Changed: Save both plasticity and aging model for long. data as default.

Changed: CUpdated html doc. Changed paths: M CHANGES.txt M cat_batch_long.sh M cat_conf_long.m M doc/index.html
ChristianGaser · Feb 14, 2024 · ef165ea · ef165ea
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diff --git a/CHANGES.txt b/CHANGES.txt
@@ -1,4 +1,15 @@
 ------------------------------------------------------------------------
+r2540 | gaser | 2024-02-14 11:18:19
+
+Changed paths:
+ M CHANGES.txt
+ M cat_batch_long.sh
+ M cat_conf_long.m
+ M doc/index.html
+
+Changed: Save both plasticity and aging model for long. data as default.
+Changed: CUpdated html doc.
+------------------------------------------------------------------------
 r2538 | gaser | 2024-02-13 17:37:40
 
 Changed paths:

diff --git a/cat_batch_long.sh b/cat_batch_long.sh
@@ -28,7 +28,7 @@ spm12dir=spm12
 LOGDIR=$PWD
 export_dartel=0
 output_surface=1
-long_model=1
+long_model=3
 printlong=2 
 time=`date "+%Y%b%d_%H%M"`
 defaults_tmp=/tmp/defaults$$.m
@@ -120,6 +120,9 @@ parse_args ()
         fi
         shift
         ;;
+      --small* | -l*)
+        long_model=1
+        ;;
       --large* | -l*)
         long_model=2
         ;;
@@ -341,14 +344,16 @@ USAGE:
   -fg         | --fg                    do not run matlab process in background
   -ns         | --no-surf               disable surface and thickness estimation
   -e          | --export-dartel         export affine registered segmentations for Dartel
-  -large      | --large                 use longitudinal model for detecting large changes (i.e. ageing or development)
+  -large      | --large                 use longitudinal model for detecting large changes (i.e. ageing)
+                                        This option is only thought for compatibility with older scripts. Do not use that option together with the model flag. 
+  -small      | --small                 use longitudinal model for detecting smaller changes (i.e. plasticity)
                                         This option is only thought for compatibility with older scripts. Do not use that option together with the model flag. 
   -nj         | --nojvm                 supress call of jvm using the -nojvm flag
   -model      | --model                 longitudinal model:
                                           0 - detect large changes with brain/head growth (i.e. developmental effects)
                                           1 - detect small changes (i.e. due to plasticity)
-                                          2 - detect large changes (i.e. ageing or development)
-                                          3 - save results for both models 1 and 2
+                                          2 - detect large changes (i.e. ageing)
+                                          3 - save results for both models 1 and 2 (default)
   -printlong  | --printlong             print longitudinal report
                                           0 - no printing
                                           1 - print report but only volume results

diff --git a/cat_conf_long.m b/cat_conf_long.m
@@ -108,8 +108,9 @@
 longmodel.labels = {
   'Optimized for detecting small changes (i.e. plasticity/learning effects)', ...
   'Optimized for detecting large changes (i.e. aging effects)', ...
-  'Optimized for detecting large changes with brain/head growth (i.e. developmental effects)'}; 
-longmodel.values = {1 2 0};
+  'Optimized for detecting large changes with brain/head growth (i.e. developmental effects)', ...
+  'Save both plasticity and aging models'};
+longmodel.values = {1 2 0 3};
 if expert 
   % Add the internal values and the special plasticity & aging model for 
   % developer only because it is not fully working now (RD20220317).
@@ -119,11 +120,8 @@
     longmodel.labels{4} = [longmodel.labels{3}(1:end-1) ' V2; 4)']; 
     longmodel.values{4} = 4;
   end
-  longmodel.labels{3} = [longmodel.labels{3}(1:end-1) '; 0)']; 
-  longmodel.labels{3 + expert} = 'Save plasticity and aging models (3)';
-  longmodel.values{3 + expert} = 3;
 end
-longmodel.val  = {1};
+longmodel.val  = {3};
 longmodel.help = {
 'The longitudinal pre-processing in CAT12 has been developed and optimized to detect subtle effects over shorter periods of time (e.g. brain plasticity or training effects after a few weeks or even shorter periods of time) and is less sensitive to detect larger changes over longer periods of time (e.g. ageing or developmental effects). To detect larger effects, we also offer a model that additionally takes into account deformations between time points. The use of deformations between the time points makes it possible to estimate and detect larger changes, while subtle effects over shorter periods of time in the range of weeks or a few months can be better detected with the model for small changes.'
 ''

diff --git a/doc/index.html b/doc/index.html
@@ -1757,7 +1757,7 @@ <h4 id="long_process">Preprocessing of longitudinal data</h4>
             </ul>
 
             <p>&rarr; For all other options you can follow the instructions for preprocessing of cross-sectional data as described before. Please note that not all writing options are available for longitudinal data.</p>
-            <p>For the naming conventions of all written files see <a href="#naming">Naming Convention of Output Files</a>. The GM segments are mwp1r* (or mwmwp1r* for the model with larger changes) , the WM segments are named mwp2r* (mwmwp2r*) if you have selected the option to modulate the data. Without modulation the leading &quot;m&quot; is omitted.</p>
+            <p>For the naming conventions of all written files see <a href="#naming">Naming Convention of Output Files</a>. The GM segments are mwp1r* for the plasticity model or mwmwp1r* for the aging model with larger changes, the WM segments are named mwp2r* (mwmwp2r*). Without modulation the leading &quot;m&quot; is omitted.</p>
 
             <!-- ############################# -->
             <h4>Statistical analysis of longitudinal data - overview</h4>
@@ -3055,8 +3055,8 @@ <h4>Images and surfaces of longitudinal data</h4>
             <p>Furthermore, if you select the longitudinal model for detecting larger changes (e.g. ageing or developmental effects) the segmented images are additionally indicated by a leading &quot;mw&quot; due to the additional warping and modulation steps.</p>
 
             <u>Example:</u><br>
-            mwp1r * - gray matter<br>
-            mwmwp1r* - gray matter (longitudinal model for detecting larger changes)<br>
+            mwp1r * - gray matter (plasticity model)<br>
+            mwmwp1r* - gray matter (aging model for detecting larger changes)<br>
 
             <!-- ############################# -->
             <h4>Reports (saved in subfolder &quot;report&quot;)</h4>