Really great avenue to attack. Definitely improved things but let me address points in order:
1. We are using motion correcting and censoring at 0.3. These seemed quite effective at the activation stage and same parameters are being used now in FC
2. For 1D file we removed motion and censors via "select -Baseline" and "cenfill none' in 3dsynth/3dcalc stage of creating our seed ROI time series.
3. For the 3d+time input file for 3dTcorr1D R^2, (per your concept) I tried using 3dSynth and 3ddcalc A-B to manually remove motion baselines and censors from the preprocessed input file.
This appears to have gotten rid of the random results (see image 1). But now it looks similar to the correlation image previously sent of 3dDeconvolve pathway where its just a wash of correlation with little differentiation.
So I tried to apply your concept as well to the 3dDeconvolve R^2 pathway, I added motion regressors and censor file into the 3dDeconvolve R^2 step (see below scripting) so it can remove them rather than manipulating the input file before hand.
No dice. While its great that they now look similar... I think we might be back at my other question about if we are approaching thresholding and FDR corrections appropriately. @Gang - do you have any feedback here?
The interesting part is that if you bump up the p value WAYYYY up there for the group results they do look very accurate for Left PAC during this task (see image 2). So it appears the analysis is working... just there is a lot of noisy ambient correlations obscuring them.
My only other thought is that perhaps there is a signal cleaning step we are missing for
task-based FC, maybe something akin to bandpass or global signal filtering for resting state..? But noting I have read in literature indicates this.
Thanks all,
~Dane
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3dDeconvolve \
-force_TR 2.5 \
-input ${subj}_prepro_all+tlrc. \
-polort 2 \
-mask ${subj}_s4_vr_zp4_cardnudg_e2a_amsk+tlrc. \
-censor $censorfile/${subj}_autocensor_AC3VC_pre-moco.1D \
-nfirst 0 \
-GOFORIT 5 \
-num_stimts 7 \
-stim_file 1 $outputdir/${subj}/${subj}_prepro_all_stim5c_dmbfitts_3dSynthRemvBase_StrgClean_${ROI}_Timeseries.1D -stim_label 1 Strg_Seed${ROI} \
-stim_file 2 $motiondir/${subj}_motion_all.1D'[0]' -stim_label 2 'roll' \
-stim_file 3 $motiondir/${subj}_motion_all.1D'[1]' -stim_label 3 'pitch' \
-stim_file 4 $motiondir/${subj}_motion_all.1D'[2]' -stim_label 4 'yaw' \
-stim_file 5 $motiondir/${subj}_motion_all.1D'[3]' -stim_label 5 'dS' \
-stim_file 6 $motiondir/${subj}_motion_all.1D'[4]' -stim_label 6 'dL' \
-stim_file 7 $motiondir/${subj}_motion_all.1D'[5]' -stim_label 7 'dP' \
-stim_base 2 -stim_base 3 -stim_base 4 -stim_base 5 -stim_base 6 -stim_base 7 \
-rout \
-tout \
-bucket $outputdir/${subj}/${subj}_prepro_all_stim5c_dmbfitts_3dSynthRemvBase_StrgClean_${ROI}_roi2wb_ply2Cen_r^2map \
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