Is there anyone here who does continuous natural stimulation(auditory)? I am deeply troubled by the results of my experiment.
I have a problem that has been bothering me for a long time, we have been trying to find out why, but nothing.
In our experiment, the subjects are instructed to listen to two four-minute stories(one story, one run), and we want to make the correlation of two runs. But we found the ventricles lit up after correlation(a screenshot in attach file), does anyone have the same problem as me？
First, I’m not sure this is normal…
If it’s not normal, is there anything other than head motion that could be causing this.(Because the subject had smaller head motion,<3mm).
I also used the same script to analyze my colleague’s experimental data. His experiment was watching movies and then doing correlation. The ventricles don’t light up unless the threshold is very low. It looks normal.
This is my script.
afni_proc.py -subj_id sub6.120 \
-dsets 6.120.1+orig.HEAD 6.120.4+orig.HEAD \
-blocks despike tshift align tlrc volreg blur mask scale regress \
-copy_anat anat6+orig \
-align_opts_aea -cost lpc+ZZ -gaint_move \
-tlrc_base TT_N27+tlrc \
-volreg_align_to MIN_OUTLIER \
-blur_size 6.0 \
-regress_apply_mot_types demean deriv \
3dTcat -prefix s6.120.1 errts.sub6.120.tproject+tlrc’[0…119]’
3dTcat -prefix s6.120.4 errts.sub6.120.tproject+tlrc’[120…239]’
3dTcorrelate -prefix 6.120.1_4 s6.120.1+tlrc s6.120.4+tlrc
Thanks a lot,
You have mentioned “small head motion, <3mm”. Actually, I would say that large headmotion can still fit under that categorization.
Are you running the new afni_proc.py APQC-HTML stuff? If so, do you have the enorm+outlier plot that you could show here (or send offline)?
And it looks like you are not censoring points with motion/outliers… that might further lead to suspicion of motion. Consider if you are showing a funny movie, and subjects giggle at the same point-- that would lead to stimulus correlated motion, and something that would show up precisely as high correlation in a naturalistic design.
I will also PM you instructions for uploading the data if you would like me to take a look in vivo.
Also, correlations so specific to the ventricles can be enhanced by breathing and heart pulsations, which is probably why Peter asked about your acquisition parameters (e.g. TR or multi-band options). But it also seems possible that you are choosing a seed location that hits or is in a ventricle (the question on registration may be alluding to that). Exactly how are you choosing and applying a seed? Especially if it is just a single coordinate or a “sphere”, have you looked to see where it is on each subject?
And this question seems to have been opened in at least 3 separate threads now, two of which are active. I recommend ceasing to reply on this one, and to only continue on the one that Peter had initially replied to here:
I went ahead and merged the two topics and deleted the third thread.
Regarding the bright ventricles, I think Rick’s suggestion about respiration is the main culprit here, related to Rasmus Birn old topic: