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main_analysis_chanpair_acrosstime_github.m
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main_analysis_chanpair_acrosstime_github.m
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%% Main analysis connectivity
clear all;
clc;
num_trials = 5; % To analyze trial by trial (only do it with the first 5 trials)
addpath(genpath([pwd '/scripts']));
cond_lab = {'cane', 'grasp'};
lab_age = '12m'; % Change Age if necessary!
method = ''; % ISPC
data_location = [pwd '/LAEEG_' lab_age '/chanpair/'];
subnum_cane=dir([data_location '*CTS_MTH_chanpair_' lab_age '*']);
subnum_grasp=dir([data_location '*GTS_MTH_chanpair_' lab_age '*']);
sub_list_cane={subnum_cane.name};
sub_list_grasp={subnum_grasp.name};
index1 = find(cellfun('length',regexp(sub_list_cane,['connect_overtime' method '_LA'])) == 1);
index2 = find(cellfun('length',regexp(sub_list_grasp,['connect_overtime' method '_LA'])) == 1);
sub_list_cane = sub_list_cane(index1);
sub_list_grasp = sub_list_grasp(index2);
num_subj = length(sub_list_cane);
load(strcat(pwd,'/metadata/time.mat'));
load(strcat(pwd,'/metadata/frequency.mat'));
win_extrems = 500;
time_time = time(1)+win_extrems:10:time(end)-win_extrems; % for ICPC across time
for fr = 1 : 3 % Loop across the 3 frequencies of interest
switch fr
case 1
freq_win = [3, 5]; % Theta
case 2
freq_win = [6, 9]; % Alpha
case 3
freq_win = [15, 19]; % Beta
end
freq_range = [num2str(freq_win(1)) '-' num2str(freq_win(2)) 'Hz'];
pos_freq = frequency>=freq_win(1) & frequency<=freq_win(2);
% to count number subjects with 3 trials, 4 trials or more
sum_3trials = zeros(1,2);
sum_4trials = zeros(1,2);
sum_5trials = zeros(1,2);
%% loop across subjects
it = 0;
included_trials = zeros(2, num_subj);
for s = 1:2:num_subj*2
it = it+1;
list1 = eval(['sub_list_' cond_lab{1}]); % cane
list2 = eval(['sub_list_' cond_lab{2}]); % grasp
sub1 = list1{it}
sub2 = list2{it}
data_1 = load([data_location sub1]); % cane
data_2 = load([data_location sub2]); % grasp
included_trials(1, it) = size(data_1.ispc_OC, 3);
included_trials(2, it) = size(data_2.ispc_OC, 3);
% ISPC
% Mean across hemisphere, trials and frequency
ispc_FC_all(it,:,1) = squeeze(mean(mean(mean(data_1.ispc_FC(pos_freq,:,:,:),4),3),1));
ispc_FC_all(it,:,2) = squeeze(mean(mean(mean(data_2.ispc_FC(pos_freq,:,:,:),4),3),1));
ispc_PC_all(it,:,1) = squeeze(mean(mean(mean(data_1.ispc_PC(pos_freq,:,:,:),4),3),1));
ispc_PC_all(it,:,2) = squeeze(mean(mean(mean(data_2.ispc_PC(pos_freq,:,:,:),4),3),1));
ispc_FO_all(it,:,1) = squeeze(mean(mean(mean(data_1.ispc_FO(pos_freq,:,:,:),4),3),1));
ispc_FO_all(it,:,2) = squeeze(mean(mean(mean(data_2.ispc_FO(pos_freq,:,:,:),4),3),1));
ispc_PO_all(it,:,1) = squeeze(mean(mean(mean(data_1.ispc_PO(pos_freq,:,:,:),4),3),1));
ispc_PO_all(it,:,2) = squeeze(mean(mean(mean(data_2.ispc_PO(pos_freq,:,:,:),4),3),1));
