help > Denoising CSF confound
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Jan 21, 2021  09:01 PM | Fabien Hauw
Denoising CSF confound
Hello,

I have a problem with the denoising of my resting state images.

So i have one subject that i want to compare to 36 other healthy subjects.
I have 2 groups of healthy controls, with different RT and different acquisition modalities (one had multi echo).

My issue is that when I preprocess and denoise these resting state in conn, the denoising step is not good, especially for the CSF compound : for example here is 1 subject (see attached file), the denoising is really bad, and when i raise the threshold, there is explained variance by the CSF almost everywhere except in the ventricules... I specify that my ROI images for grey/white matter and CSF are good enough, and aligned with MNI space for the "bad" subjects".

I will now explain how I manage the preprocessing:

- As one group had a multi echo acquisition, the echo fusion is made by MEICA via AFNI, and it does the slice timing correction and realignment before the fusion; the other group and my subject of interest have simple echo acquisition and then had realignment and STC on SPM.

- I have tried to put the functional scans once they were realigned and STC in conn, so conn only had to make segmentation and normalization, but there were 2 situations regarding the anat:
  • I give conn raw anat scan and it does the whole preprocessing on it: in this case, there was no bias correction made, and the segmentation was pretty bad for the CSF and grey/white matter, so bad denoising; plus, there was an issue of « NON MATCHED DIMENSIONS » with the functional scans, I couldn't find what did this mean...
  • I give conn already preprocessed anat scan (already normalized and bias corrected), but then it does the segmentation from functional scan, therefore it was worst than previous situation...
—> so I decided to put preprocessed functional scans in conn (but without ART outlier detection, normalization, nor smoothing), and completely preprocessed anat scans. I even put the different « ROI » resulting from the segmentation i.e. white matter, grey matter and CSF, already normalized. This is the way I do my preprocessing on conn.

And eventually, when I have to start the denoising, I have this kind of images, for some subjects it seems that the variance explained by CSF is mainly in the ventricles, but for some other (almost half I guess), this variance is mainly outside the ventricles, some times exclusively in the white or grey matter...
When I look at 1st level analyses: some of the subjects don't even have a correct default mode network activations...

So my point is:
- Is this an issue or totally normal? Should I improve the denoising or is it okay to take a look at the analyses with this denoising result?
- If an issue, how should I do to get over it?

I don't know if I'm clear, let me know if not...

Thanks a lot for your time and answer,
Best,
Fabien Hauw.