Dear FSL group,
I want to set up my subject-level model in FEAT but there is one type of contrast that I just can’t figure out how to set up. We are planning to perform RSFC analysis on 4 ACC seeds: right ventral ACC, right dorsal ACC, left ventral ACC and left dorsal ACC. We have extracted the mean time course of each seed for examining both positive and negative connectivity between each seed and other voxels throughout the brain. Setting up contrasts that test the negative and positive connectivity patterns of each seed is straightforward. However, I have difficulty setting up a contrast that for instance tests whether there are any regions that both the right vACC and right dACC positively connect to, in which one of them (vACC/dACC) has a stronger connectivity to that region than the other. For example, both vACC and dACC might be positively connected to the same region in the anterior insula. We would very much like to know which seed has the strongest connectivity to that specific part of the insula. Along the same line, we are interested in similar effects in negatively connected regions. Additionally, we would like to directly compare the RSFC of each seed with each other, so to which regions is the vACC exclusively connected to compared to the dACC (i.e. vACC vs. dACC). In other words, I want to set up contrasts that test differentiation and similarities in connectivity patterns.
To keep it simple I have set up a model that includes only the right side of the brain with no confound regressors. I hope you could be so kind to provide me with some assistance on setting up the specific contrasts.
C1. vACC_Postive 1 0
C2. vACC_Negative -1 0
C3. dACC_Postive 0 1
C4. dACC_Negative 0 -1
C5. vACC_Postive > dACC_Postive ? ?
C6. vACC_Negative > dACC_Negative ? ?
C.7 dACC_Postive > vACC_Postive ? ?
C.8 dACC_Negative vs. vACC_Negative ? ?
C9. vACC_Postive vs. dACC_Postive ? ?
C10. vACC_Negative vs. dACC_Negative ? ?
C.11 dACC_Postive vs. vACC_Postive ? ?
C.12 dACC_Negative vs. vACC_Negative ? ?
Any assistance is greatly appreciated!
Thanks in advance for your time and effort.
All the best,
Mark
|