ispc_OC_all(it,:,1) = squeeze(mean(mean(mean(data_1.ispc_OC(pos_freq,:,:,:),4),3),1));
ispc_OC_all(it,:,2) = squeeze(mean(mean(mean(data_2.ispc_OC(pos_freq,:,:,:),4),3),1));
%% ISPC including separate trials (up to 5)
%% Condition 1
if(size(data_1.ispc_FO,3) < num_trials)
if(size(data_1.ispc_FO,3) > 3) % 4 trials
sum_4trials(1) = sum_4trials(1) + 1;
ispc_FC_trial(it,:,1:4,1) = squeeze(mean(mean(data_1.ispc_FC(pos_freq,:,1:4,:),4),1));
ispc_PC_trial(it,:,1:4,1) = squeeze(mean(mean(data_1.ispc_PC(pos_freq,:,1:4,:),4),1));
ispc_FO_trial(it,:,1:4,1) = squeeze(mean(mean(data_1.ispc_FO(pos_freq,:,1:4,:),4),1));
ispc_PO_trial(it,:,1:4,1) = squeeze(mean(mean(data_1.ispc_PO(pos_freq,:,1:4,:),4),1));
ispc_OC_trial(it,:,1:4,1) = squeeze(mean(mean(data_1.ispc_OC(pos_freq,:,1:4,:),4),1));
ispc_FC_trial(it,:,5,1) = NaN;
ispc_PC_trial(it,:,5,1) = NaN;
ispc_FO_trial(it,:,5,1) = NaN;
ispc_PO_trial(it,:,5,1) = NaN;
ispc_OC_trial(it,:,5,1) = NaN;
else % 3 trials
sum_3trials(1) = sum_3trials(1) + 1;
ispc_FC_trial(it,:,1:3,1) = squeeze(mean(mean(data_1.ispc_FC(pos_freq,:,1:3,:),4),1));
ispc_PC_trial(it,:,1:3,1) = squeeze(mean(mean(data_1.ispc_PC(pos_freq,:,1:3,:),4),1));
ispc_FO_trial(it,:,1:3,1) = squeeze(mean(mean(data_1.ispc_FO(pos_freq,:,1:3,:),4),1));
ispc_PO_trial(it,:,1:3,1) = squeeze(mean(mean(data_1.ispc_PO(pos_freq,:,1:3,:),4),1));
ispc_OC_trial(it,:,1:3,1) = squeeze(mean(mean(data_1.ispc_OC(pos_freq,:,1:3,:),4),1));
ispc_FC_trial(it,:,4:5,1) = NaN;
ispc_PC_trial(it,:,4:5,1) = NaN;
ispc_FO_trial(it,:,4:5,1) = NaN;
ispc_PO_trial(it,:,4:5,1) = NaN;
ispc_OC_trial(it,:,4:5,1) = NaN;
end
else % 5 trials or more
sum_5trials(1) = sum_5trials(1) + 1;
ispc_FC_trial(it,:,:,1) = squeeze(mean(mean(data_1.ispc_FC(pos_freq,:,1:num_trials,:),4),1));
ispc_PC_trial(it,:,:,1) = squeeze(mean(mean(data_1.ispc_PC(pos_freq,:,1:num_trials,:),4),1));
ispc_FO_trial(it,:,:,1) = squeeze(mean(mean(data_1.ispc_FO(pos_freq,:,1:num_trials,:),4),1));
ispc_PO_trial(it,:,:,1) = squeeze(mean(mean(data_1.ispc_PO(pos_freq,:,1:num_trials,:),4),1));
ispc_OC_trial(it,:,:,1) = squeeze(mean(mean(data_1.ispc_OC(pos_freq,:,1:num_trials,:),4),1));
end
%% Condition 2
if(size(data_2.ispc_FO,3) < num_trials)
if(size(data_2.ispc_FO,3) > 3) % 4 trials
sum_4trials(2) = sum_4trials(2) + 1;
ispc_FC_trial(it,:,1:4,2) = squeeze(mean(mean(data_2.ispc_FC(pos_freq,:,1:4,:),4),1));
ispc_PC_trial(it,:,1:4,2) = squeeze(mean(mean(data_2.ispc_PC(pos_freq,:,1:4,:),4),1));
ispc_FO_trial(it,:,1:4,2) = squeeze(mean(mean(data_2.ispc_FO(pos_freq,:,1:4,:),4),1));
ispc_PO_trial(it,:,1:4,2) = squeeze(mean(mean(data_2.ispc_PO(pos_freq,:,1:4,:),4),1));
ispc_OC_trial(it,:,1:4,2) = squeeze(mean(mean(data_2.ispc_OC(pos_freq,:,1:4,:),4),1));
ispc_FC_trial(it,:,5,2) = NaN;
ispc_PC_trial(it,:,5,2) = NaN;
ispc_FO_trial(it,:,5,2) = NaN;
ispc_PO_trial(it,:,5,2) = NaN;
ispc_OC_trial(it,:,5,2) = NaN;
else % 3 trials
sum_3trials(2) = sum_3trials(2) + 1;
