Hi, sorry if it's a dumb question but from what I understand, the network we get from first level analysis is essentially Region to Region (ROI-to-ROI) matrix e.g. load resultsROI_Subject001_Condition001.mat

Are we able to get Region to voxel networks in a similar manner? I am asking because I am able to import these ROI-ROI matrices into python for ML. But I also want to try for Region to Voxel as suggested by a paper I read. 

If anyone could enlighten me, I'd really appreciate it! Thank you

Hi Calvin,

Yes, in CONN nomenclature that is called "SBC" (for Seed-Based-Connectivity), computing the connectivity/correlation between a seed region and each voxel in the brain. You may define a new first-level analysis and select the SBC option, and then select which region(s) you may want to include as seed(s), and CONN will create a new BETA_*.nii NIFTI image for each seed (and subject/condition) containing those connectivity maps.

Hope this helps

Alfonso

Originally posted by Calvin Hew:

Hi, sorry if it's a dumb question but from what I understand, the network we get from first level analysis is essentially Region to Region (ROI-to-ROI) matrix e.g. load resultsROI_Subject001_Condition001.mat

Are we able to get Region to voxel networks in a similar manner? I am asking because I am able to import these ROI-ROI matrices into python for ML. But I also want to try for Region to Voxel as suggested by a paper I read. 

If anyone could enlighten me, I'd really appreciate it! Thank you