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-      <p align="center" style="text-align:center;">This is <b>CAT12.9 (r2186) from 2023-04-26</b><br />You can update your copy of CAT12 here: <a href="matlab:cat_update(1);">Check for update</a>.<br />If you find any bug, please report them at <a href="mailto:[email protected]">[email protected]</a>.</p>
+      <p align="center" style="text-align:center;">This is <b>CAT12.9 (r2219) from 2023-07-17</b><br />You can update your copy of CAT12 here: <a href="matlab:cat_update(1);">Check for update</a>.<br />If you find any bug, please report them at <a href="mailto:[email protected]">[email protected]</a>.</p>
       <h1 style="text-align:center;"><img src="images/CAT.png" width=40% height=auto alt="CAT" ></h1>
 
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@@ -3707,8 +3707,15 @@ <h5>References for quality control</h5>
             <h2 id="faq">FAQ</h2>
 
             <details>            
-              <summary><u>The old "Check Sample Homogeneity" tool was quite useful for finding duplicate subjects in large samples. The new homogeneity tool, which uses Z-score, no longer supports this.</u></summary>
-              Estimating the Z-score is much faster than calculating the covariance matrix between all scans, especially for larger samples. Furthermore, newer CAT12 versions use the quatric mean Z-score, which gives outliers a greater weight and make them more obvious in the plot. However, the old tool is still available <a class="function" href="matlab:spm_jobman('interactive','','spm.tools.cat.tools.check_homogeneity');">here</a>.
+              <summary><u>Can we use CAT12 for white matter volume analysis?</u></summary>
+              Of course, CAT12 can examine white matter (WM). However, keep in mind that there are more sensitive methods for WM, such as DTI, and the sensitivity for WM may be lower compared to grey matter. This is because white matter regions are often quite homogeneous in T1-weighted images, making it more difficult to find differences.<br>
+              However, if you do find something, all is fine, but if you do not, it may simply be due to the lower sensitivity.</a>.
+            </details>            
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+            <details>            
+              <summary><u>The old "Check Sample Homogeneity" tool was quite useful for finding duplicate subjects in large samples. The new homogeneity tool, which uses Z-score, no longer supports this. What is the difference between these measures?</u></summary>
+              Both homogeneity measures differ in their calculations and it’s difficult to say which is a better and more suitable measure. I prefer the new z-score measure over correlation since it’s quicker to estimate for larger samples and aligns with the idea that outliers are often identified by the sample standard deviation. The z-score is computed as the difference between the sample mean and the voxel value, divided by the standard deviation, and averaged across all voxels.<br>
+              Furthermore, newer CAT12 versions use the quatric mean Z-score, which gives outliers a greater weight and make them more obvious in the plot. However, the old tool is still available <a class="function" href="matlab:spm_jobman('interactive','','spm.tools.cat.tools.check_homogeneity');">here</a>.
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@@ -3726,7 +3733,7 @@ <h2 id="faq">FAQ</h2>
               <summary><u>How can I run CAT12 on a HPC system?</u></summary>
               On the HPC I would prefer to call CAT12 from the shell without display. Here you can either use the standalone version of CAT12 (without need of Matlab license) or the standard version. <br>
               The <a href="https://neuro-jena.github.io/enigma-cat12/">ENIGMA-CAT12 protocol</a> describes the available steps. You can decide with two flags (-ns, -e) whether you call the standalone or standard version.<br>
-              Standalone version:<brY
+              Standalone version:<br>
               /software/CAT12.8.2_MCR/standalone/cat_standalone.sh -m /software/CAT12.8.2_MCR/v93 \<br>
               -b /software/CAT12.8.1_MCR/standalone/cat_standalone_segment_enigma.m \<br>
               /data/enigma-data/raw/sub*.nii.gz<br>
@@ -3769,7 +3776,7 @@ <h2 id="faq">FAQ</h2>
 
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               <summary><u>Is there a workflow to use the resampled surfaces for permutation analyses in FSL randomise or PALM?</u></summary>
-              Randomize will not work with surfaces, but PALM supports gifti files. Thus, the resampled files should work with PALM.
+              Randomising will not work with surfaces, but PALM does support gifti files. So the resampled files should work with PALM. However, if you are an SPM user, the TFCE toolbox may be easier to use as you can use your existing SPM design. The TFCE toolbox supports threshold free cluster enhancement and is seamlessly integrated with CAT12.
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