diff --git a/README.md b/README.md
index 23ca757..5a03be9 100644
--- a/README.md
+++ b/README.md
@@ -34,6 +34,8 @@ git clone https://github.com/arnodelorme/roiconnect.git
 ```
 That's it! If you want to run the plugin, please start [EEGLAB](https://github.com/sccn/eeglab#to-use-eeglab) first. You may need to add EEGLAB to the [MATLAB path](https://de.mathworks.com/help/matlab/ref/addpath.html).  
 
+📌 `test_pipes/` includes some test pipelines which can be used to get started.
+
 # Key features
 The features of the toolbox are implemented in the following three main functions: `pop_roi_activity`, `pop_roi_connect` and `pop_roi_connectplot`.
 
@@ -66,12 +68,12 @@ The function computes all FC metrics in a frequency-resolved way, i.e., the outp
 You can visualize power and FC in different modes by calling `pop_roi_connectplot`. Below, we show results of a single subject from the real data example in [[1]](#1). You can find the MATLAB code and corresponding analyses [here](https://github.com/fpellegrini/MotorImag). The plots show power or FC in left motor imagery condition. Due to the nature of the task, we show results in the 8 to 13 Hz frequency band but you are free to choose any frequency or frequency band you want. 
 
 :pushpin: If any of the images are too small for you, simply click on them, they will open in full size in another tab.<br>
-:round_pushpin: Plotting is particularly optimized for PSD, MIM/MIC and GC/TRGC. The matrix plots are only available for the Desikan-Killiany atlas (68 ROIs). We are currently working on a generalized solution for all atlases. 
+:round_pushpin: Plotting is particularly optimized for PSD, MIM/MIC and GC/TRGC. 
 
 ### Power as a region-wise bar plot
 If you wish to visualize power as a barplot only, please make sure to explicitely turn `plotcortex` off because it is turned on by default. 
 ```matlab
-EEG = pop_roi_connectplot(EEG, 'measure', 'roipsd', 'plotcortex', 'off', 'plotbarplot', on, 'freqrange', [8 13]) % alpha band;
+EEG = pop_roi_connectplot(EEG, 'measure', 'roipsd', 'plotcortex', 'off', 'plotbarplot', 'on', 'freqrange', [8 13]) % alpha band;
 ```
 <p float="middle">
   <img src="https://github.com/Hiyeri/roiconnect/blob/master/resources/power_barplot_left.jpg?raw=true" width="400"/>     
@@ -93,7 +95,7 @@ Again, if you do not wish to see the cortex plot, you should explicitely turn `p
 EEG = pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'freqrange', [8 13]);
 ```
 <p float="middle">
-  <img src="https://github.com/Hiyeri/roiconnect/blob/master/resources/FC_MIM_matrix_left.jpg?raw=true" width="400"/>     
+  <img src="https://github.com/Hiyeri/roiconnect/blob/master/resources/FC_MIM_matrix.png?raw=true" width="400"/>     
   &nbsp; &nbsp;
 </p>
 
@@ -103,17 +105,17 @@ pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'o
 ```
 
 <p float="middle">
-  <img src="https://github.com/Hiyeri/roiconnect/blob/master/resources/FC_MIM_matrix_groupedhems_left.jpg?raw=true" width="400"/>     
+  <img src="https://github.com/Hiyeri/roiconnect/blob/master/resources/FC_MIM_matrix_groupedhems.png?raw=true" width="400"/>     
   &nbsp; &nbsp;
 </p>
 
 You can additionally filter by hemispheres and regions belonging to specific brain lobes. As an example, let us see how FC of the left hemisphere looks like.
 
 ```matlab
-pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'freqrange', [8 13], 'hemisphere', 'left') % left hemisphere, left motor imagery;
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'freqrange', [8 13], 'hemisphere', 'left');
 ```
 <p float="middle">
-  <img src="https://github.com/Hiyeri/roiconnect/blob/master/resources/FC_MIM_matrix_lefthem_left.jpg?raw=true" width="400"/>     
+  <img src="https://github.com/Hiyeri/roiconnect/blob/master/resources/FC_MIM_matrix_lefthem.png?raw=true" width="400"/>     
   &nbsp; &nbsp;
 </p>
 
diff --git a/pop_roi_connectplot.m b/pop_roi_connectplot.m
index 109b664..7bf7a91 100644
--- a/pop_roi_connectplot.m
+++ b/pop_roi_connectplot.m
@@ -416,13 +416,14 @@
 
         % plot on matrix
         if strcmpi(g.plotmatrix, 'on') && ~isempty(matrix)
-            matrix = matrix.*seedMask; 
-            try
-                roi_plotcoloredlobes(EEG, matrix, titleStr, g.measure, g.hemisphere, g.grouphemispheres, g.region);
-            catch
-               warning('Functionalities only available for the Desikan-Killiany atlas (68 ROIs).')
