diff --git a/mvpa/cosmo_pca.m b/mvpa/cosmo_map_pca.m
similarity index 92%
rename from mvpa/cosmo_pca.m
rename to mvpa/cosmo_map_pca.m
index a7b2ff5e..bf2f178e 100644
--- a/mvpa/cosmo_pca.m
+++ b/mvpa/cosmo_map_pca.m
@@ -1,27 +1,27 @@
-function [ds, pca_params]=cosmo_pca(ds, varargin)
+function [ds, pca_params]=cosmo_map_pca(ds, varargin)
 % normalize dataset either by estimating or applying estimated parameters
 %
-% [ds, pca_params]=cosmo_pca(ds[, pca_params, pca_explained_count, 
-%                            pca_explained_ratio])
+% [ds, pca_params]=cosmo_map_pca(ds[, pca_params, pca_explained_count,
+%                                     pca_explained_ratio])
 %
 % Inputs
 %   ds            a dataset struct with field .samples of size PxQ, or a
 %                 numeric array of that size
-%   pca_params    previously estimated pca parameters using the 
-%                 'pca_params' output result from a previous call to this 
+%   pca_params    previously estimated pca parameters using the
+%                 'pca_params' output result from a previous call to this
 %                 function
-%   pca_explained_count    retain only the first 'pca_explained_count' 
+%   pca_explained_count    retain only the first 'pca_explained_count'
 %                          components
-%   pca_explained_ratio    retain the first components that explain 
+%   pca_explained_ratio    retain the first components that explain
 %                 'pca_explained_ratio' percent of the variance (value
 %                 between 0 and 1, where 1 retains all components)
 %
 % Output
 %   ds            a dataset struct similar to ds, but with .samples data
 %                 transformed using pca.
-%   params        estimated parameters for pca. These can be re-used for a 
-%                 second pca step of an independent dataset. For example, 
-%                 parameters can be estimated from a training dataset and 
+%   params        estimated parameters for pca. These can be re-used for a
+%                 second pca step of an independent dataset. For example,
+%                 parameters can be estimated from a training dataset and
 %                 then applied to a testing dataset
 %
 % #   For CoSMoMVPA's copyright information and license terms,   #
@@ -32,7 +32,7 @@
 apply_params = isfield(opt,'pca_params');
 pca_explained_count = isfield(opt,'pca_explained_count');
 pca_explained_ratio = isfield(opt,'pca_explained_ratio');
-    
+
 %they are mutually exclusive
 if sum([apply_params,pca_explained_count,pca_explained_ratio])>1
     error(['apply_params, pca_explained_count, pca_explained_ratio '...
@@ -84,7 +84,7 @@
         elseif pca_explained_ratio>1
             error('pca_explained_ratio should not be greater than 1');
         end
-        %retain the first components that explain the amount of variance 
+        %retain the first components that explain the amount of variance
         pca_params.pca_explained_ratio=pca_explained_ratio;
         retain=cumsum(explained)<=pca_explained_ratio*100;
     else