adapt scripts for step a7

code/a7_prep_data_for_analysis.m

@@ -1,306 +0,0 @@
-%% I_SS_prep_data_for_analysis_20170922
-
-% 180124 | now also exclude ART and EMG artifacts
-% 180327 | include OAs, deal wih dropped trials of subjects with missing onsets
-%        | interpolate data to requested times vs. choosing shortest
-%        duration (zero interpolation)
-
-% This script fixes issues with missing onsets in the following way:
-
-% IMPORTANT: For 2160, the first two trials were not available,
-% hence we have to add +2 to the index to identify the correct
-% behavioral trials that belong to the EEG data. For 2203 the
-% first trial is missing. The third and second trial should
-% also be removed, regardless of whether they are indicated to
-% be dropped due to automatic correction.
-
-%% initialize
-
-restoredefaultpath;
-clear all; close all; pack; clc;
-
-%% pathdef
-
-if ismac
-    pn.study        = '/Volumes/LNDG/Projects/StateSwitch/';
-    pn.eeg_root     = [pn.study, 'dynamic/data/eeg/task/A_preproc/SA_preproc_study/'];
-    pn.EEG          = [pn.eeg_root, 'B_data/C_EEG_FT/']; %mkdir(pn.EEG);
-    pn.History      = [pn.eeg_root, 'B_data/D_History/']; %mkdir(pn.History);
-    % add ConMemEEG tools
-    pn.MWBtools     = [pn.eeg_root, 'T_tools/fnct_MWB/'];           addpath(genpath(pn.MWBtools));
-    pn.THGtools     = [pn.eeg_root, 'T_tools/fnct_THG/'];           addpath(genpath(pn.THGtools));
-    pn.commontools  = [pn.eeg_root, 'T_tools/fnct_common/'];        addpath(genpath(pn.commontools));
-    pn.fnct_JQK     = [pn.eeg_root, 'T_tools/fnct_JQK/'];           addpath(genpath(pn.fnct_JQK));
-    pn.FT           = [pn.eeg_root, 'T_tools/fieldtrip-20170904/']; addpath(pn.FT); ft_defaults;
-    pn.helper       = [pn.eeg_root, 'A_scripts/helper/'];           addpath(pn.helper);
-else
-    pn.root         = '/home/mpib/LNDG/StateSwitch/WIP_eeg/SA_preproc_study/';
-    pn.EEG          = [pn.root, 'B_data/C_EEG_FT/'];
-    pn.History      = [pn.root, 'B_data/D_History/'];
-end
-
-%% define Condition & IDs for preprocessing
-
-condEEG = 'dynamic';
-
-%% define IDs for segmentation
-
-% N = 47 YAs + 53 OAs;
-IDs = {'1117';'1118';'1120';'1124';'1126';'1131';'1132';'1135';'1136';'1138';...
-    '1144';'1151';'1158';'1160';'1163';'1164';'1167';'1169';'1172';'1173';...
-    '1178';'1182';'1215';'1216';'1219';'1221';'1223';'1227';'1228';'1233';...
-    '1234';'1237';'1239';'1240';'1243';'1245';'1247';'1250';'1252';'1257';...
-    '1261';'1265';'1266';'1268';'1270';'1276';'1281';...
-    '2104';'2107';'2108';'2112';'2118';'2120';'2121';'2123';'2125';'2129';...
-    '2130';'2131';'2132';'2133';'2134';'2135';'2139';'2140';'2145';'2147';...
-    '2149';'2157';'2160';'2201';'2202';'2203';'2205';'2206';'2209';'2210';...
-    '2211';'2213';'2214';'2215';'2216';'2217';'2219';'2222';'2224';'2226';...
-    '2227';'2236';'2237';'2238';'2241';'2244';'2246';'2248';'2250';'2251';...