-               figure; imagesc(matrix);
-            end
+            matrix = matrix.*seedMask;
+            roi_plotcoloredlobes(EEG, matrix, titleStr, g.measure, g.hemisphere, g.grouphemispheres, g.region);
+%             try
+%                 roi_plotcoloredlobes(EEG, matrix, titleStr, g.measure, g.hemisphere, g.grouphemispheres, g.region);
+%             catch
+%                warning('Functionalities only available for the Desikan-Killiany atlas (68 ROIs).')
+%                figure; imagesc(matrix);
+%             end
         end
 
         % plot on cortical surface
@@ -440,6 +441,8 @@
             end
             h = textsc(cortexTitle, 'title');
             set(h, 'fontsize', 20);
+        elseif cortexFlag == -1
+            warning('EEG.roi.cortex does not contain the field "Faces" required to plot surface topographies.')
         end
 
         % plot 3D
@@ -477,15 +480,24 @@
     end
 end
 
-function [colors, color_idxx, roi_idxx, labels_dk_cell_idx, roi_loc] = get_colored_labels(EEG)
-    % retrieve labels from atlas
+function labels = get_labels(EEG)
+% retrieve labels from atlas
     labels = strings(1,length(EEG.roi.atlas.Scouts));
     for i = 1:length(labels)
         scout = struct2cell(EEG.roi.atlas.Scouts(i));
         labels(i) = char(scout(1));
     end
     labels = cellstr(labels);
-    
+end
+
+function new_labels = replace_underscores(labels)
+    % remove underscores in label names to avoid bug
+    new_labels = strrep(labels, '_', ' ');
+end
+
+function [colors, color_idxx, roi_idxx, labels_sorted, roi_loc] = get_colored_labels(EEG)
+    labels = get_labels(EEG);
+
     colors = {[0,0,0]/255, [163, 107, 64]/255, [171, 163, 71]/255, [217, 37, 88]/255, [113, 15, 82]/255,[35, 103, 81]/255,[2, 45, 126]/255,};
     % assign labels to colors
     roi_loc ={'LT';'RT';'LL';'RL';'LF';'RF';'LO';'RO';'LT';'RT';'LPF';'RPF';'LT';'RT';'LP';'RP';'LT';'RT';'LT';'RT';'LL';'RL';'LO';'RO';'LPF';'RPF';'LO';'RO';'LPF';'RPF';'LT';'RT';'LC';'RC';'LT';'RT';'LF';'RF';'LPF';'RPF';'LF';'RF';'LO';'RO';'LC';'RC';'LL';'RL';'LC';'RC';'LP';'RP';'LL';'RL';'LF';'RF';'LF';'RF';'LP';'RP';'LT';'RT';'LP';'RP';'LT';'RT';'LT';'RT'};
@@ -502,21 +514,21 @@
     roi_loc = strrep(roi_loc, 'R', '');
     try
         [color_idxx,roi_idxx] = sort(str2double(roi_loc));
-        labels_dk_cell_idx = labels(roi_idxx);
+        labels_sorted = labels(roi_idxx);
     catch
         roi_idxx = 1:length(labels);
         color_idxx = mod(roi_idxx, length(colors))+1;
-        labels_dk_cell_idx = labels;
+        labels_sorted = labels;
     end
 end
 
 function roi_plotpower(EEG, source_roi_power_norm_dB, titleStr)
-    [colors, color_idxx, roi_idxx, labels_dk_cell_idx, ~] = get_colored_labels(EEG);
-    n_roi_labels = size(labels_dk_cell_idx, 2);
+    [colors, color_idxx, roi_idxx, labels_sorted, ~] = get_colored_labels(EEG);
+    n_roi_labels = size(labels_sorted, 2);
 
     barh(source_roi_power_norm_dB(roi_idxx));
     set(gca, 'YDir', 'reverse');
-    set(gca,'ytick',[1:n_roi_labels],'yticklabel',labels_dk_cell_idx(1:end), 'fontweight','bold','fontsize', 9, 'TickLength',[0.015, 0.02], 'LineWidth',0.7);
+    set(gca,'ytick',[1:n_roi_labels],'yticklabel',labels_sorted(1:end), 'fontweight','bold','fontsize', 9, 'TickLength',[0.015, 0.02], 'LineWidth',0.7);
     h = title([ 'ROI source power' ' (' titleStr ')' ]);
     set(h, 'fontsize', 16);
     ylabel('power [dB]')
@@ -542,7 +554,7 @@ function roi_plotcoloredlobes( EEG, matrix, titleStr, measure, hemisphere, group
         error('Region plotting is only supported for the Desikan-Killiany atlas.');
     end
     
-    % plot matrix with colored labels sorted by region according to the Desikan-Killiany atlas    
+    % plot matrix with colored labels    
     load cm18
     switch lower(measure)
         case {'mim', 'mic', 'coh'}
@@ -550,35 +562,54 @@ function roi_plotcoloredlobes( EEG, matrix, titleStr, measure, hemisphere, group
         otherwise
             cmap = cm18;
     end
-    [colors, color_idxx, roi_idxx, labels_dk_cell_idx, roi_loc] = get_colored_labels(EEG);
-    
