fMRI Tutorial #3: Looking at the Data¶
Now that you’ve downloaded the dataset, let’s see what it looks like. If the dataset has been downloaded to your Downloads directory, navigate to the Desktop and type the following:
mv ~/Downloads/ds000102_0001/ Flanker
Which will rename the folder to
Flanker and put it on your Desktop.
As you saw in the previous Data Download page, the dataset has a standardized structure: Each subject folder contains an anatomical directory and a functional directory labeled
func, and these in turn contain the anatomical and functional images, respectively. (The
func directory also contains onset times, or timestamps for when the subject underwent either a Congruent or Incongruent trial.) This format is known as BIDS, or Brain Imaging Data Structure, which makes it easy to organize and find your data.
Inspecting the Anatomical Image¶
Whenever you download imaging data, check the anatomical and functional images to inspect them for any problems - scanner spikes, incorrect orientation, poor contrast, and so on. It will take some time to develop an eye for what these problems look like, but with practice it will become quicker and easier to do.
Let’s take a look at the anatomical image in the
anat folder for
sub-08. Navigate to the sub-08 folder and then type
This will open the anatomical image in
fsleyes, FSL’s image viewer.
Inspect the image by clicking and dragging the mouse around. You can switch viewing panes by clicking in the corresponding window. Note that the other windows are updated in real time as you move your mouse around. This is because MRI data is collected as a three-dimensional image, and moving along one of the dimensions will change the other windows as well.
You may have noticed that this subject appears to be missing his face. That is because the data from OpenNeuro.org have been deidentified: Not only has information such as name and date of scanning been removed from the header, but the faces have also been erased. This is done in order to ensure the subject’s anonymity.
As you continue to inspect the image, here are two things you can watch out for:
- Lines that look like ripples in a pond. These are called Gibbs Ringing Artifacts, and they may indicate an error in the reconstruction of the MR signal from the scanner. These ripples may also be caused by the subject moving too much during the scan. In either case, if the ripples are large enough, they may cause preprocessing steps like brain extraction or normalization to fail.
- Abnormal intensity differences within the grey or the white matter. These may indicate pathologies such as aneurysms or cavernomas, and they should be reported to your radiologist right away; make sure you are familiar with your laboratory’s protocols for reporting artifacts. For a gallery of pathologies you may see in an MRI image, click here.
Inspecting the Functional Images¶
When you are done looking at the anatomical image, click on
Overlay -> Remove All from the menu at the top of your screen. Then, click on
File -> Add from File, navigate to
sub-08’s func directory, and select the image ending in
run-1_bold.nii.gz. This image also looks like a brain, but it is not as clearly defined as the anatomical image. This is because the resolution is lower. It is typical for a study to collect a high-resolution T1-weighted (i.e., anatomical) image, and lower-resolution functional images, in part because we collect the functional images much more quickly.
Many of the quality checks for the functional image are the same as with the anatomical image: Watch out for extremely bright or extremely dark spots in the grey or white matter, as well as for image distortions such as abnormal stretching or warping. One place where it is common to see a little bit of distortion is in the orbitofrontal part of the brain, just above the eyeballs. There are ways to reduce this distortion, but for now we will ignore it.
Another quality check is to make sure there isn’t excessive motion. Functional images are often collected as a time-series; that is, multiple volumes are concatenated together into a single dataset. You can rapidly flip through all of the volumes like pages of a book by clicking on the movie reel icon in fsleyes. Note any sudden, jerky movements in any of the viewing panes. During preprocessing, we will quantify how much motion there was in order to decide whether to keep or to discard that subject’s data.