-    '2252';'2258';'2261'};
-
-%%  loop IDs
-
-setting.plot = 0; % plot imagesc of resulting timeseries
-
-% prior to loop create matrixes for overviews over artifact-free trials and total trial numbers
-overview_nartfree_trials = {};
-overview_trial_numbers = {};
-ID_unavailable = cell(length(IDs),4);
-for id = 1:length(IDs)
-    for iRun = 1:4
-        
-%         if ~exist([pn.EEG, IDs{id}, '_r',num2str(iRun), '_', condEEG, '_EEG_Rlm_Fhl_rdSeg_Art.mat'])
-%             display(['processing ID ' IDs{id}, ' Run: ', num2str(iRun)]);
-%         else
-%             display(['ID ' IDs{id}, ' Run: ', num2str(iRun), ' has already been processed.']);
-%             continue;
-%         end
-        
-        try
-        %%  load files
-            
-            % load data
-            load([pn.EEG, IDs{id}, '_r',num2str(iRun), '_', condEEG, '_EEG_Rlm_Fhl_rdSeg'],'data_EEG');
-            dataICA = load([pn.EEG, IDs{id}, '_', condEEG, '_EEG_Rlm_Fhl_Ica'],'data');
-            data = data_EEG; clear data_EEG;
-            data.elec = dataICA.data.elec;
-            data.chanlocs = dataICA.data.chanlocs; clear dataICA;
-            % load config
-            load([pn.History, IDs{id}, '_r',num2str(iRun), '_', condEEG, '_config'],'config')
-
-        %% cut data to requested time (necessary due to acquisition jitter)
-        % Note that this does not affect the data, but we simply cut some
-        % sample points from the ITI which is not of interest anyways.
-
-            trig.eventDurInS = [1.5, 2, 1, 3, 2, 1.5]; % total time to extract is 11s
-            trig.eventTriggers = {'S 17'; 'S 72'; 'S 20'; 'S 24'; 'S 64'};
-        
-            % 2160 has only 62 trials, i.e. the first two trials were
-            % not recorded.
-
-            cfg = [];
-            cfg.toilim = [-1.5 9.5];
-            data = ft_redefinetrial(cfg, data);
-            
-        %%  define parameter
-
-            % ICs to reject
-            iclabels    = config.ica1.iclabels.manual;
-            %ics2reject = [iclabels.bli(:); iclabels.mov(:); iclabels.hrt(:); iclabels.ref(:)];
-            ics2reject = [iclabels.bli(:); iclabels.mov(:); iclabels.hrt(:); iclabels.ref(:); iclabels.art(:); iclabels.emg(:)];
-            clear iclabels
-
-            % trials to remove
-            trls2remove = config.ArtDect.trials;
-
-            % channels to interpolate
-            chns2interp = config.ArtDect.channels;
-
-        %% for select IDs, interpolate channels prior to ICA
-        
-        if strcmp(IDs{id}, '2112')
-            cfg = [];
-            cfg.channel = {'all','-ECG','-A2'};
-            dataSelect = ft_preprocessing(cfg,data);
-            cfg = [];
-            cfg.method     = 'spline';
-            if strcmp(IDs{id}, '2112')
-                cfg.badchannel = {'Fz'; 'FCz'};
-            end
-            cfg.trials     = 'all';
-            cfg.lambda     = 1e-5; 
-            cfg.order      = 4; 
-            data = ft_channelrepair(cfg,data);
-            clear cfg;
-        end
-            
-        %% ICA (from weights)
-
-            % ica config
-            cfg.method           = 'runica';
-            cfg.channel          = {'all','-ECG','-A2'};
-            cfg.trials           = 'all';
-            cfg.numcomponent     = 'all';
-            cfg.demean           = 'yes';
-            cfg.runica.extended  = 1;
-
-            % ICA solution
-            cfg.unmixing     = config.ica1.unmixing;
-            cfg.topolabel    = config.ica1.topolabel;
-
-            % components
-            comp = ft_componentanalysis(cfg,data);
-
-            % clear cfg
-            clear cfg data
-
-        %% remove components
-
-            % cfg for rejecting components (reject: blinks, eye movements, ecg, ref)
-            cfg.component = sortrows(ics2reject)';
-            cfg.demean    = 'yes';
-
-            % reject components
-            data = ft_rejectcomponent(cfg,comp);
-
-            % clear cfg
-            clear cfg comp ics2reject
-
-        %%  remove trials
-
-            % IMPORTANT: For 2160, the first two trials were not available,
-            % hence we have to add +2 to the index to identify the correct
-            % behavioral trials that belong to the EEG data. For 2203 the
-            % first trial is missing. The third and second trial should
-            % also be removed, regardless of whether they are indicated to
-            % be dropped due to automatic correction.