     clim_min = min(matrix, [], 'all');
     clim_max = max(matrix, [], 'all');
-    
-    % assign region input to an index
-    [GC, GR] = groupcounts(roi_loc);
-    switch lower(region)
-        case 'cingulate'
-            region_idx = 1;
-        case 'prefrontal'
-            region_idx = 2;
-        case 'frontal'
-            region_idx = 3;
-        case 'temporal'
-            region_idx = 4;
-        case 'parietal'
-            region_idx = 5;
-        case 'central'
-            region_idx = 6;
-        case 'occipital'
-            region_idx = 7;
-        otherwise
-            region_idx = 99;
+
+    % hemisphere parameters to determine which labels to use 
+    last_char = EEG.roi.atlas.Scouts(1).Label(end); 
+    if strcmpi(hemisphere, 'left')
+        if strcmpi(last_char, 'R')
+            hem_idx = {2 2 2};  % use labels 2:2:end (first two values), only use 1/2 of the labels (3rd value)
+        else 
+            hem_idx = {1 2 2};  % use labels 1:2:end (first two values), only use 1/2 of the labels (3rd value)
+        end
+    elseif strcmpi(hemisphere, 'right')
+        if strcmpi(last_char, 'L')
+            hem_idx = {1 2 2};  
+        else
+            hem_idx = {2 2 2};  
+        end
+    else
+        hem_idx = {1 1 1};
     end
     
     % sort matrix according to color scheme
     % reduce matrix to only keep components corresponding to selected region
     if isDKatlas == 1
+        [colors, color_idxx, roi_idxx, labels_sorted, roi_loc] = get_colored_labels(EEG);
+        labels = labels_sorted;
+
+        % assign region input to an index
+        [GC, ~] = groupcounts(roi_loc);
+        switch lower(region)
+            case 'cingulate'
+                region_idx = 1;
+            case 'prefrontal'
+                region_idx = 2;
+            case 'frontal'
+                region_idx = 3;
+            case 'temporal'
+                region_idx = 4;
+            case 'parietal'
+                region_idx = 5;
+            case 'central'
+                region_idx = 6;
+            case 'occipital'
+                region_idx = 7;
+            otherwise
+                region_idx = 99;
+        end
+
         matrix = matrix(roi_idxx, roi_idxx); 
         if not(region_idx == 99)
             if region_idx == 1
@@ -588,44 +619,40 @@ function roi_plotcoloredlobes( EEG, matrix, titleStr, measure, hemisphere, group
             end
             end_idx = start_idx + GC(region_idx) - 1;
             matrix = matrix(start_idx:end_idx, start_idx:end_idx);  
-            labels_dk_cell_idx = labels_dk_cell_idx(start_idx:end_idx);
+            labels = labels(start_idx:end_idx);
             color_idxx = color_idxx(start_idx:end_idx);
         end
         n_roi_labels = size(matrix, 1);
-    end
-
-    % hemisphere parameters to determine which labels to use 
-    if strcmpi(hemisphere, 'left')
-        hem_idx = {1 2 2};  % use labels 1:2:end (first two values), only use 1/2 of the labels (3rd value)
-    elseif strcmpi(hemisphere, 'right')
-        hem_idx = {2 2 2};  % use labels 2:2:end (first two values), only use 1/2 of the labels (3rd value)
     else
-        hem_idx = {1 1 1};  % use labels 1:1:end (first two values, all labels), use 1/1 of the labels (3rd value, all labels)
+        labels = get_labels(EEG);
     end
 
+    % remove underscores in labels to avoid plotting bug
+    labels = replace_underscores(labels);
+
     % create dummy plot and add custom legend
     f = figure();
     %f.WindowState = 'maximized';
     hold on
     n_dummy_labels = 7;
     x = 1:10;
-    for k=1:n_dummy_labels
-        plot(x, x*k, '-', 'LineWidth', 9, 'Color', colors{k});
-    end
 
     % labels on dummy plot for positioning
     xlim([0 n_roi_labels])
     ylim([0 n_roi_labels])
-    set(gca,'xtick',[1:n_roi_labels],'xticklabel',labels_dk_cell_idx(hem_idx{1}:hem_idx{2}:n_roi_labels));%, 'TickLabelInterpreter','none');
+    set(gca,'xtick',1:n_roi_labels,'xticklabel',labels(hem_idx{1}:hem_idx{2}:n_roi_labels));%, 'TickLabelInterpreter','none');
     ax = gca;
-    for i=hem_idx{1}:hem_idx{2}:n_roi_labels   
