diff --git a/matlab/get_prior_info.m b/matlab/get_prior_info.m
index 2bcc30c3e..f64077858 100644
--- a/matlab/get_prior_info.m
+++ b/matlab/get_prior_info.m
@@ -107,14 +107,13 @@ function get_prior_info(info)
     end
     
     if info==2% Prior optimization.
-       
+        % Initialize to the prior mode if possible
         k = find(~isnan(bayestopt_.p5));
         xparam1(k) = bayestopt_.p5(k);
-        
+        % Pertubation of the initial condition.
         look_for_admissible_initial_condition = 1;
         scale = 1.0;
         iter  = 0;
-        
         while look_for_admissible_initial_condition
             xinit = xparam1+scale*randn(size(xparam1));
             if all(xinit>bayestopt_.p3) && all(xinit<bayestopt_.p4)
@@ -128,22 +127,20 @@ function get_prior_info(info)
                 end
             end
         end
-        
+        % Maximization
         [xparams,lpd,hessian] = ...
         maximize_prior_density(xinit, bayestopt_.pshape, ...
                                bayestopt_.p6, ...
                                bayestopt_.p7, ...
                                bayestopt_.p3, ...
                                bayestopt_.p4);
-       disp(' ')
-       disp(' ')
-       disp('------------------')
-       disp('PRIOR OPTIMIZATION')
-       disp('------------------')
-       disp(' ')
-       
-       
-       
+        % Display the results.
+        disp(' ')
+        disp(' ')
+        disp('------------------')
+        disp('PRIOR OPTIMIZATION')
+        disp('------------------')
+        disp(' ')
        for i = 1:length(xparams)
            disp(['deep parameter ' int2str(i) ': ' get_the_name(i,0) '.'])
            disp(['  Initial condition ....... ' num2str(xinit(i)) '.'])