-        
-            if strcmp(IDs{id}, '2160') && iRun==1
-                trls2remove=[trls2remove;1];
-            elseif strcmp(IDs{id}, '2203') && iRun==1
-                trls2remove=[trls2remove;1];
-            end
-            
-            % define trials to keep
-            trials               = 1:length(data.trial);
-            trials(trls2remove)  = [];
-
-            if strcmp(IDs{id}, '2160') && iRun==1
-                trials=trials+2;
-                data.time = cat(2,data.time{end},data.time{end},data.time);
-                data.trial = cat(2,data.trial{end},data.trial{end},data.trial);
-            elseif strcmp(IDs{id}, '2203') && iRun==1
-                trials=trials+1;
-                data.time = cat(2,data.time{end},data.time);
-                data.trial = cat(2,data.trial{end},data.trial);
-            end
-            
-            % config for deleting trials
-            cfg.trials   = trials;
-
-            % remove trials
-            data   = ft_preprocessing(cfg,data);
-            nartfree_trials = trials;
-            overview_nartfree_trials{id,iRun} = nartfree_trials;
-
-            config.nartfree_trials = nartfree_trials;
-            
-            % clear variables
-            clear cfg trials trls2remove
-
-        %% remove eye & reference channels (before interpolation)
-
-            cfg.channel     = {'all','-IOR','-LHEOG','-RHEOG','-A1'};
-            cfg.demean      = 'yes';
-
-            % remove channels
-            tmpdat = ft_preprocessing(cfg,data);
-
-            % clear cfg
-            clear cfg
-
-            % interpolation cfg
-            cfg.method     = 'spline';
-            cfg.badchannel = tmpdat.label(chns2interp);
-            cfg.trials     = 'all';
-            cfg.lambda     = 1e-5; 
-            cfg.order      = 4; 
-            cfg.elec       = config.elec;
-
-            % interpolate
-            tmpdat = ft_channelrepair(cfg,tmpdat);
-
-            % clear cfg
-            clear cfg chns2interp
-
-        %%  replace interpolated data
-
-            for j = 1:length(data.trial)
-
-                data.trial{j}(1:60,:) = tmpdat.trial{j};
-
-            end; clear j
-
-            % clear temporary data
-            clear tmpdat
-
-        %%  keep channel x trial artifacts  
-
-            data.ArtDect.channels_x_trials = config.ArtDect.channels_x_trials;            
-
-        %%  save data
-            data_EEG = data; clear data;
-            save([pn.EEG, IDs{id}, '_r',num2str(iRun), '_', condEEG, '_EEG_Rlm_Fhl_rdSeg_Art'],'data_EEG')
-
-%         check data
-%         data_EEG = THG_label_artefacts_20110916(data_EEG);
-%         figure; imagesc(config.ArtDect.channels_x_trials)
-
-            % plot resulting trials
-
-            if setting.plot == 1
-                h = figure;
-                data = NaN(64,size(data_EEG.trial,1),5540);
-                for indTrial = 1:size(data_EEG.trial,2)
-                    data(:,indTrial,1:size(data_EEG.trial{indTrial},2))= data_EEG.trial{indTrial};
-                    subplot(8,8,indTrial);
-                    imagesc(squeeze(data_EEG.trial{indTrial}));
-                end; suptitle(['processing ID ' IDs{id}, ' Run: ', num2str(iRun)]);
-                close(h);
-            end
-
-        %% create overview of percentage of excluded trials, update config.trl
-
-            tmp_trialNumbers(1,1) = length(data_EEG.trial);
-            tmp_trialNumbers(2,1) = 64; % maximum amount of trials
-            tmp_trialNumbers(3,1) = (100-((tmp_trialNumbers(1,1)/tmp_trialNumbers(2,1))*100)); % percentage of excluded trials
-            overview_trial_numbers{id, iRun} = tmp_trialNumbers;
-            config.overview_trial_numbers = tmp_trialNumbers;
-
-        %%  update config.trl with trigger codes
-
-            % add info whether trial is included in final set; 1 = trial containing no artifact
-            config.trl(:,4)                 = 0;
-            config.trl(nartfree_trials, 4)  = 1;
-            % add trial number
-            config.trl(:,5) = 0;
-            config.trl(nartfree_trials, 5)  = nartfree_trials;
-            % load marker file
-            mrk = config.mrk;
-            for i = 1:size(mrk,2)
-               mrk_val{i,1} = mrk(1,i).value;
-            end
-            % add onset and offset triggers
-            config.trl(:,6) = 17;
-            config.trl(:,7) = 64;
-            % save config
-            save([pn.History, IDs{id}, '_r',num2str(iRun), '_', condEEG, '_config'],'config')
-            
-        catch ME
-            warning('Error occured. Please check.');
-            rethrow(ME)
-            fprintf('\n ID not availble! Skip! \n')
-            ID_unavailable{id,iRun} = (IDs{id});
-        end % try...catch
-    end % run
-end % id

code/a7_prep_data_for_analysis/a7_prep_data_for_analysis.m

@@ -0,0 +1,171 @@
+function a7_prep_data_for_analysis(id, rootpath)
+
+if ismac % run if function is not pre-compiled
+    id = '1'; % test for example subject
+    currentFile = mfilename('fullpath');
+    [pathstr,~,~] = fileparts(currentFile);
+    cd(fullfile(pathstr,'..', '..'))
