Can I get information on lobular volumes from SUIT_lobuli_summarize?

I have isolated and normalized a set of images. I would love to get information volume information on the cerebellar lobules. Is this possible with SUIT_lobuli_summarize?

After you normalize into SUIT space, the lobules of different participants have (by definition) all the same volume. To get volume information back, there is one approach:
You could reslice the atlas into each individual space (using suit_reslice_inv).

suit_reslice_inv('Cerebellum-SUIT.nii','mc_<name>_snc.mat');

The resultant image can then be summarised for each subject by looping over subjects:

for s=1:num_subject
V=spm_vol(<individual reslices atlas image>);
X=spm_read_vols(V);
for l=1:num_lobules
Numvox(s,l) = length(find(X==l));
end;
end;

Can I use suit_reslice with 4d niftis?

Is it possible to reslice 4D-niftis using suit_reslice?

In older versions this was not possible, as we never resliced raw functional data into SUIT-space, only the beta-estimates (see fMRI analysis). This is now fixed in the new version of suit_reslice. Suit_reslice_dartel may not work yet with 4D niftis.

I'm getting warning messages using suit_reslice

This warning appears by default due to the fact the mask usually isn't in the same orientation as the source (functional) data, and can safely be ignored.

Dentate mask definition

I am not clear whether the ROI image should consist of a single axial slice, or the full 3D structure.

The dentate mask needs to be a 3D-structure, marked on a set of slices. Indicating it on the EPI (or on a scan with the same distortion as the EPI) will increase the accuracy of your analysis.

have you found it useful to rely on an intensity filter to isolate the dentate (in EPI images), or do you suggest hand-tracing the structure in each individual?

An intensity filter works very well, followed by a little bit manual correction. Note that the dorsal-medial part of the dentate is usually lighter (less iron) than the rest, so it is easily missed by just using a fixed threshold.

Positive and negative activations on the flatmap

How can I display both positive and negative activations on the flatmap (as you have done in Diedrichsen & Zotow, 2015, Figure 7)?

Right now, the matlab function can only display and threshold one contrast at the time. One solution is to save the mapped data as a functional gifti file and then load and display it using Caret:

• C.cdata=suit_map2surf('myFile.nii');
• C=gifti(C);
• save(C,'mygiftifile.func.gii');


• Then open up Caret. Got to File-> Open Spec: select the SUIT.C.spec file.
• Add the functional file through File-> Open ,select your gifti file.
• Go to the display control panel (D/C) -> Overlay / Underlay Surface, and select the metric as overlay
• Set the thresholds and color map in Display Control -> Metric Settings.

I'm getting messages in suit_normalize

I'm getting one or more of the following messages in suit_normalize:

This could result in an error in the process, in this case, It is recommended to set the origin of the anatomical image (0,0,0) to the anterior commissure. This can be done in several packages, first looking at the position of the AC and then subtracting those coordinates from the coordinates in the qform of the nifty header.

How can I reslice images into subject space after using suit_normalize_dartel or suit_normalize_dentate?

Normalization in SUIT using normalize_dartel and normalize_dentate functions uses the DARTEL engine. This will create a nifty image of the deformation field applied to the original image (u_a_[filename].nii). In order to warp images back to the original space, you can use the regular DARTEL tools from SPM. Just go to TOOLS > DARTEL > CREATE INVERSE WARP. Then use your "u_a_[filename].nii" deformation image and the nifty image you want to warp back.

I get an error when trying to load a .gii file in MATLAB

SPM ships with custom libraries for reading files in the GIFTI format (.gii). These libraries are further dependent on third-party libraries such as XMLTree. Some newer MATLAB versions require the latest implementation of the XMLTree library, which may not be present in your version of SPM. To download and install the latest version of XMLTree, please follow the instructions here.

Need help?

For newer issues, problems. questions, and inquiries, please check the issue pages of the Github repositories for the Matlab or Python version of the toolbox. For questions regarding cerebellar atlas maps, please check the issue page for the Cerebellar Atlas package. If the questions is not already answered, please raise a new issue on Github and we will do our best to respond as soon as possible.