-        ax.XTickLabel{ceil(i/hem_idx{3})} = sprintf('\\color[rgb]{%f,%f,%f}%s', colors{color_idxx(i)}, ax.XTickLabel{ceil(i/2)});
-    end
-    xtickangle(90)
-    pos = get(gca, 'Position');
     if isDKatlas == 1
+        for k=1:n_dummy_labels
+            plot(x, x*k, '-', 'LineWidth', 9, 'Color', colors{k});
+        end
+        for i=hem_idx{1}:hem_idx{2}:n_roi_labels   
+            ax.XTickLabel{ceil(i/hem_idx{3})} = sprintf('\\color[rgb]{%f,%f,%f}%s', colors{color_idxx(i)}, ax.XTickLabel{ceil(i/2)});
+        end
         legend('Cingulate', 'Prefrontal', 'Frontal', 'Temporal', 'Parietal', 'Central', 'Occipital', 'Location', 'southeastoutside'); % modify legend position
     end
+    xtickangle(90)
+    pos = get(gca, 'Position');
     set(gca, 'Position', pos, 'DataAspectRatio',[1 1 1], 'visible', 'off')
     axes('pos', [pos(1) pos(2) pos(3) pos(4)]) % plot matrix over the dummy plot and keep the legend
     
@@ -640,14 +667,20 @@ function roi_plotcoloredlobes( EEG, matrix, titleStr, measure, hemisphere, group
         matrix = horzcat(mat_left_col, mat_right_col); % sort columns
         
         % sort labels
-        lc = {labels_dk_cell_idx; transpose(color_idxx)};
-        for i = 1:length(lc)
-            left = lc{i}(1:2:end);
-            right = lc{i}(2:2:end);
-            lc{i} = [left right];
+        try % if color can be assigned
+            lc = {labels; transpose(color_idxx)};
+            for i = 1:length(lc)
+                left = lc{i}(1:2:end);
+                right = lc{i}(2:2:end);
+                lc{i} = [left right];
+            end
+            labels = lc{1};
+            color_idxx = transpose(lc{2});
+        catch
+            left = labels(1:2:end);
+            right = labels(2:2:end);
+            labels = [left right];
         end
-        labels_dk_cell_idx = lc{1};
-        color_idxx = transpose(lc{2});
     end
 
     % reduce matrix to keep only one hemisphere
@@ -677,16 +710,16 @@ function roi_plotcoloredlobes( EEG, matrix, titleStr, measure, hemisphere, group
     set(gca, 'Position', pos, 'DataAspectRatio',[1 1 1], 'visible', 'on')
 
     % add colored labels with display option
+    ax = gca;
+    set(gca,'xtick',1:n_roi_labels,'xticklabel',labels(hem_idx{1}:hem_idx{2}:n_roi_labels));
     if isDKatlas == 1
-        set(gca,'ytick',[1:n_roi_labels],'yticklabel',labels_dk_cell_idx(hem_idx{1}:hem_idx{2}:n_roi_labels), 'fontweight','bold', 'fontsize', 9, 'TickLength',[0.015, 0.02], 'LineWidth',0.75);
+        set(gca,'ytick',1:n_roi_labels,'yticklabel',labels(hem_idx{1}:hem_idx{2}:n_roi_labels), 'fontsize', 9, 'TickLength',[0.015, 0.02], 'LineWidth',0.75);
+        for i=hem_idx{1}:hem_idx{2}:n_roi_labels  
+            ax.XTickLabel{ceil(i/hem_idx{3})} = sprintf('\\color[rgb]{%f,%f,%f}%s', colors{color_idxx(i)}, ax.XTickLabel{ceil(i/hem_idx{3})});
+            ax.YTickLabel{ceil(i/hem_idx{3})} = sprintf('\\color[rgb]{%f,%f,%f}%s', colors{color_idxx(i)}, ax.YTickLabel{ceil(i/hem_idx{3})});
+        end
     else
-        set(gca,'ytick',[1:n_roi_labels],'yticklabel',labels_dk_cell_idx(hem_idx{1}:hem_idx{2}:n_roi_labels), 'fontsize', 7, 'TickLength',[0.015, 0.02], 'LineWidth',0.75);
-    end
-        set(gca,'xtick',[1:n_roi_labels],'xticklabel',labels_dk_cell_idx(hem_idx{1}:hem_idx{2}:n_roi_labels));
-    ax = gca;
-    for i=hem_idx{1}:hem_idx{2}:n_roi_labels  
-        ax.XTickLabel{ceil(i/hem_idx{3})} = sprintf('\\color[rgb]{%f,%f,%f}%s', colors{color_idxx(i)}, ax.XTickLabel{ceil(i/hem_idx{3})});
-        ax.YTickLabel{ceil(i/hem_idx{3})} = sprintf('\\color[rgb]{%f,%f,%f}%s', colors{color_idxx(i)}, ax.YTickLabel{ceil(i/hem_idx{3})});
+        set(gca,'ytick',1:n_roi_labels,'yticklabel',labels(hem_idx{1}:hem_idx{2}:n_roi_labels), 'fontsize', 7, 'TickLength',[0.015, 0.02], 'LineWidth',0.75);
     end
     h = title([ 'ROI to ROI ' upper(measure) ' (' titleStr ')' ]);
     set(h, 'fontsize', 16);
@@ -696,8 +729,8 @@ function roi_plotcoloredlobes( EEG, matrix, titleStr, measure, hemisphere, group
 function roi_largeplot(EEG, mim, trgc, roipsd, titleStr)