ispc_FC_trial(it,:,1:3,2) = squeeze(mean(mean(data_2.ispc_FC(pos_freq,:,1:3,:),4),1));
ispc_PC_trial(it,:,1:3,2) = squeeze(mean(mean(data_2.ispc_PC(pos_freq,:,1:3,:),4),1));
ispc_FO_trial(it,:,1:3,2) = squeeze(mean(mean(data_2.ispc_FO(pos_freq,:,1:3,:),4),1));
ispc_PO_trial(it,:,1:3,2) = squeeze(mean(mean(data_2.ispc_PO(pos_freq,:,1:3,:),4),1));
ispc_OC_trial(it,:,1:3,2) = squeeze(mean(mean(data_2.ispc_OC(pos_freq,:,1:3,:),4),1));
ispc_FC_trial(it,:,4:5,2) = NaN;
ispc_PC_trial(it,:,4:5,2) = NaN;
ispc_FO_trial(it,:,4:5,2) = NaN;
ispc_PO_trial(it,:,4:5,2) = NaN;
ispc_OC_trial(it,:,4:5,2) = NaN;
end
else % 5 trials or more
sum_5trials(2) = sum_5trials(2) + 1;
ispc_FC_trial(it,:,:,2) = squeeze(mean(mean(data_2.ispc_FC(pos_freq,:,1:num_trials,:),4),1));
ispc_PC_trial(it,:,:,2) = squeeze(mean(mean(data_2.ispc_PC(pos_freq,:,1:num_trials,:),4),1));
ispc_FO_trial(it,:,:,2) = squeeze(mean(mean(data_2.ispc_FO(pos_freq,:,1:num_trials,:),4),1));
ispc_PO_trial(it,:,:,2) = squeeze(mean(mean(data_2.ispc_PO(pos_freq,:,1:num_trials,:),4),1));
ispc_OC_trial(it,:,:,2) = squeeze(mean(mean(data_2.ispc_OC(pos_freq,:,1:num_trials,:),4),1));
end
subjects_included{it} = list1{it};
end
save_data=[pwd, '/all_subj_con_acrosstime' method '_' lab_age '_' freq_range '.mat'];
save (save_data, 'ispc_FC_all', 'ispc_PC_all', 'ispc_FO_all', 'ispc_PO_all', 'ispc_OC_all', 'ispc_FC_trial', 'ispc_PC_trial', 'ispc_FO_trial', 'ispc_PO_trial', 'ispc_OC_trial',...
'subjects_included', 'sum_4trials','sum_3trials', 'sum_5trials', '-v7.3');
% load(strcat(pwd,'/metadata/time.mat'));
% load(strcat(pwd,'/metadata/frequency.mat'));
load(strcat(pwd,'/metadata/channel104_location.mat'));
freqs = frequency;
num_subj = length(subjects_included);
%% Save data (average trials)
n_subj = size(ispc_FO_all,1);
n_time = size(ispc_FO_all,2);
n_cond = 2;
n_rows = n_cond*n_time;
n_columns = n_subj + 4; % Time, Age, Pair, Condition + subjects
data_FC_ispc = cell(n_rows,n_columns);
data_PC_ispc = cell(n_rows,n_columns);
data_FO_ispc = cell(n_rows,n_columns);
data_PO_ispc = cell(n_rows,n_columns);
data_OC_ispc = cell(n_rows,n_columns);
c_time = time_time';
[c_age{1:n_time,1}] = deal(lab_age);
[c_cond{1:n_time,1}] = deal(cond_lab{1});
[c_cond{1:n_time,2}] = deal(cond_lab{2});
[c_chpair{1:n_time,1}] = deal('FC');
[c_chpair{1:n_time,2}] = deal('PC');
[c_chpair{1:n_time,3}] = deal('FO');
[c_chpair{1:n_time,4}] = deal('PO');
[c_chpair{1:n_time,5}] = deal('OC');
vnames = {'Time','Condition','Age','ChannelPair',subjects_included{:}};
it = 1;
for c = 1:2
%% IF WE WANT TO EXPORT THE DATA TO R AND PLOT IT THERE
% Create cell matrix that we will use at the end to create a
% table
%%%% ISPC - connectivity estimate
data_FC_ispc(it:it+n_time-1 , 1) = num2cell(c_time);
data_FC_ispc(it:it+n_time-1 , 2) = c_cond(:,c);
data_FC_ispc(it:it+n_time-1 , 3) = c_age(:,1);
data_FC_ispc(it:it+n_time-1 , 4) = c_chpair(:,1); % FC
