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:
- Functional: Label current functional files as "original
data"
- Functional: Realignment (subject motion estimation and
correction)
- Functional: Segmentation (Grey/White/CSF segmentation)
- Functional: Outlier detection (ART-based identification of
outlier scans for scrubbing)
- Functional: Label current functional files as "MNI-space
data"
- 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!
Threaded View
Title | Author | Date |
---|---|---|
Alejandro Garma | May 21, 2024 | |
Alfonso Nieto-Castanon | May 21, 2024 | |