     % plot MIM, TRGC and power (barplot) in a single large figure
     load cm18
-    [colors, color_idxx, roi_idxx, labels_dk_cell_idx, ~] = get_colored_labels(EEG);
-    n_roi_labels = size(labels_dk_cell_idx, 2);
+    [colors, color_idxx, roi_idxx, labels_sorted, ~] = get_colored_labels(EEG);
+    n_roi_labels = size(labels_sorted, 2);
     
     f = figure();
     f.WindowState = 'maximized';
@@ -713,8 +746,8 @@ function roi_largeplot(EEG, mim, trgc, roipsd, titleStr)
         img_sorted = img(roi_idxx, roi_idxx);
         imagesc(img_sorted)
 
-        set(gca,'ytick',[1:n_roi_labels],'yticklabel',labels_dk_cell_idx(1:end), 'fontsize', 5, 'TickLength',[0.015, 0.02], 'LineWidth',0.75);
-        set(gca,'xtick',[1:n_roi_labels],'xticklabel',labels_dk_cell_idx(1:end));
+        set(gca,'ytick',[1:n_roi_labels],'yticklabel',labels_sorted(1:end), 'fontsize', 5, 'TickLength',[0.015, 0.02], 'LineWidth',0.75);
+        set(gca,'xtick',[1:n_roi_labels],'xticklabel',labels_sorted(1:end));
         h = title([ 'ROI to ROI ' fc_names{k} ' (' titleStr ')' ]);
         set(h, 'fontsize', 16);
         hcb = colorbar;
@@ -735,7 +768,7 @@ function roi_largeplot(EEG, mim, trgc, roipsd, titleStr)
     barh(roipsd(roi_idxx));
 
     set(gca, 'YDir', 'reverse');
-    set(gca,'ytick',[1:n_roi_labels],'yticklabel',labels_dk_cell_idx(1:end), 'fontweight','bold','fontsize', 9, 'TickLength',[0.015, 0.02], 'LineWidth',0.7);
+    set(gca,'ytick',[1:n_roi_labels],'yticklabel',labels_sorted(1:end), 'fontsize', 9, 'TickLength',[0.015, 0.02], 'LineWidth',0.7);
     h = title([ 'ROI source power' ' (' titleStr ')' ]);
     set(h, 'fontsize', 16);
     ylabel('power [dB]')
diff --git a/resources/FC_MIM_matrix.png b/resources/FC_MIM_matrix.png
new file mode 100644
index 0000000..9c4495c
Binary files /dev/null and b/resources/FC_MIM_matrix.png differ
diff --git a/resources/FC_MIM_matrix_groupedhems.png b/resources/FC_MIM_matrix_groupedhems.png
new file mode 100644
index 0000000..02b233c
Binary files /dev/null and b/resources/FC_MIM_matrix_groupedhems.png differ
diff --git a/resources/FC_MIM_matrix_left.png b/resources/FC_MIM_matrix_left.png
new file mode 100644
index 0000000..4ea9399
Binary files /dev/null and b/resources/FC_MIM_matrix_left.png differ
diff --git a/pipeline_connectivity.m b/test_pipes/pipeline_connectivity.m
similarity index 96%
rename from pipeline_connectivity.m
rename to test_pipes/pipeline_connectivity.m
index 2fe5d0e..a4b5159 100644
--- a/pipeline_connectivity.m
+++ b/test_pipes/pipeline_connectivity.m
@@ -46,6 +46,4 @@
     tic
     EEG = pop_roi_connect(EEG, 'methods', measures(iMeasure));
     t(iMeasure) = toc;
-end
-
-pop_roi_connectplot(EEG, 'measure', 'MIM', 'plotmatrix', 'on', 'plotcortex', 'on');
\ No newline at end of file
+end
\ No newline at end of file
diff --git a/test_pipes/test_brainplots_dkatlas.m b/test_pipes/test_brainplots_dkatlas.m
new file mode 100644
index 0000000..247ddc3
--- /dev/null
+++ b/test_pipes/test_brainplots_dkatlas.m
@@ -0,0 +1,33 @@
+% Test cortical surface topographies with different parameters. Here, the Desikan-Killiany atlas with 68 ROIs is used as the source model.
+%% Run pipeline
+clear
+eeglab
+
+eeglabp = fileparts(which('eeglab.m'));
+EEG = pop_loadset('filename','eeglab_data_epochs_ica.set','filepath',fullfile(eeglabp, 'sample_data/'));
+EEG = pop_resample( EEG, 100);
+EEG = pop_epoch( EEG, { }, [-0.5 1.5], 'newname', 'EEG Data epochs epochs', 'epochinfo', 'yes');
+EEG = pop_select( EEG, 'trial',1:30);
+[ALLEEG, EEG, CURRENTSET] = eeg_store(ALLEEG, EEG);
+eeglab redraw;
+
+EEG = pop_dipfit_settings( EEG, 'hdmfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_vol.mat'), ...
+    'coordformat','MNI','mrifile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_mri.mat'),...
+    'chanfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','elec', 'standard_1005.elc'),...
+    'coord_transform',[0.83215 -15.6287 2.4114 0.081214 0.00093739 -1.5732 1.1742 1.0601 1.1485] ,'chansel',[1:32] );
+
+EEG = pop_leadfield(EEG, 'sourcemodel',fullfile(eeglabp,'functions','supportfiles','head_modelColin27_5003_Standard-10-5-Cap339.mat'), ...
