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help > two sample t test result (seed-to-voxel analysis)
Jun 3, 2020 03:06 PM | Dong An
two sample t test result (seed-to-voxel analysis)
Dear Alfonso and CONN experts,
First, I very appreciate your great contribution to CONN toolbox. It is great!
I am new at using CONN, and I am confused about my two sample t test result. I selected right amygdala as ROI, and used ROI-to-voxel analysis type to compare patient and control resting state functional connectivity. I think if amygdala is a major cluster in both patient and control groups, it should not appear in 2 sample t test result.
But in my result, it is surprising that amygdala is involved in the biggest clusters and the peak location is at right amygdala.
Here is how I did:
I imported fmriprep preprocessed data (52 subjects: 31 patients 21 controls) into CONN, for right amygdala ROI, I used the Harvard-Oxford structural atlas by default in CONN. For 1st level covariates, I removed all covariates (because the fmriprep preprocessed data have been denoised using ICA-aroma). For 2nd level covariates, I added "patient group"(enter 1 for 31 patients and enter 0 for 21 controls), and added "control group(enter 0 for 31 patients and enter 1 for 21 controls). In denoising section, I added only CSF (5p) and white matter (5p) as covariates to regress, I did not add effect of rest. Then I click linear detrending, pass filtering: [0.01 inf] after regression. Then I did 1st level analysis (the setting is: functional connectivity weighted GLM correlation(bivariate) no weighting ), and 2nd level analysis design is: patient, control [1 -1] rest [1] seeds/sources: right amygdala [1].
Please see attached screenshot of "result explorer"; after t sample t test, the peak coordinate of the biggest cluster is (22,-14,-12), and please see attached .txt file containing all subregions of this cluster. I do not understand why right and left amygdala is still involved in this biggest cluster after 2 sample t test. Also, when I tried adding age or sex as covariates: patient, control, age [1 -1 0], amygdala still appear. Could you please tell me where I was wrong?
Thank you in advance!
Xinyuan
First, I very appreciate your great contribution to CONN toolbox. It is great!
I am new at using CONN, and I am confused about my two sample t test result. I selected right amygdala as ROI, and used ROI-to-voxel analysis type to compare patient and control resting state functional connectivity. I think if amygdala is a major cluster in both patient and control groups, it should not appear in 2 sample t test result.
But in my result, it is surprising that amygdala is involved in the biggest clusters and the peak location is at right amygdala.
Here is how I did:
I imported fmriprep preprocessed data (52 subjects: 31 patients 21 controls) into CONN, for right amygdala ROI, I used the Harvard-Oxford structural atlas by default in CONN. For 1st level covariates, I removed all covariates (because the fmriprep preprocessed data have been denoised using ICA-aroma). For 2nd level covariates, I added "patient group"(enter 1 for 31 patients and enter 0 for 21 controls), and added "control group(enter 0 for 31 patients and enter 1 for 21 controls). In denoising section, I added only CSF (5p) and white matter (5p) as covariates to regress, I did not add effect of rest. Then I click linear detrending, pass filtering: [0.01 inf] after regression. Then I did 1st level analysis (the setting is: functional connectivity weighted GLM correlation(bivariate) no weighting ), and 2nd level analysis design is: patient, control [1 -1] rest [1] seeds/sources: right amygdala [1].
Please see attached screenshot of "result explorer"; after t sample t test, the peak coordinate of the biggest cluster is (22,-14,-12), and please see attached .txt file containing all subregions of this cluster. I do not understand why right and left amygdala is still involved in this biggest cluster after 2 sample t test. Also, when I tried adding age or sex as covariates: patient, control, age [1 -1 0], amygdala still appear. Could you please tell me where I was wrong?
Thank you in advance!
Xinyuan
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Title | Author | Date |
---|---|---|
Dong An | Jun 3, 2020 | |
Alfonso Nieto-Castanon | Jun 9, 2020 | |
Dong An | Jun 10, 2020 | |