+    rootpath = pwd;
+end
+
+% inputs
+pn.eeg_BIDS = fullfile(rootpath, 'data', 'inputs', 'rawdata', 'eeg_BIDS');
+pn.channel_locations = fullfile(rootpath, 'data', 'inputs', 'rawdata', 'channel_locations');
+pn.events = fullfile(rootpath, 'data', 'inputs', 'rawdata', 'events');
+pn.tools = fullfile(rootpath, 'tools');
+% outputs
+pn.eeg_ft = fullfile(rootpath, 'data', 'outputs', 'eeg');
+pn.history = fullfile(rootpath, 'data', 'outputs', 'history');
+
+if ismac % run if function is not pre-compiled
+     addpath(fullfile(pn.tools, 'fieldtrip')); ft_defaults;
+     addpath(fullfile(pn.tools, 'helpers'));
+end
+
+% N = 33
+IDs = tdfread(fullfile(pn.eeg_BIDS, 'participants.tsv'));
+IDs = cellstr(IDs.participant_id);
+
+id = str2num(id);
+
+display(['processing ID ' num2str(IDs{id})]);
+
+%% load files
+
+% load data
+load(fullfile(pn.eeg_ft, [IDs{id}, '_task-xxxx_eeg_seg.mat']),'data_eeg', 'events');
+
+data_ica = load(fullfile(pn.eeg_ft, [IDs{id}, '_task-xxxx_eeg_ica.mat']),'data');
+data = data_eeg; clear data_eeg;
+data.elec = data_ica.data.elec;
+data.chanlocs = data_ica.data.chanlocs; clear data_ica;
+
+% load config
+load(fullfile(pn.history, [IDs{id}, '_task-xxxx_config.mat']),'config');
+
+%% define parameter
+
+% ICs to reject
+iclabels    = config.ica1.iclabels.manual;
+ics2reject = [iclabels.bli(:); iclabels.mov(:); iclabels.hrt(:); iclabels.ref(:); iclabels.art(:); iclabels.emg(:)];
+clear iclabels
+
+% trials to remove
+trls2remove = config.ArtDect.trials;
+
+% channels to interpolate
+chns2interp = config.ArtDect.channels;
+
+%% ICA (from weights)
+
+% ica config
+cfg.method           = 'runica';
+cfg.channel          = {'all'};
+cfg.trials           = 'all';
+cfg.numcomponent     = 'all';
+cfg.demean           = 'yes';
+cfg.runica.extended  = 1;
+
+% ICA solution
+cfg.unmixing     = config.ica1.unmixing;
+cfg.topolabel    = config.ica1.topolabel;
+
+% components
+comp = ft_componentanalysis(cfg,data);
+
+% clear cfg
+clear cfg data
+
+%% remove components
+
+% cfg for rejecting components (reject: blinks, eye movements, ecg, ref)
+cfg.component = sortrows(ics2reject)';
+cfg.demean    = 'yes';
+
+% reject components
+data = ft_rejectcomponent(cfg,comp);
+
+% clear cfg
+clear cfg comp ics2reject
+
+%% remove trials
+
+% define trials to keep
+trials               = 1:length(data.trial);
+trials(trls2remove)  = [];
+
+% config for deleting trials
+cfg.trials   = trials;
+
+% remove trials
+data   = ft_preprocessing(cfg,data);
+nartfree_trials = trials;
+
+config.nartfree_trials = nartfree_trials;
+
+% clear variables
+clear cfg trials trls2remove
+
+%% remove eye & reference channels (before interpolation)
+
+cfg.channel     = {'all','-IO1','-IO2','-M1', '-M2','-VEOG','-HEOG'};
+cfg.demean      = 'yes';
+
+% remove channels
+data = ft_preprocessing(cfg,data);
+
+% clear cfg