data_FC_ispc(it:it+n_time-1 , 5:5+n_subj-1) = num2cell(ispc_FC_all(:,:,c)');
data_PC_ispc(it:it+n_time-1 , 1) = num2cell(c_time);
data_PC_ispc(it:it+n_time-1 , 2) = c_cond(:,c);
data_PC_ispc(it:it+n_time-1 , 3) = c_age(:,1);
data_PC_ispc(it:it+n_time-1 , 4) = c_chpair(:,2); % PC
data_PC_ispc(it:it+n_time-1 , 5:5+n_subj-1) = num2cell(ispc_PC_all(:,:,c)');
data_FO_ispc(it:it+n_time-1 , 1) = num2cell(c_time);
data_FO_ispc(it:it+n_time-1 , 2) = c_cond(:,c);
data_FO_ispc(it:it+n_time-1 , 3) = c_age(:,1);
data_FO_ispc(it:it+n_time-1 , 4) = c_chpair(:,3); % FO
data_FO_ispc(it:it+n_time-1 , 5:5+n_subj-1) = num2cell(ispc_FO_all(:,:,c)');
data_PO_ispc(it:it+n_time-1 , 1) = num2cell(c_time);
data_PO_ispc(it:it+n_time-1 , 2) = c_cond(:,c);
data_PO_ispc(it:it+n_time-1 , 3) = c_age(:,1);
data_PO_ispc(it:it+n_time-1 , 4) = c_chpair(:,4); % PO
data_PO_ispc(it:it+n_time-1 , 5:5+n_subj-1) = num2cell(ispc_PO_all(:,:,c)');
data_OC_ispc(it:it+n_time-1 , 1) = num2cell(c_time);
data_OC_ispc(it:it+n_time-1 , 2) = c_cond(:,c);
data_OC_ispc(it:it+n_time-1 , 3) = c_age(:,1);
data_OC_ispc(it:it+n_time-1 , 4) = c_chpair(:,5); % OC
data_OC_ispc(it:it+n_time-1 , 5:5+n_subj-1) = num2cell(ispc_OC_all(:,:,c)');
it = it+n_time;
end
%% Save data (save data 5 first trials separately)
n_cond = 2;
n_trials = num_trials;
n_rows = n_cond*n_time*n_trials;
n_factors = 5;
n_columns = n_subj + n_factors; % Time, Condition, Age, ChanPair, #trial + subjects
data_FC_ispc_tr = cell(n_rows,n_columns);
data_PC_ispc_tr = cell(n_rows,n_columns);
data_FO_ispc_tr = cell(n_rows,n_columns);
data_PO_ispc_tr = cell(n_rows,n_columns);
data_OC_ispc_tr = cell(n_rows,n_columns);
c_time = time_time';
[c_trial{1:n_time,1}] = deal('Trial1');
[c_trial{1:n_time,2}] = deal('Trial2');
[c_trial{1:n_time,3}] = deal('Trial3');
[c_trial{1:n_time,4}] = deal('Trial4');
[c_trial{1:n_time,5}] = deal('Trial5');
vnames_tr = {'Time','Condition','Age','ChannelPair','TrialNum',subjects_included{:}};
it = 1;
for trial = 1:n_trials
for c = 1:2
%% IF WE WANT TO EXPORT THE DATA TO R AND PLOT IT THERE
% Create cell matrix that we will use at the end to create a table
%%%% ISPC
data_FC_ispc_tr(it:it+n_time-1 , 1) = num2cell(c_time);
data_FC_ispc_tr(it:it+n_time-1 , 2) = c_cond(:,c);
data_FC_ispc_tr(it:it+n_time-1 , 3) = c_age(:,1);
data_FC_ispc_tr(it:it+n_time-1 , 4) = c_chpair(:,1); % FC
data_FC_ispc_tr(it:it+n_time-1 , 5) = c_trial(:,trial); % trial
data_FC_ispc_tr(it:it+n_time-1 , n_factors+1:n_factors+n_subj) = num2cell(ispc_FC_trial(:,:,trial,c)');
data_PC_ispc_tr(it:it+n_time-1 , 1) = num2cell(c_time);
data_PC_ispc_tr(it:it+n_time-1 , 2) = c_cond(:,c);
data_PC_ispc_tr(it:it+n_time-1 , 3) = c_age(:,1);
data_PC_ispc_tr(it:it+n_time-1 , 4) = c_chpair(:,2); % PC
data_PC_ispc_tr(it:it+n_time-1 , 5) = c_trial(:,trial); % trial
data_PC_ispc_tr(it:it+n_time-1 , n_factors+1:n_factors+n_subj) = num2cell(ispc_PC_trial(:,:,trial,c)');
