Running the connectivitymatrix portion of QSIrecon on the HBN

1

Hi,

bear with me, I am normally working on structural stuff only, but am starting to dabble a bit in dwi as well.

We are looking at the data QSIprep’ed data of the HBN (accessible for registered users here: https://fcon_1000.projects.nitrc.org/indi/cmi_healthy_brain_network/downloads/downloads_MRI_R11.html). The paper An analysis-ready and quality controlled resource for pediatric brain white-matter research | Scientific Data describes the preprocessed data. Now we have two questions:

  1. The preprocessed data includes results from running AFQ. Is this equivalent to running the pre-defined AFQ workflow within qsirecon? Or are there differences?

  2. Can we use the already preprocessed data to then run qsirecon on top to get connectivity matrices.

Thanks,
Melanie

1 Like
2

Hi @melanieganz,

The differences would be mainly due to pyAFQ updates in QSIRecon since the release of this paper.

Yes.

Best,
Steven

3

Thank you so much Steven!

Do you by chance know of an example in the qsirecon docs where we can see how to run just the connectivity matrix quantification on top of already existing AFQ runs, so when they have been done outside of qsirecon? I looked at the documentation, but couldn’t really find anything like that outside of the workflows.

4

Hi @melanieganz,

You would need a sufficiently dense whole-brain tractogram to do that, which I do not think you would have from the HBN-POD2 outputs. Thus I recommend running the mrtrix_multishell_msmt_ACT-hsvs workflow in QSIRecon.

It uses mrtrix tools like dwi2response dhollander, dwi2fod msmt, mtnormalise, 5ttgen hsvs, etc. You can see some of the parameters in the recon spec itself: qsirecon/qsirecon/data/pipelines/mrtrix_multishell_msmt_ACT-hsvs.yaml at main · PennLINC/qsirecon · GitHub

Best,
Steven

5

Ah, thanks for that pointer!

1 Like