+    'sourcemodel2mni',[0 -24 -45 0 0 -1.5708 1000 1000 1000] ,'downsample',1);
+
+EEG = pop_roi_activity(EEG, 'leadfield',EEG.dipfit.sourcemodel,'model','LCMV','modelparams',{0.05},'atlas','LORETA-Talairach-BAs','nPCA',3);
+EEG = pop_roi_connect(EEG, 'methods', {'MIM'});
+
+%% Plot brain plot with different parameters
+% brain plot without any filters
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'on');  
+
+% frequency band specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'on', 'freqrange', [8 13]);  
+
+% seed voxel specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'on', 'plotcortexseedregion', 49); 
\ No newline at end of file
diff --git a/test_pipes/test_brainplots_loretaatlas.m b/test_pipes/test_brainplots_loretaatlas.m
new file mode 100644
index 0000000..7c9a490
--- /dev/null
+++ b/test_pipes/test_brainplots_loretaatlas.m
@@ -0,0 +1,33 @@
+% Test cortical surface topographies with different parameters. Here, the LORETA-Talairach-BAs atlas with 90 ROIs is used as the source model.
+%% Run pipeline
+clear
+eeglab
+
+eeglabp = fileparts(which('eeglab.m'));
+EEG = pop_loadset('filename','eeglab_data_epochs_ica.set','filepath',fullfile(eeglabp, 'sample_data/'));
+EEG = pop_resample( EEG, 100);
+EEG = pop_epoch( EEG, { }, [-0.5 1.5], 'newname', 'EEG Data epochs epochs', 'epochinfo', 'yes');
+EEG = pop_select( EEG, 'trial',1:30);
+[ALLEEG, EEG, CURRENTSET] = eeg_store(ALLEEG, EEG);
+eeglab redraw;
+
+EEG = pop_dipfit_settings( EEG, 'hdmfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_vol.mat'), ...
+    'coordformat','MNI','mrifile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_mri.mat'),...
+    'chanfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','elec', 'standard_1005.elc'),...
+    'coord_transform',[0.83215 -15.6287 2.4114 0.081214 0.00093739 -1.5732 1.1742 1.0601 1.1485] ,'chansel',[1:32] );
+
+EEG = pop_leadfield(EEG, 'sourcemodel',fullfile(eeglabp,'plugins','dipfit','LORETA-Talairach-BAs.mat'), ...
+    'sourcemodel2mni',[0 -24 -45 0 0 -1.5708 1000 1000 1000] ,'downsample',1);
+
+EEG = pop_roi_activity(EEG, 'leadfield',EEG.dipfit.sourcemodel,'model','LCMV','modelparams',{0.05},'atlas','LORETA-Talairach-BAs','nPCA',3);
+EEG = pop_roi_connect(EEG, 'methods', {'MIM'});
+
+%% Plot brain plot with different parameters
+% brain plot without any filters
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'on');  
+
+% frequency band specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'on', 'freqrange', [8 13]);  
+
+% seed voxel specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'on', 'plotcortexseedregion', 49); 
\ No newline at end of file
diff --git a/test_pipes/test_flex_epochlength.m b/test_pipes/test_flex_epochlength.m
new file mode 100644
index 0000000..ca06458
--- /dev/null
+++ b/test_pipes/test_flex_epochlength.m
@@ -0,0 +1,31 @@
+% Test pipeline with an epoch length other than 2 seconds (test with 1 second epoch length).
+%% Run pipeline
+clear
+eeglab
+
+eeglabp = fileparts(which('eeglab.m'));
+EEG = pop_loadset('filename','eeglab_data_epochs_ica.set','filepath',fullfile(eeglabp, 'sample_data/'));
+EEG = pop_resample( EEG, 100);
+EEG = pop_epoch( EEG, { }, [-0.5 0.5], 'newname', 'EEG Data epochs epochs', 'epochinfo', 'yes');
+EEG = pop_select( EEG, 'trial',1:30);
+[ALLEEG, EEG, CURRENTSET] = eeg_store(ALLEEG, EEG);
+eeglab redraw;
+
+EEG = pop_dipfit_settings( EEG, 'hdmfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_vol.mat'), ...
+    'coordformat','MNI','mrifile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_mri.mat'),...
+    'chanfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','elec', 'standard_1005.elc'),...
+    'coord_transform',[0.83215 -15.6287 2.4114 0.081214 0.00093739 -1.5732 1.1742 1.0601 1.1485] ,'chansel',[1:32] );
+
+EEG = pop_leadfield(EEG, 'sourcemodel',fullfile(eeglabp,'functions','supportfiles','head_modelColin27_5003_Standard-10-5-Cap339.mat'), ...
