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Wed, 8 Aug 2018 18:08:05 +0100

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 ```Dear Dr Matthew Webster, this is very helpful! thank you so much! kindly I would like to ask one last follow-up question about the mask that we use in the command Randomise. However, I totally, understood your responses! The motivation of the question is to expand my understanding! Kindly, is there any relationship between the size of the mask and the false positives that randomise may generate? In other words, If we use a whole brain mask and then we threshold the statistical maps at 0.05, that means there is 5% possibility for false positives. If we threshold at 0.01 that means there is a possibility of 1% false positives. How about the size of the mask (or the number of voxels in the mask). I assume that reducing the size of the mask would lead to lower number of voxels as a result this will increase the possibility for false positives. Is this correct? Also, using smaller mask like the thalamus to do an ROI based voxel-wise correlation would increase the possibility to find localized correlations similar to what we find in fMRI data when we use an ROI and we find activation in the same ROI, is this correct? I deeply thank you for any clarification! Sincerely! John Hello,          The original t-statistic can be converted to R^2 via R^2=t^2/(t^2+dof) The correlation-coefficient is the square-root of this ( taking the same sign as t ) Kind Regards Matthew -------------------------------- Dr Matthew Webster FMRIB Centre John Radcliffe Hospital University of Oxford Dear Dr Matthew Webster, I genuinely appreciate your great responses. I would appreciate if you shed more light on #2. Would you please clarify how I can transform the p values to partial correlation co-efficients. Thanks again, John On 6 Aug 2018, at 21:10, John anderson <[log in to unmask]> wrote: Dear Dr Anderson Winkler, I have two groups of subjects (patients n=85 and healthy controls n=33). I would like to use Randomise in a voxel-wise correlation analyses between clinical scales and whole brain signal. For that objective I ran the following command: randomise -i 4D_data.nii.gz -o vw -m MNI152_T1_2mm_brain_mask.nii.gz -d design.mat -t design.con -n 5000 -T I threshold the resultant statistical map (vw_tfce_corrp_tstat1.nii.gz) at p<0.05 and this showed significant clusters for some of the analyses in specific region of interest (ROI) in the brain that support the analysis-hypothesis. I mean, I found correlation in whole brain voxel-wise correlation analysis between the clinical scales and brain MR signal in pathologically relevant regions where I really expect a correlation. Some other analyses were not significant at p<0.05 but I saw clusters of correlation between the clinical scales and brain signal at p<0.3 in specific regions of the brain where I really expect correlation. In order to get around this issue (i.e. correlations are not significant but I can see it in pathologically relevant regions using sub significant-thresholds): To make these correlations significant, I replaced the whole brain mask in "randomise" by another mask for an ROI where I expect the correlation to be significant. I ran the previous randomise command and indeed the non significant correlation become significant at p<0.05. My questions are: 1- Is this procedure correct? I mean replacing the whole brain mask by a smaller mask to narrow the voxel-wise analysis from whole brain voxel-wise correlation to an "ROI based voxel-wise correlation". Can I still able to report such analysis in a manuscript under "ROI based voxel-wise correlation" instead of "whole brain correlation analysis"? 2- What is the difference between this "ROI based voxel-wise correlation" and pearson correlation within the ROI (between the clinical scales and the MR signal in the ROI)? 3- Are there any rules (i.e size of the mask, number of the voxels in the mask, ...) for choosing the mask in the flag "m" in Randomise. In other words-mathematically, should we always use whole brain mask to reduce the false positives after correcting the results to multiple comparison? Are the smaller masks would increase the false postivities? Let's say we expect correlation in a small regions of interest (e.g thalamus). Whole brain correlation would not show the effect significat. Can I replace whole brain mask by a mask for the thalamus to make the correlations significant. Thank you so much for any clarification, John ######################################################################## To unsubscribe from the FSL list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1 To unsubscribe from the FSL list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1 ######################################################################## To unsubscribe from the FSL list, click the following link: https://www.jiscmail.ac.uk/cgi-bin/webadmin?SUBED1=FSL&A=1```