All, 

I am working on a project where I have determined a specific structure from CONN analyses but now want to calculate the "dispersion" of that ROI for each subject. This metric is the variance of the signal / the mean of the signal.  This paper uses it with SPM preprocessing:

Mcafee SS, Robinson G, Gajjar A, et al. Cerebellar mutism is linked to midbrain volatility and desynchronization from speech cortices. Brain. 2023;146(11):4755. doi:10.1093/BRAIN/AWAD209

"Preprocessing was performed in SPM12 (https://www.fil.ion.ucl. ac.uk/spm/software/spm12/), which included slice timing correction, motion correction, spatial normalization and smoothing. Motion-corrected EPI time-series data were co-registered to the na- tive T1 MPRAGE image for each session, and the T1 image was normalized to an anatomic template. The same transformation was then applied to the EPI data for spatial normalization of the fMRI time series.  ... Confounding signals from white matter and CSF were removed prior to further analysis." 

However, when I pull the ROI traces from the "project> results> preprocessing> ROI_Subject001_Condition001.mat" files - they are all zero or near zero-meaned, which results in dispersion values in the Xe17 range. I have tried to modify the preprocessing steps to avoid linear detrending with no solution. 

Is there a way to pull the ROI time-series without the zero-meaning of the signal? Which step of the preprocessing would be causing this? I assume the denoising CompCor - but I do not want to eliminate the confound correction and denoising process entirely. I would like to pull the traces from CONN to ensure most of the analysis is consistent. 

Any guidance on accomplishing this would be helpful. 

Thank you,