+    'sourcemodel2mni',[0 -24 -45 0 0 -1.5708 1000 1000 1000] ,'downsample',1);
+
+EEG = pop_roi_activity(EEG, 'leadfield',EEG.dipfit.sourcemodel,'model','LCMV','modelparams',{0.05},'atlas','LORETA-Talairach-BAs','nPCA',1);
+
+measures = { 'MIM' 'wPLI' };
+for iMeasure = 1:length(measures)
+    tic
+    EEG = pop_roi_connect(EEG, 'methods', measures(iMeasure));
+    t(iMeasure) = toc;
+end
+
+
diff --git a/test_pipes/test_largebarplot_dkatlas.m b/test_pipes/test_largebarplot_dkatlas.m
new file mode 100644
index 0000000..a9b177f
--- /dev/null
+++ b/test_pipes/test_largebarplot_dkatlas.m
@@ -0,0 +1,27 @@
+% Test region-to-region power bar plot. Here, the Desikan-Killiany atlas with 68 ROIs is used as the source model.
+%% Run pipeline
+clear
+eeglab
+
+eeglabp = fileparts(which('eeglab.m'));
+EEG = pop_loadset('filename','eeglab_data_epochs_ica.set','filepath',fullfile(eeglabp, 'sample_data/'));
+EEG = pop_resample( EEG, 100);
+EEG = pop_epoch( EEG, { }, [-0.5 1.5], 'newname', 'EEG Data epochs epochs', 'epochinfo', 'yes');
+EEG = pop_select( EEG, 'trial',1:30);
+[ALLEEG, EEG, CURRENTSET] = eeg_store(ALLEEG, EEG);
+eeglab redraw;
+
+EEG = pop_dipfit_settings( EEG, 'hdmfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_vol.mat'), ...
+    'coordformat','MNI','mrifile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_mri.mat'),...
+    'chanfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','elec', 'standard_1005.elc'),...
+    'coord_transform',[0.83215 -15.6287 2.4114 0.081214 0.00093739 -1.5732 1.1742 1.0601 1.1485] ,'chansel',[1:32] );
+
+EEG = pop_leadfield(EEG, 'sourcemodel',fullfile(eeglabp,'functions','supportfiles','head_modelColin27_5003_Standard-10-5-Cap339.mat'), ...
+    'sourcemodel2mni',[0 -24 -45 0 0 -1.5708 1000 1000 1000] ,'downsample',1);
+
+EEG = pop_roi_activity(EEG, 'leadfield',EEG.dipfit.sourcemodel,'model','LCMV','modelparams',{0.05},'atlas','LORETA-Talairach-BAs','nPCA',3);
+EEG = pop_roi_connect(EEG, 'methods', {'MIM', 'TRGC'});
+
+%% Plot barplot
+% plot barplot with specified frequency band
+EEG = pop_roi_connectplot(EEG, 'measure', 'roipsd', 'plotcortex', 'off', 'plotbarplot', 'on', 'freqrange', [4 8]);
\ No newline at end of file
diff --git a/test_pipes/test_matrixplots_brainregions.m b/test_pipes/test_matrixplots_brainregions.m
new file mode 100644
index 0000000..39b89a2
--- /dev/null
+++ b/test_pipes/test_matrixplots_brainregions.m
@@ -0,0 +1,45 @@
+% Test region-to-region FC matrices (MIM) with different parameters. Here, the grouped LORETA-Talairach-BAs ('Brain-Regions') atlas with 34 ROIs is used as the source model.
+%% Run pipeline
+clear
+eeglab
+
+eeglabp = fileparts(which('eeglab.m'));
+EEG = pop_loadset('filename','eeglab_data_epochs_ica.set','filepath',fullfile(eeglabp, 'sample_data/'));
+EEG = pop_resample( EEG, 100);
+EEG = pop_epoch( EEG, { }, [-0.5 1.5], 'newname', 'EEG Data epochs epochs', 'epochinfo', 'yes');
+EEG = pop_select( EEG, 'trial',1:30);
+[ALLEEG, EEG, CURRENTSET] = eeg_store(ALLEEG, EEG);
+eeglab redraw;
+
+EEG = pop_dipfit_settings( EEG, 'hdmfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_vol.mat'), ...
+    'coordformat','MNI','mrifile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_mri.mat'),...
+    'chanfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','elec', 'standard_1005.elc'),...
+    'coord_transform',[0.83215 -15.6287 2.4114 0.081214 0.00093739 -1.5732 1.1742 1.0601 1.1485] ,'chansel',[1:32] );
+
+EEG = pop_leadfield(EEG, 'sourcemodel',fullfile(eeglabp,'plugins','dipfit','LORETA-Talairach-BAs.mat'), ...
+    'sourcemodel2mni',[0 -24 -45 0 0 -1.5708 1000 1000 1000] ,'downsample',1);
+
+EEG = pop_roi_activity(EEG, 'leadfield',EEG.dipfit.sourcemodel,'model','LCMV','modelparams',{0.05},'atlas','Brain-Regions','nPCA',3);
+EEG = pop_roi_connect(EEG, 'methods', {'MIM'});
+
+%% Plot matrix with different parameters
+% matrix without any filters
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on');
+
+% group by hemispheres
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'grouphemispheres', 'on');
+
+% frequency band specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'freqrange', [4 8]');
+
+% hemisphere specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'hemisphere', 'right'); 
+
+% cortical region specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'region', 'occipital');
+
+
+
+
+
+
diff --git a/test_pipes/test_matrixplots_dkatlas.m b/test_pipes/test_matrixplots_dkatlas.m
new file mode 100644
index 0000000..c9ae221
--- /dev/null
+++ b/test_pipes/test_matrixplots_dkatlas.m
@@ -0,0 +1,45 @@
+% Test region-to-region FC matrices (MIM) with different parameters. Here, the Desikan-Killiany atlas with 68 ROIs is used as the source model.
