>> conn

Starting an Analysis in CONN

My goal here isn't going to be to duplicate the conn user manual, and we're not going through an entire functional analysis. But you have to start somewhere, so here we are...

When you launch conn, you will get a nice gui window with a menu bar along the top. We want to start a new project: Project > New (blank) You will get a uiwindow that asks where you want to save the project details. You can save this .mat file wherever you like, though I would recommend somewhere near your $SUBJECTS_DIR for the project. Next you will have to specify parameters for setting up the analysis

Basic information

The first uiwindow you need to populate has some general experimental setup information:

Number of subjects

Indicate here how many subjects you wish to process. This will tell conn how many datasets to expect. You don't even have to add everyone in the experiment to the analysis: If you have FreeSurfer data for 10 people, but just want to process 1 or two people, then just indicate that there are 1 or 2 subjects.

Number of session

By this, they mean functional runs. Our Imagery experiment has 2 visits with 6 functional runs each. If someone completed both visits, they would have 12 sessions worth of data. As with the subjects parameter, you don't have to use all the runs. You might wish to just analyze the 6 runs from the first visit, in which case you would say there are 6 sessions. The program will almost certainly crash if some runs are missing for some participants because it will expect the same amount of data for each participant. You will need to separately process individuals with missing runs.

Repetition Time (seconds)

This is our experimental TR. For the Imagery study, our TR is approximately 2 seconds (2.047, to be precise).

Acquisition type

Leave it as the default, Continuous, which means the scanner is continuously acquiring BOLD data throughout the run. It's unlikely that you'll be analyzing data collected using sparse sampling.

Structural data

Here is where you have to find the T1 and surface files for your participants. They made the program clever enough to do pattern matching, so if you pick a root directory, and then indicate the file pattern for the structural data, it will find all the matching files. For example, if you left-click on your $SUBJECTS_DIR, type in T1.mgz and click the Find button , it will identify the paths to all the structural files generated by FreeSurfer. From there, you highlight the files you wish to work with and click the Select button (make sure the number of selected files matches the number of highlighted Subjects). If the T1 data have already been preprocessed with FreeSurfer, you should be asked if you wish to also import the segmentation files. Say Yes.

One thing I will point out is that our FreeSurfer analyses are done in surface space, which doesn't care about where the particular voxels sit in relation to the cube of voxels surrounding the standard MNI template brain. For that reason, your structural and functional data will seldom be even close to aligned with the MNI brain. This isn't usually a problem, but I'm now considering coregistration of the data (but not spatial normalization) as a routine preprocessing step. Stay tuned.