Replace ana02_behave.m

05_scripts/ana02_behave.m

@@ -8,8 +8,9 @@
 % Author: Julius Welzel
 
 % define paths
-PATHIN = [MAIN '04_Data\'];
+PATHIN = [MAIN '04_Data\ana11_behavioural\'];
 PATHIN_RTs = [MAIN '04_Data\ana04_erd\'];
+PATHIN_EMG = [path_data 'ana03_emg\'];
 
 PATHOUT= [MAIN '04_Data\ana11_behavioural\'];
 
@@ -17,12 +18,12 @@ if ~exist(PATHOUT)
   mkdir(PATHOUT);
 end
 
-list = dir(fullfile([PATHIN 'ana02_clean\*clean*.set']));
-SUBJ = extractBefore({list.name},'_');
-
-load([PATHOUT 'behavioural.mat']);
+load([PATHIN 'behavioural.mat']);
 load([PATHIN_RTs 'cfg.mat']);
 
+list = dir(fullfile([path_data 'ana02_clean\*clean*.set']));
+SUBJ = extractBefore({list.name},'_');
+
 %% Scatter Age vs. MoCa
 
 age = table2array(behavioural(:,3));
@@ -36,14 +37,14 @@ b = figure;
 [unique_groups, ~, group_idx] = unique(sex);
 pointsize = 150;
 scatter(age,MoCa, pointsize, group_idx,'s','filled');
-cmap = lbmap(20,'RedBlue');    %or build a custom color map
-colormap( cmap([4 19],:) );
+cmap = cbrewer('seq', 'Blues',6);    %or build a custom color map
+colormap( [cmap(5,:);0.5 0.5 0.5] );
 legend('female','male');
 ylim([23 30])
 ylabel 'MoCa score'
 xlim([50 85])
 xlabel 'Age'
-save_fig(gcf,PATHOUT,'scatter_moca_age','FontSize',25)
+save_fig(gcf,PATHOUT,'scatter_moca_age','fontsize',25,'figsize',[0 0 20 20])
 
 %% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 %
@@ -52,16 +53,25 @@ save_fig(gcf,PATHOUT,'scatter_moca_age','FontSize',25)
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 % extract trial relevant markers // 1 = Start, 0 = Stimulus start, 2 = trial end
-load ([PATHIN_RTs 'RTs.mat']);
-
-t = 1;
-e = 1;
+load ([PATHIN_RTs 'RTs_mue.mat']);
+load ([PATHIN_RTs 'cfg.mat']);
+load ([PATHIN_EMG 'emg_all.mat']);
+cfg.n_trials = 96;
+SUBJ = str2double(SUBJ);
 
 
 %% plot
-SUBJ = str2double(SUBJ);
 old = (SUBJ<80);
 young = (SUBJ>=80);
+g_idx = ones(1,(length(RT)));
+g_idx(old) = 0;
+
+
+blocks = cell(1,cfg.n_trials);
+blocks(cfg.blck_idx{1,1}) = {'EX1'};
+blocks(cfg.blck_idx{2,1}) = {'MI1'};
+blocks(cfg.blck_idx{3,1}) = {'MI2'};
+blocks(cfg.blck_idx{4,1}) = {'EX2'};
 
 
 for t = 1:length(RT)
@@ -82,16 +92,31 @@ for t = 1:length(RT)
     
 end
 
+RT_all = [ex1;mi1 ;mi2 ;ex2];
+
+%mean for each block
 ex1_o = mean(nanmean(ex1(:,old)));
 mi1_o = mean(nanmean(mi1(:,old)));
 mi2_o = mean(nanmean(mi2(:,old)));
-mi2_o = mean(nanmean(ex2(:,old)));
+ex2_o = mean(nanmean(ex2(:,old)));
 
 ex1_y = mean(nanmean(ex1(:,young)));
 mi1_y = mean(nanmean(mi1(:,young)));
 mi2_y = mean(nanmean(mi2(:,young)));
 ex2_y = mean(nanmean(ex2(:,young)));
 
+% ste for each block
+ex1_o_se = ste(nanmean(ex1(:,old)));
+mi1_o_se = ste(nanmean(mi1(:,old)));
+mi2_o_se = ste(nanmean(mi2(:,old)));
+ex2_o_se = ste(nanmean(ex2(:,old)));
+
+ex1_y_se = ste(nanmean(ex1(:,young)));
+mi1_y_se = ste(nanmean(mi1(:,young)));
+mi2_y_se = ste(nanmean(mi2(:,young)));
+ex2_y_se = ste(nanmean(ex2(:,young)));
+
+
 
 all_t_o = [nanmean(ex1(:,old),2);nanmean(mi1(:,old),2);nanmean(mi2(:,old),2);nanmean(ex2(:,old),2)];
 ste_t_o = [ste(ex1(:,old)'),ste(mi1(:,old)'),ste(mi2(:,old)'),ste(ex2(:,old)')];
@@ -101,9 +126,10 @@ err_b_o = [ste_t_o;-ste_t_o];
 all_t_y = [nanmean(ex1(:,young),2);nanmean(mi1(:,young),2);nanmean(mi2(:,young),2);nanmean(ex2(:,young),2)];
 ste_t_y = [ste(ex1(:,young)'),ste(mi1(:,young)'),ste(mi2(:,young)'),ste(ex2(:,young)')];
 err_b_y = [ste_t_y;-ste_t_y];
+
 x=(1:size(all_t_o,1));
 
