help
help > RE: Extremely high values of contrast estimates in SPM after using CONN preprocessed and denoised data
Mar 5, 2019 05:03 PM | Alfonso Nieto-Castanon - Boston University
RE: Extremely high values of contrast estimates in SPM after using CONN preprocessed and denoised data
Hi Avantika,
I would suggest trying to set the "grand mean scaling" option in SPM first-level estimation off, since that looks like a possible culprit for this behavior (after band-pass filtering, the mean functional data is zero at every voxel, so global signal scaling -and similarly any other default mechanisms that rely on the average BOLD signal containing anatomical information/features- are likely to fail in rather unexpected ways). Let me know if that works
Best
Alfonso
Originally posted by avantika mathur:
I would suggest trying to set the "grand mean scaling" option in SPM first-level estimation off, since that looks like a possible culprit for this behavior (after band-pass filtering, the mean functional data is zero at every voxel, so global signal scaling -and similarly any other default mechanisms that rely on the average BOLD signal containing anatomical information/features- are likely to fail in rather unexpected ways). Let me know if that works
Best
Alfonso
Originally posted by avantika mathur:
Hi Conn users,
After following the following posts,
https://www.nitrc.org/forum/message.php?...
I used the alternative method to import conn preprocessed data in SPM which is the following :
Entering the preprocessed/denoised timeseries into SPM to perform the first-level analyses.
The data I am analyzing is children data thus, ART was used at liberal threshold in preprocessing [Global signal z value threshold 10, subject motion 5 mm]. I did not have the "effect of Condition X" entered as confounding effects during Denoising.
I used the file generated after conn preprocessing and denoising...the niftiDATA_Subject001_Condition000 and further defined first-level design matrices within SPM, specified masking threshold to -Inf in first level analysis [https://www.nitrc.org/forum/message.php?msg_id=14852].
After doing first level analysis and group level analysis [10 subjects], I get weird beta estimate values - which are extremely high . Attached are the bar plots for the same [1st bar-chart - single subject, 2nd bar chart - group of 10 subjects]. Beta values should not be this high.
Can someone direct me where I am going wrong?
Avantika
After following the following posts,
https://www.nitrc.org/forum/message.php?...
I used the alternative method to import conn preprocessed data in SPM which is the following :
Entering the preprocessed/denoised timeseries into SPM to perform the first-level analyses.
The data I am analyzing is children data thus, ART was used at liberal threshold in preprocessing [Global signal z value threshold 10, subject motion 5 mm]. I did not have the "effect of Condition X" entered as confounding effects during Denoising.
I used the file generated after conn preprocessing and denoising...the niftiDATA_Subject001_Condition000 and further defined first-level design matrices within SPM, specified masking threshold to -Inf in first level analysis [https://www.nitrc.org/forum/message.php?msg_id=14852].
After doing first level analysis and group level analysis [10 subjects], I get weird beta estimate values - which are extremely high . Attached are the bar plots for the same [1st bar-chart - single subject, 2nd bar chart - group of 10 subjects]. Beta values should not be this high.
Can someone direct me where I am going wrong?
Avantika
Threaded View
| Title | Author | Date |
|---|---|---|
| avantika mathur | Mar 2, 2019 | |
| Alfonso Nieto-Castanon | Mar 5, 2019 | |
| avantika mathur | Mar 7, 2019 | |
| Sneha Sheth | Sep 27, 2021 | |