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Hi,

I suppose what we are seeing in the top row of your figure are Freesurfer 
labels, right? I.e. you probably used the '--olab' argument with the 
'mri_surfcluster' command, and are loading each cluster from a different label 
file?

If my speculation is correct, then what you observe could be due to the 
'threshold' setting in freeview, i.e. this little box just below the label box 
in the left part of the GUI.

This threshold is by default set to zero, but lowering it to some sufficiently 
negative value (i.e. the minimum value in the 'sig' map) should also display 
those regions that seem to be missing at the moment.

At least this is what I observed when I tried to reproduce your observation, 
i.e. I could create (and reverse by setting another threshold) similar 
'cut-outs' in the cluster maps.

In addition, you could also load the ouput files that are produced by the 
'--o', '--ocn', or '--oannot' arguments of the 'mri_surfcluster' command. I 
would guess that they don't show this pattern of missing areas.

Hope this helps,

Kersten


On Di, 2019-09-03 at 14:00 +1000, Bronwyn Overs wrote:

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Dear Freesurfer mailing list,

I am trying to get to the bottom of a discrepancy between two surface based 
images generated from the output of an LME analysis. The surfaces in row 1 of 
the attached image were generated by loading the four FDR significant clusters 
that were >100mm^2 in the cluster summary file.  The surfaces in row 2 of the 
attached image were generated by loading the significance map generated for the 
same fixed effect (saved from the LME), and thresholding at the FDR corrected 
p-value. The question I have is why are there such large swatches of the 
cortical surface in the row 2 images that are labelled as log10 p = 5, when 
they are not included in the most significant and largest clusters that were 
found in the cluster summary file?


Kind regards,


Bronwyn Overs

Research Assistant

[cid:1567613630.3700.24.camel@dzne.de]


Neuroscience Research Australia
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