-%%
+%% shaded errorbar all trials
 figure
 shadedErrorBar(x,all_t_y,ste_t_y','lineprops','-r')
 hold on
@@ -116,6 +142,111 @@ xlim([1 96]);
 vline([8,48,88],'-k')
 
 %set figure screensize and save
-save_fig(gcf,PATHOUT,'RTs','FontSize',20)
+save_fig(gcf,PATHOUT,'RTs','FontSize',25,'figsize',[0 0 35 20])
+
+%% shaded errorbar blocks
+bz = 2+1;
+b_o = 1:bz:cfg.num_block*bz;
+b_y = [1+1:bz:cfg.num_block*bz]+1;
+b_b = [1+2:bz:cfg.num_block*bz-1]+2;
+b = 1:cfg.num_block
+
+blck_time_y = [ex1_y mi1_y mi2_y ex2_y];
+blck_time_o = [ex1_o mi1_o mi2_o ex2_o];
+
+blck_time_y_se = [ex1_y_se mi1_y_se mi2_y_se ex2_y_se];
+blck_time_o_se = [ex1_o_se mi1_o_se mi2_o_se ex2_o_se];
+
+figure
+t_o = shadedErrorBar(b,blck_time_y,blck_time_y_se,'lineprops',{'-','Color',c_young,'LineWidth',2})
+hold on
+errorbar(blck_time_y,blck_time_y_se,'-','Color',c_young,'LineWidth',2)
+hold on
+t_y = shadedErrorBar(b,blck_time_o,blck_time_o_se,'lineprops',{'-','Color',c_old,'LineWidth',2})
+hold on
+errorbar(blck_time_o,blck_time_o_se,'-','Color',c_old,'LineWidth',2)
+
+
+t_o.edge(1).LineWidth = 2;
+t_o.edge(2).LineWidth = 2;
+t_y.edge(1).LineWidth = 2;
+t_y.edge(2).LineWidth = 2;
+
+xlim([0.8 4.2])
+xticks (b);
+xticklabels({'EX 1','MI 1','MI 2','EX 2'})
+ylabel('[ms]');
+xlabel('Blocks');
+
+
+%set figure screensize and save
+save_fig(gcf,PATHOUT,'RTs_blck.png','fontsize',25,'figsize',[0 0 30 20])
+
+
+%% Boxplots
+bz = 2+1;
+b_o = 1:bz:cfg.num_block*bz;
+b_y = [1+1:bz:cfg.num_block*bz]+1;
+b_b = [1+2:bz:cfg.num_block*bz]+2;
+
+n_old = sum(old);
+blck_lab(1:n_old) = {'EX1'};
+blck_lab(n_old+1:n_old*2) = {'MI1'};
+blck_lab(2*n_old+1:n_old*3) = {'MI2'};
+blck_lab(3*n_old+1:n_old*4) = {'EX2'};
+
+
+b_c = 1;
+for b = 1:cfg.num_block  
+    b_p(:,b_c) = nanmean(RT_all(cfg.blck_idx{b,1},young));
+    b_c = b_c+1;
+    b_p(:,b_c) = nanmean(RT_all(cfg.blck_idx{b,1},old))
+    b_c = b_c+1;
+end
+
+bp = figure
+boxplot(b_p,'Colors',c_o)
+h = findobj(gca,'Tag','Box');
+for j=1:2:length(h)-1
+patch(get(h(j),'XData'),get(h(j),'YData'),c_y,'FaceAlpha',.5);
+patch(get(h(j+1),'XData'),get(h(j+1),'YData'),c_o,'FaceAlpha',.5);
 
+end
+
+
+
+
+b_mi_o = struct('y', [nanmean(ex1(:,old))  nanmean(mi1(:,old))  nanmean(mi2(:,old))  nanmean(ex2(:,old))],'x',blck_lab,'name', 'Old','marker', struct('color',c_o),'type', 'box');
+b_mi_y = struct('y', [nanmean(ex1(:,young))  nanmean(mi1(:,young))  nanmean(mi2(:,young))  nanmean(ex2(:,young))],'x',blck_lab,'name','Young','marker', struct('color',c_y),'type', 'box');
+
+EX1_y = struct('y', nanmean(ex1(:,young)),'type', 'box');
 
+MI1_o = struct('y', nanmean(mi1(:,old)),'type', 'box');
+MI1_y = struct('y', nanmean(mi1(:,young)),'type', 'box');
+
+MI2_o = struct('y', nanmean(mi2(:,old)),'type', 'box');
+MI2_y = struct('y', nanmean(mi2(:,young)),'type', 'box');
+
+EX2_o = struct('y', nanmean(ex2(:,old)),'type', 'box');
+EX2_y = struct('y', nanmean(ex2(:,young)),'type', 'box');
+
+
+data = {b_mi_y,b_mi_o};
+layout = struct(...
+    'yaxis', struct(...
+      'title', 'Trial times [ms]', ...
+      'zeroline', false), ...
+    'boxmode', 'group');
+response = plotly(data, struct('layout', layout, 'filename', 'box-grouped', 'fileopt', 'overwrite'));
+plot_url = response.url
+
+%%
+%{
+% color grouping data (number of cylinders) and select a subset of the data
+g=gramm('x',repmat([1:cfg.n_trials],length(RT),1)','y',RT_all,'color',g_idx);
+g.facet_grid([],blocks');
+g.stat_boxplot();
+g.set_names('column','Block','x','Trials','y','RT [ms]','color','Group');
+g.draw();
+
+%}