+clear cfg
+
+% interpolation cfg
+cfg            = [];
+cfg.method     = 'spline';
+cfg.badchannel = data.label(chns2interp);
+cfg.trials     = 'all';
+cfg.lambda     = 1e-5; 
+cfg.order      = 4; 
+cfg.elec       = config.elec;
+
+% interpolate
+data = ft_channelrepair(cfg,data);
+
+% clear cfg
+clear cfg chns2interp
+
+%% keep channel x trial artifacts  
+
+data.ArtDect.channels_x_trials = config.ArtDect.channels_x_trials;
+
+%% create overview of percentage of excluded trials, update config.trl
+
+tmp_trialNumbers(1,1) = length(data_eeg.trial);
+tmp_trialNumbers(2,1) = 1200; % maximum amount of trials
+tmp_trialNumbers(3,1) = (100-((tmp_trialNumbers(1,1)/tmp_trialNumbers(2,1))*100)); % percentage of excluded trials
+config.overview_trial_numbers = tmp_trialNumbers;
+
+%% update config.trl with trigger codes
+
+% add info whether trial is included in final set; 1 = trial containing no artifact
+config.trl(:,4)                 = 0;
+config.trl(nartfree_trials, 4)  = 1;
+% add trial number
+config.trl(:,5) = 0;
+config.trl(nartfree_trials, 5)  = nartfree_trials;
+% load marker file
+mrk = config.mrk;
+for i = 1:size(mrk,2)
+   mrk_val{i,1} = mrk(1,i).value;
+end
+
+% save config
+save([pn.History, IDs{id}, '_r',num2str(iRun), '_', condEEG, '_config'],'config')
+
+%% update event table
+
+% remove trials that were not retained during preprocessing
+
+events(config.trl(:,5)==0,:) = [];
+
+%% save data
+data_eeg = data; clear data;
+save(fullfile(pn.eeg_ft, [IDs{id}, '_task-xxxx_eeg_art.mat']),'data_eeg', 'events');

code/a7_prep_data_for_analysis/a7_prep_data_for_analysis_START.sh

@@ -0,0 +1,22 @@
+#!/bin/bash
+
+fun_name="a7_prep_data_for_analysis"
+job_name="eegmp_final"
+
+mkdir ./logs
+
+rootpath="$(pwd)/../.."
+rootpath=$(builtin cd $rootpath; pwd)
+
+for subj in $(seq 1 33); do
+	echo "#!/bin/bash"                    			> job.slurm
+	echo "#SBATCH --job-name ${job_name}_${subj}" 	>> job.slurm
+	echo "#SBATCH --cpus-per-task 4"				>> job.slurm
+	echo "#SBATCH --mem 8gb" 						>> job.slurm
+	echo "#SBATCH --time 01:00:00" 					>> job.slurm
+	echo "#SBATCH --output ./logs/${job_name}_${subj}.out"			>> job.slurm
+	echo "#SBATCH --workdir ." 										>> job.slurm
+	echo "./${fun_name}_run.sh /opt/matlab/R2016b ${subj} ${rootpath}" 	>> job.slurm
+	sbatch job.slurm
+	rm -f job.slurm
+done

code/a7_prep_data_for_analysis/a7_prep_data_for_analysis_prepare.m

@@ -0,0 +1,11 @@
+function a7_prep_data_for_analysis_prepare()
+
+%% add fieldtrip toolbox
+
+addpath(fullfile('..','..', 'tools', 'fieldtrip'));
+ft_defaults()
+ft_compile_mex(true)
+
+mcc -m a7_prep_data_for_analysis.m
+
+exit

code/a7_prep_data_for_analysis/a7_prep_data_for_analysis_prepare.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+
+# This script prepares tardis by compiling the necessary function in MATLAB.
