On 6/30/2022 2:31 PM, Mark Ebden wrote:

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Hi Douglas,

Thank you. From your explanation, the software's numbers from 0 to 1 aren't corrected p-values -- specifically, they aren't corrections in the well-accepted sense of Bonferroni corrections or other analagous multiple-comparisons corrections. They seem to be percentiles (what you refer to as ranks), where 1 corresponds to an extreme ranking in the basket of 10k, and 0 indicates the other extreme, per voxel/vertex.
They are -log10(pvalue)*sign(effect) as with all FS.

Hope I have that right. I'm also not sure what you meant about converting the noise into p-values. Below is my interpretation of what the pseudocode would be. Is it right? I suspect it's not quite ready yet for sharing, because the concept of a maximum needs to be inserted.

   for each voxel:
      p0 = the p-value from a t-test or similar between the two groups, as they are
      x0 = -log10(p0)
      for i from 1 to 10k:
         perform a random split between the two groups comprising the contrast analysis
         p = the p-value from a t-test or similar between the two groups
         x[i] = -log10(p)
      r = percentile indicating where x0 falls within the distribution of x's 10k values
      # N.B.: r represents the result for this voxel, from 0 to 1, to go in cache.th40.pos.sig.voxel.mgh

Almost, it is more like this:

for i = 1 to 10k
  construct a z map (white gaussian noise) on the surface
  smooth by a given FWHM (look in glmfit/fwhm.dat)
  renormalize the z map so that std=1
  find the voxel with the largest z value; keep track of the z value (convert the z to a p)
Now you have a list of 10k largest z values (or smallest p-values)
  -- for mc-z simulations these are cached in $FREESURFER_HOME/average/mult-comp-cor

For each voxel in your data
  get uncorrected p-value
  compute a corrected p-value by counting the number in the 10k list that are smaller than the uncorrected p-value (divide by 10k)
  compute the -log10(corrected pvalue)



Thanks for any help. Also, how would the pseudocode differ for sig.cluster.mgh vs sig.voxel.mgh?

Thanks,

Mark

From: freesurfer-bounces@nmr.mgh.harvard.edu <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Douglas N. Greve <dgreve@mgh.harvard.edu>
Sent: Sunday, June 19, 2022 10:37 AM
To: freesurfer@nmr.mgh.harvard.edu <freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] How is cache.th40.pos.sig.voxel.mgh computed, exactly?
 
from mri_glmfit-sim --help csdbase.sig.voxel.mgh - the sig volume corrected for multiple comparisons on a voxel-wise basis. The threshhold and sign are irrelevant. The value at each voxel is the corrected -log10(p-value) for that voxel.
from mri_glmfit-sim --help

csdbase.sig.voxel.mgh - the sig volume corrected for multiple comparisons on a voxel-wise basis. The threshhold and sign are irrelevant. The value at each voxel is the corrected -log10(p-value) for that voxel.

It is computed from a simulation in which gaussian noise is smoothed, then converted to p-values (log10(p)), then the maximum log10(p) is found. This is repeated 10,000 times to give 10k maximums. A corrected p-value for each voxel is then computed based upon the rank of the raw pvalue in this list of 10k.


On 6/10/2022 4:14 PM, Mark Ebden wrote:

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Hi,

I was wondering if anyone knows how the numbers in cache.th40.pos.sig.voxel.mgh are computed, or where I'd look to learn this. There is a one-liner in the documentation but I'd like the mathematical details of the correction etc. so I can determine what the final numbers (from 0 to 1) represent. I've noticed from browsing the plot in FreeView that significant areas have values close to 1, which is puzzling.

Thanks if you could point me in the right direction.

Kind regards,

Mark

Mar

 

                                               

Mark Ebden, D.Phil  

(Pronouns: He/Him)  

Research Analyst  

  

The Hospital for Sick Children  

555 University Ave, Toronto ON M5G 1X8  

P 416.888.0841  



 




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