data_FO_ispc_tr(it:it+n_time-1 , 1) = num2cell(c_time);
data_FO_ispc_tr(it:it+n_time-1 , 2) = c_cond(:,c);
data_FO_ispc_tr(it:it+n_time-1 , 3) = c_age(:,1);
data_FO_ispc_tr(it:it+n_time-1 , 4) = c_chpair(:,3); % FO
data_FO_ispc_tr(it:it+n_time-1 , 5) = c_trial(:,trial); % trial
data_FO_ispc_tr(it:it+n_time-1 , n_factors+1:n_factors+n_subj) = num2cell(ispc_FO_trial(:,:,trial,c)');
data_PO_ispc_tr(it:it+n_time-1 , 1) = num2cell(c_time);
data_PO_ispc_tr(it:it+n_time-1 , 2) = c_cond(:,c);
data_PO_ispc_tr(it:it+n_time-1 , 3) = c_age(:,1);
data_PO_ispc_tr(it:it+n_time-1 , 4) = c_chpair(:,4); % PO
data_PO_ispc_tr(it:it+n_time-1 , 5) = c_trial(:,trial); % trial
data_PO_ispc_tr(it:it+n_time-1 , n_factors+1:n_factors+n_subj) = num2cell(ispc_PO_trial(:,:,trial,c)');
data_OC_ispc_tr(it:it+n_time-1 , 1) = num2cell(c_time);
data_OC_ispc_tr(it:it+n_time-1 , 2) = c_cond(:,c);
data_OC_ispc_tr(it:it+n_time-1 , 3) = c_age(:,1);
data_OC_ispc_tr(it:it+n_time-1 , 4) = c_chpair(:,5); % OC
data_OC_ispc_tr(it:it+n_time-1 , 5) = c_trial(:,trial); % trial
data_OC_ispc_tr(it:it+n_time-1 , n_factors+1:n_factors+n_subj) = num2cell(ispc_OC_trial(:,:,trial,c)');
it = it+n_time;
end
end
%% SAVE CSV FILES TO ANALYZE AND PLOT DATA WITH R
% Create output tables
T_FC_ispc = cell2table(data_FC_ispc, 'VariableNames',vnames);
writetable(T_FC_ispc, [pwd '/For R/T_FC_ispc_time' method '_' lab_age '_' freq_range '.csv']);
T_PC_ispc = cell2table(data_PC_ispc, 'VariableNames',vnames);
writetable(T_PC_ispc, [pwd '/For R/T_PC_ispc_time' method '_' lab_age '_' freq_range '.csv']);
T_FO_ispc = cell2table(data_FO_ispc, 'VariableNames',vnames);
writetable(T_FO_ispc, [pwd '/For R/T_FO_ispc_time' method '_' lab_age '_' freq_range '.csv']);
T_PO_ispc = cell2table(data_PO_ispc, 'VariableNames',vnames);
writetable(T_PO_ispc, [pwd '/For R/T_PO_ispc_time' method '_' lab_age '_' freq_range '.csv']);
T_OC_ispc = cell2table(data_OC_ispc, 'VariableNames',vnames);
writetable(T_OC_ispc, [pwd '/For R/T_OC_ispc_time' method '_' lab_age '_' freq_range '.csv']);
T_FC_ispc_tr = cell2table(data_FC_ispc_tr, 'VariableNames',vnames_tr);
writetable(T_FC_ispc_tr, [pwd '/For R/T_FC_ispc_time_tr' method '_' lab_age '_' freq_range '.csv']);
T_PC_ispc_tr = cell2table(data_PC_ispc_tr, 'VariableNames',vnames_tr);
writetable(T_PC_ispc_tr, [pwd '/For R/T_PC_ispc_time_tr' method '_' lab_age '_' freq_range '.csv']);
T_FO_ispc_tr = cell2table(data_FO_ispc_tr, 'VariableNames',vnames_tr);
writetable(T_FO_ispc_tr, [pwd '/For R/T_FO_ispc_time_tr' method '_' lab_age '_' freq_range '.csv']);
T_PO_ispc_tr = cell2table(data_PO_ispc_tr, 'VariableNames',vnames_tr);
writetable(T_PO_ispc_tr, [pwd '/For R/T_PO_ispc_time_tr' method '_' lab_age '_' freq_range '.csv']);
T_OC_ispc_tr = cell2table(data_OC_ispc_tr, 'VariableNames',vnames_tr);
writetable(T_OC_ispc_tr, [pwd '/For R/T_OC_ispc_time_tr' method '_' lab_age '_' freq_range '.csv']);
end