+
+# check [module avail matlab] and choose matlab version
+
+fun_name="a7_prep_data_for_analysis"
+
+module load matlab/R2016b
+matlab -nodesktop -nosplash -r "run ${fun_name}_prepare.m"
+mv run_${fun_name}.sh ${fun_name}_run.sh

code/a8_assign_conditions_to_data.m

@@ -1,129 +0,0 @@
-% Add behavioral information to the EEG data.
-
-% 180123 | written by JQK
-% 180327 | including OAs, check for existing data, changed behavioral matrix
-
-clear all; close all; pack; clc;
-
-%% pathdef
-
-if ismac
-    pn.study        = '/Volumes/LNDG/Projects/StateSwitch/';
-    pn.eeg_root     = [pn.study, 'dynamic/data/eeg/task/A_preproc/SA_preproc_study/'];
-    pn.dynamic_In   = [pn.eeg_root, 'B_data/B_EEG_ET_ByRun/'];
-    pn.triggerTiming= [pn.eeg_root, 'C_figures/D_TriggerTiming/'];
-    pn.EEG          = [pn.eeg_root, 'B_data/C_EEG_FT/']; %mkdir(pn.EEG);
-    pn.History      = [pn.eeg_root, 'B_data/D_History/']; %mkdir(pn.History);
-    pn.logs         = [pn.eeg_root, 'Y_logs/H_ArtCorr/'];
-    % add ConMemEEG tools
-    pn.MWBtools     = [pn.eeg_root, 'T_tools/fnct_MWB/'];           addpath(genpath(pn.MWBtools));
-    pn.THGtools     = [pn.eeg_root, 'T_tools/fnct_THG/'];           addpath(genpath(pn.THGtools));
-    pn.commontools  = [pn.eeg_root, 'T_tools/fnct_common/'];        addpath(genpath(pn.commontools));
-    pn.fnct_JQK     = [pn.eeg_root, 'T_tools/fnct_JQK/'];           addpath(genpath(pn.fnct_JQK));
-    pn.FT           = [pn.eeg_root, 'T_tools/fieldtrip-20170904/']; addpath(pn.FT); ft_defaults;
-    pn.helper       = [pn.eeg_root, 'A_scripts/helper/'];           addpath(pn.helper);
-else
-    pn.root         = '/home/mpib/LNDG/StateSwitch/WIP_eeg/SA_preproc_study/';
-    pn.EEG          = [pn.root, 'B_data/C_EEG_FT/'];
-    pn.History      = [pn.root, 'B_data/D_History/'];
-    pn.triggerTiming= [pn.root, 'C_figures/D_TriggerTiming/'];
-    pn.logs         = [pn.root, 'Y_logs/H_ArtCorr/'];
-end
-
-%% define Condition & IDs for preprocessing
-
-condEEG = 'dynamic';
-
-%% define IDs for segmentation
-
-% N = 47 YAs + 53 OAs;
-IDs = {'1117';'1118';'1120';'1124';'1126';'1131';'1132';'1135';'1136';'1138';...
-    '1144';'1151';'1158';'1160';'1163';'1164';'1167';'1169';'1172';'1173';...
-    '1178';'1182';'1215';'1216';'1219';'1221';'1223';'1227';'1228';'1233';...
-    '1234';'1237';'1239';'1240';'1243';'1245';'1247';'1250';'1252';'1257';...
-    '1261';'1265';'1266';'1268';'1270';'1276';'1281';...
-    '2104';'2107';'2108';'2112';'2118';'2120';'2121';'2123';'2125';'2129';...
-    '2130';'2131';'2132';'2133';'2134';'2135';'2139';'2140';'2145';'2147';...
-    '2149';'2157';'2160';'2201';'2202';'2203';'2205';'2206';'2209';'2210';...
-    '2211';'2213';'2214';'2215';'2216';'2217';'2219';'2222';'2224';'2226';...
-    '2227';'2236';'2237';'2238';'2241';'2244';'2246';'2248';'2250';'2251';...
