enh: reorganize section about regressors correlation

docs/users/howto_read_fmriprep_visual_report.md

@@ -186,9 +186,22 @@ Note on how variance and scaling affects this display? (in other words, spikes a
 
 ### Correlations among nuisance regressors
 
-This may also be addressed in more depth by the confounds and regressors documentation (link to page)
-Can be used to diagnose partial volume effects
-PVE indicated by high correlations of a confound time series (or several) with the global signal
+This report presents a plot of correlations among confound regressors. The left-hand panel shows the matrix of correlations among selected confound time series as a heat-map. The right-hand panel displays the correlation of selected confound time series with the mean global signal computed across the whole brain; the regressors shown are those with greatest correlation with the global signal. These plots can be used to guide selection of a confound model or to assess the extent to which tissue-specific regressors correlate with global signal.; e.g if two regressors are highly correlated, it is recommended to include in the confound model only one of the two.
+
+[NEEDS COMPLETION]
+
+* Selection of a confound model
+    * Good:
+        * Carefully choose a serie of regressors that are not highly correlated to include in the confound model.
+    * Bad: 
+        * Include in the confound model two regressors that are highly correlated
+    * Common pitfall in interpreptation:
+        * The CompCor components do not correlate with each other by construction. As such, a block of zero-correlation is visible near the diagonal.
+
+* Assessement of partial volume effect
+    * Good:
+    * Bad:
+        * High correlation of confound time series with the global signal is an indicator of high partial volume effect.
 
 ### ICA-AROMA
 What you’re looking at: