Dear Doug,

I ran the following command, but it still gives me network-wise cortical measures. But I am actually looking for cortical measures of each region within each network:

mris_anatomical_stats -th3 -mgz -cortex 2500a/label/lh.cortex.label -f 2500a/stats/lh.aparc.Yeo7.stats -b -a Yeo2011_7Networks_N1000.annot -c 2500a/label/aparc.annot.Yeo7.ctab 2500a lh white

INFO: using TH3 volume calc

INFO: assuming MGZ format for volumes.

INFO: using 2500a/label/lh.cortex.label as mask to calc cortex NumVert, SurfArea and MeanThickness.

computing statistics for each annotation in Yeo2011_7Networks_N1000.annot.

reading volume /Volumes/HD-DHTR6/01_Project_FreeSurfer/2500a/mri/wm.mgz...

reading input surface /Volumes/HD-DHTR6/01_Project_FreeSurfer/2500a/surf/lh.white...

Using TH3 vertex volume calc

Total face volume 284736

Total vertex volume 281405 (mask=0)

reading input pial surface /Volumes/HD-DHTR6/01_Project_FreeSurfer/2500a/surf/lh.pial...

reading input white surface /Volumes/HD-DHTR6/01_Project_FreeSurfer/2500a/surf/lh.white...

reading colortable from annotation file...

colortable with 8 entries read (originally MyColorLUT)

Saving annotation colortable 2500a/label/aparc.annot.Yeo7.ctab

table columns are:

number of vertices

total surface area (mm^2)

total gray matter volume (mm^3)

average cortical thickness +- standard deviation (mm)

integrated rectified mean curvature

integrated rectified Gaussian curvature

folding index

intrinsic curvature index

structure name

atlas_icv (eTIV) = 1393613 mm^3 (det: 1.397882 )

lhCtxGM: 279618.799 278859.000 diff= 759.8 pctdiff= 0.272

rhCtxGM: 283065.244 282415.000 diff= 650.2 pctdiff= 0.230

lhCtxWM: 221173.591 221952.500 diff= -778.9 pctdiff=-0.352

rhCtxWM: 221330.870 222469.500 diff=-1138.6 pctdiff=-0.514

SubCortGMVol 57065.000

SupraTentVol 1072714.504 (1069458.000) diff=3256.504 pctdiff=0.304

SupraTentVolNotVent 1066020.504 (1062764.000) diff=3256.504 pctdiff=0.305

BrainSegVol 1210413.000 (1208649.000) diff=1764.000 pctdiff=0.146

BrainSegVolNotVent 1201232.000 (1200612.504) diff=619.496 pctdiff=0.052

BrainSegVolNotVent 1201232.000

CerebellumVol 138356.000

VentChorVol 6694.000

3rd4th5thCSF 2487.000

CSFVol 723.000, OptChiasmVol 112.000

MaskVol 1616427.000

8855 5731 2791 0.977 1.446 0.081 0.035 129 14.2 FreeSurfer_Defined_Medial_Wall

28199 18195 45320 2.362 0.630 0.131 0.031 374 34.3 7Networks_1

21313 13976 38622 2.484 0.632 0.119 0.027 239 22.6 7Networks_2

16377 10929 29338 2.522 0.521 0.116 0.024 192 15.7 7Networks_3

12076 8058 25013 2.797 0.650 0.119 0.028 146 13.2 7Networks_4

11151 7626 29041 3.067 0.733 0.127 0.033 167 14.5 7Networks_5

16205 10841 32923 2.607 0.631 0.123 0.028 228 17.6 7Networks_6

34755 23626 78358 2.825 0.621 0.125 0.029 494 39.7 7Networks_7

On Fri, Jul 17, 2020 at 9:35 AM Douglas N. Greve <dgreve@mgh.harvard.edu> wrote:

Try something like
mris_anatomical_stats -th3 -mgz -cortex ../label/lh.cortex.label -f ../stats/lh.yeo.stats -b -a ../label/lh.yeo.annot -c ../label/yeo.annot.ctab 1040 lh white

Assuming that your yeo atlas is in $SUBJECTS_DIR/$subject/label/lh.yeo.annot

On 7/15/2020 2:05 PM, Martin Juneja wrote:
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Dear Doug,

Thanks for your response !

Yes, I have Yeo atlas in the individual space, and recon-all.log has the following command:

mris_anatomical_stats -th3 -mgz -cortex ../label/lh.cortex.label -f ../stats/lh.aparc.stats -b -a ../label/lh.aparc.annot -c ../label/aparc.annot.ctab 1040 lh white \n
computing statistics for each annotation in ../label/lh.aparc.annot.

Could you please help me in customizing this because it seems it gives me stats for each annotation e.g. stats for 34 areas (for Desikan atlas) and 7 networks (for Yeo 7 network, I think this is averaged over each network, correct?), but I am looking for stats of the regions which constitute those networks (e.g. stats for the areas which are part of the default mode network i.e., 4 individual stats of 4 individual red colored regions in the following figure).
On Wed, Jul 15, 2020 at 8:54 AM Douglas N. Greve <dgreve@mgh.harvard.edu> wrote:
If you have the Yeo atlas in the individual space, you can use mris_anatomical_stats to compute stats the same as in the Desikan atlas. Look in recon-all.log for the command line and customize it as needed

On 7/14/2020 5:00 PM, Martin Juneja wrote:
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Hi experts,

I extracted network-wise cortical measures (i.e., 7 cortical thickness values for 7 networks for Yeo atlas).

I was wondering if there is a way to get the cortical thickness of each ROI within each of these networks e.g., cortical thickness values of all the ROIs which constitute default-mode network of Yeo's 7 network parcellation, and then cortical thickness values of all the ROIs which constitute limbic network of Yeo's 7 network parcellation, and so on.

I know Desikan atlas can be used to get morphometry measures of 34 ROIs per hemisphere. But the problem is that e.g., default-mode ROIs from Desikan atlas do not completely overlap with the DMN of 7-network parcellation from Yeo atlas. In other words, superior frontal cortex from default-mode network of Yeo 7 network parcellation is a big chunk compared to several small ROIs (some partial and some full) in Desikan atlas, so I do not see any way how to find ROIs which just match with that superior frontal cortex of default-mode of Yeo's 7 network.

Any help would be much appreciated !
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