-    '2252';'2258';'2261'};
-
-%% load behavioral data
-
-behavData = load('/Volumes/LNDG/Projects/StateSwitch/dynamic/data/behavior/STSW_dynamic/A_MergeIndividualData/B_data/SS_MergedDynamic_EEG_MRI_YA_09-Mar-2018.mat');
-
-%% extract data by subject
-
-for id = 1:numel(IDs)
-    if 1%~exist([pn.EEG, IDs{id}, '_', condEEG, '_EEG_Rlm_Fhl_rdSeg_Art_Cond.mat'])
-    for iRun = 1:4
-
-        %% load preprocessed EEG data
-
-        tmp = [];
-        tmp.clock = tic; % set tic for processing duration
-
-        load([pn.History, IDs{id}, '_r',num2str(iRun), '_', condEEG, '_config'],'config');
-        load([pn.EEG, IDs{id}, '_r',num2str(iRun), '_', condEEG, '_EEG_Rlm_Fhl_rdSeg_Art'],'data_EEG');
-
-        data = data_EEG; clear data_EEG;
-
-        %% remove extraneous channels
-
-        rem             = [];
-        rem.channel     = {'all','-IOR','-LHEOG','-RHEOG','-A1'};
-        rem.demean      = 'no';
-        
-        dataNew{iRun} = ft_preprocessing(rem,data); clear rem data;
-        
-        %% get behavioral data (incl. condition assignment)
-
-        behavIdx = find(strcmp(behavData.IDs_all, IDs{id})); % get index of current subject in behavioral matrix
-        SubjBehavData.Atts          = behavData.MergedDataEEG.Atts(:,behavIdx);
-        SubjBehavData.StateOrders   = behavData.MergedDataEEG.StateOrders(:,behavIdx);
-        SubjBehavData.RTs           = behavData.MergedDataEEG.RTs(:,behavIdx);
-        SubjBehavData.Accs          = behavData.MergedDataEEG.Accs(:,behavIdx);
-        SubjBehavData.CuedAttributes = reshape(cat(1,behavData.MergedDataEEG.expInfo{behavIdx}.AttCuesRun{:})',256,1);
-        
-        % create matrix with crucial condition info
-        CondData = NaN(256,7);
-        for indTrial = 1:256
-           tmp_cuedTrial = SubjBehavData.CuedAttributes(indTrial);
-           if ismember(1,tmp_cuedTrial{:})
-               CondData(indTrial,1) = 1;
-           end
-           if ismember(2,tmp_cuedTrial{:})
-               CondData(indTrial,2) = 1;
-           end
-           if ismember(3,tmp_cuedTrial{:})
-               CondData(indTrial,3) = 1;
-           end
-           if ismember(4,tmp_cuedTrial{:})
-               CondData(indTrial,4) = 1;
-           end
-        end
-        CondData(:,5) = repmat(1:8,1,32)'; % serial position
-        CondData(:,6) = SubjBehavData.Atts;
-        CondData(:,7) = 1:256;
-        CondData(:,8) = SubjBehavData.StateOrders;
-        CondData(:,9) = SubjBehavData.RTs;
-        CondData(:,10) = SubjBehavData.Accs;
-        % select trials from current run
-        CurTrials{iRun} = CondData(((iRun-1)*64)+1:iRun*64,:);
-        % remove trials that were not retained during preprocessing
-        removedTrials = []; removedTrials = setdiff(1:64,config.nartfree_trials);
-        CurTrials{iRun}(removedTrials,:) = [];
-        
-    end; clear CondData;
-    %% combine data across runs
-    data = ft_appenddata([], dataNew{1}, dataNew{2}, dataNew{3}, dataNew{4});
-    data.TrlInfo = cat(1,CurTrials{:});
-    data.TrlInfoLabels = {'Att1 cued', 'Att2 cued', 'Att3 cued', 'Att4 cued', ...
-        'Serial position', 'WinningAtt', 'Continuous position', 'Cue Dimensionality',...
-        'RT', 'Acc'};
-    save([pn.EEG, IDs{id}, '_', condEEG, '_EEG_Rlm_Fhl_rdSeg_Art_Cond'],'data');
-    else
-        disp(['Data for ID ',IDs{id}, ' already exists!']);
-    end; % if exist
-end