open-discussion > fMRIprep and CONN Toolbox setup for resting state data
Jun 29, 2020  01:06 PM | Natasza Marrouch
fMRIprep and CONN Toolbox setup for resting state data
Dear experts,

I am new to fMRI and fMRIprep, and I wanted to get some opinions regarding the fMRIprep set-up I am using, as well as the selections in the CONN toolbox to make sure I am doing it correctly.

The data -- resting-state scans are from different sites with different voxel sizes (2.5x2.5x2.5 or 2.4x2.4x.2.4) and TR. In some cases, the scans come from a single session; in others, from 2 separate sessions, but regardless of the number of sessions, the total duration of the resting scans is similar.

Because of the above I used the following options (also, not all subjects have necessary data to use 'fieldmaps' option):

--output-spaces MNI152NLin6Asym:res-2 MNI1522NLin2009cAsym --use-syn-sdc --fs-no-reconall --ignore fieldmaps slicetiming

I was told that slice timing correction is not needed with resting-state scans and because I want to run ROI-to-ROI comparisons defined on a 2mm template consistent with MNI152NLin6Asym, I should resample the functional scans to the same space rather than use resampled to native space that varies in resolution across subjects.

Once preprocessed in fMRIprep, the following steps and confounds from fMRIprep for denoising are to follow, before ROI-to-ROI analysis and between-groups comparisons:

  * Smoothing: with a 5mm Gaussian kernel
  * Realignment
  * Scrubbing
fMRIprep regeressors for denoising:
  * aCompCor, tCompCor & their corresponding cosine regressors
  * Motion correction: DVARS, framewise displacement, motion outlier
  * Rotational parameters: rot, rot_x_derivative, rot_y_derivative, rot_z_derivative
  * Translational parameters: trans, trans_x_derivative, trans_y_derivative, trans_z_derivative
Additionally:
  * Default band-pass filter: 0.008-0.09 Hz
  * Detrending: linear

So far, I was able to troubleshoot any problems related to preprocessing data, but it would be great if I could get some input and opinions:

Are any of the steps redundant?
Is resampling the functional data to a standard space helpful?
Is the band-pass filter of an appropriate range given the type of the data?
Can you see any red flags that could potentially distort the results?

Thank you in advance!Tasha