Hi!

Hello dear CONN experts,

I have just started using CONN and have some simple questions to ensure I am processing my data correctly.

I have resting-state fMRI data from 100 subjects that I want to transform into 100 functional connectivity matrices for use with the Brain Connectivity Toolbox. I have partially preprocessed my data in FSL, performing slice timing, motion correction, B0 unwarping, and spatial smoothing. Then, I used ANTs to transform the data into MNI space.

Unfortunately, my images have low SNR and low CNR. Due to this, I want to apply additional preprocessing steps available in CONN, specifically aCompCorr and a 12 DOF covariate GLM with simultaneous band-pass filtering in the denoising step.

The current pipeline I am using in CONN is as follows:

1. Functional: Label current functional files as "original data"
   
2. Functional: Realignment (subject motion estimation and correction)
   
3. Functional: Segmentation (Grey/White/CSF segmentation)
   
4. Functional: Outlier detection (ART-based identification of outlier scans for scrubbing)
   
5. Functional: Label current functional files as "MNI-space data"
   
6. Structural: Segmentation (Grey/White/CSF tissue estimation)
   

Then, I perform only ROI-to-ROI analysis, using semi-partial correlation and HRF weighting. Finally, I compute the graph theory results using the atlas ROIs and a two-sided correlation coefficient with a threshold of 0.3, and export the adjacency matrices.

My first question is whether I am following the correct processing pipeline.

My second question is regarding my adjacency matrix: it does not appear to be symmetrical. Why is that so?

Thanks for your time, and I hope you have an excelent day!