Replace ana02_behave.m

% 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\'];

  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));

[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])

%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% 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)

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)')];

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

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();

%}