+%% Run pipeline
+clear
+eeglab
+
+eeglabp = fileparts(which('eeglab.m'));
+EEG = pop_loadset('filename','eeglab_data_epochs_ica.set','filepath',fullfile(eeglabp, 'sample_data/'));
+EEG = pop_resample( EEG, 100);
+EEG = pop_epoch( EEG, { }, [-0.5 1.5], 'newname', 'EEG Data epochs epochs', 'epochinfo', 'yes');
+EEG = pop_select( EEG, 'trial',1:30);
+[ALLEEG, EEG, CURRENTSET] = eeg_store(ALLEEG, EEG);
+eeglab redraw;
+
+EEG = pop_dipfit_settings( EEG, 'hdmfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_vol.mat'), ...
+    'coordformat','MNI','mrifile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_mri.mat'),...
+    'chanfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','elec', 'standard_1005.elc'),...
+    'coord_transform',[0.83215 -15.6287 2.4114 0.081214 0.00093739 -1.5732 1.1742 1.0601 1.1485] ,'chansel',[1:32] );
+
+EEG = pop_leadfield(EEG, 'sourcemodel',fullfile(eeglabp,'functions','supportfiles','head_modelColin27_5003_Standard-10-5-Cap339.mat'), ...
+    'sourcemodel2mni',[0 -24 -45 0 0 -1.5708 1000 1000 1000] ,'downsample',1);
+
+EEG = pop_roi_activity(EEG, 'leadfield',EEG.dipfit.sourcemodel,'model','LCMV','modelparams',{0.05},'atlas','LORETA-Talairach-BAs','nPCA',3);
+EEG = pop_roi_connect(EEG, 'methods', {'MIM'});
+
+%% Plot matrix with different parameters
+% matrix without any filters
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on');
+
+% group by hemispheres
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'grouphemispheres', 'on');
+
+% frequency band specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'freqrange', [4 8]');
+
+% hemisphere specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'hemisphere', 'right'); 
+
+% cortical region specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'region', 'occipital');
+
+
+
+
+
+
diff --git a/test_pipes/test_matrixplots_loretaatlas.m b/test_pipes/test_matrixplots_loretaatlas.m
new file mode 100644
index 0000000..9ab5d24
--- /dev/null
+++ b/test_pipes/test_matrixplots_loretaatlas.m
@@ -0,0 +1,45 @@
+% Test region-to-region FC matrices (MIM) with different parameters. Here, the LORETA-Talairach-BAs atlas with 90 ROIs is used as the source model.
+%% Run pipeline
+clear
+eeglab
+
+eeglabp = fileparts(which('eeglab.m'));
+EEG = pop_loadset('filename','eeglab_data_epochs_ica.set','filepath',fullfile(eeglabp, 'sample_data/'));
+EEG = pop_resample( EEG, 100);
+EEG = pop_epoch( EEG, { }, [-0.5 1.5], 'newname', 'EEG Data epochs epochs', 'epochinfo', 'yes');
+EEG = pop_select( EEG, 'trial',1:30);
+[ALLEEG, EEG, CURRENTSET] = eeg_store(ALLEEG, EEG);
+eeglab redraw;
+
+EEG = pop_dipfit_settings( EEG, 'hdmfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_vol.mat'), ...
+    'coordformat','MNI','mrifile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','standard_mri.mat'),...
+    'chanfile',fullfile(eeglabp, 'plugins','dipfit','standard_BEM','elec', 'standard_1005.elc'),...
+    'coord_transform',[0.83215 -15.6287 2.4114 0.081214 0.00093739 -1.5732 1.1742 1.0601 1.1485] ,'chansel',[1:32] );
+
+EEG = pop_leadfield(EEG, 'sourcemodel',fullfile(eeglabp,'plugins','dipfit','LORETA-Talairach-BAs.mat'), ...
+    'sourcemodel2mni',[0 -24 -45 0 0 -1.5708 1000 1000 1000] ,'downsample',1);
+
+EEG = pop_roi_activity(EEG, 'leadfield',EEG.dipfit.sourcemodel,'model','LCMV','modelparams',{0.05},'atlas','LORETA-Talairach-BAs','nPCA',3);
+EEG = pop_roi_connect(EEG, 'methods', {'MIM'});
+
+%% Plot matrix with different parameters
+% matrix without any filters
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on');
+
+% group by hemispheres
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'grouphemispheres', 'on');
+
+% frequency band specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'freqrange', [4 8]');
+
+% hemisphere specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'hemisphere', 'right'); 
+
+% cortical region specified
+pop_roi_connectplot(EEG, 'measure', 'mim', 'plotcortex', 'off', 'plotmatrix', 'on', 'region', 'occipital');
+
+
+
+
+
+