%Pre-content

%%% The content below - everything preceeding Section 1, should be run first.
%%% This is the case irrespective of whether you're planning to run Section
%%% 1 or Section 2. To run any concent in this script, you can either
%%% choose 'Run Section' in the menu on the far right, or you can hold down
%%% control and press enter.

%%% Cleans up the workspace - useful to run in case you have any leftovers
%%% from previous MATLAB activity.
clear all

%%% Where the data are stored (see 'Scripts: essential information' for more details). 
% e.g., pathtodata = 'C:\Users\Jen\EEG training\Experiment 1\';
pathtodata = '[ENTER YOUR PATH HERE]';

%%% Where EEGLAB is stored
% e.g., pathtoeeglab = 'C:\Users\Jen\MATLAB\eeglab2021.1';
pathtoeeglab = '[ENTER YOUR PATH HERE]';

%%% Adds the paths
addpath(pathtodata);
addpath(pathtoeeglab);

%%% List your participants. Each participant should have a new line, with
%%% the structure badchans.[dataset name] = { };
%%% e.g., badchans.[Dataset_filtering] = { };
badchans.Dataset_1 = {};

%%% tells MATLAB what the subject (dataset) names are
subjects = fieldnames(badchans)';

% This just figures out whether we're going to need backslash or
% forwardslash delimiters (i.e., whether we're using pc or unix)
if ismember(1, arrayfun( @(x)(strcmp('\',x)), pathtodata))
    path_delimiter = '\';
else
    path_delimiter = '/';
end;

%% Section 1

%%% the below line tells EEGLAB to conduct the following steps for all
%%% datasets, from 1 to whatever length 'subjects' (our dataset list) is.
for n = 1:length(subjects)
    
    subject = subjects{n}

        %%% Open EEGLAB
        eeglab
        
        %Read Data
        EEG = pop_loadcnt([pathtodata subject '\' subject '.cnt'] , 'dataformat', 'auto', 'memmapfile', '');
        EEG.setname = subject;
        [ALLEEG EEG CURRENTSET] = pop_newset(ALLEEG, EEG, 0,'setname',subject,'gui','off'); 
        EEG = eeg_checkset( EEG );
        
        %Import channel locations
        %%% Note: as long as you've specified your path to EEGLAB correctly above,
        %%% the channel location file should be found.
        EEG=pop_chanedit(EEG, 'lookup',[pathtoeeglab '\\functions\\supportfiles\\Standard-10-5-Cap385.sfp']);
        [ALLEEG EEG] = eeg_store(ALLEEG, EEG, CURRENTSET);
        
        %Resample
        %%% here '250' refers to our new sampling rate. If you want to use a different sampling rate, change this number.
        EEG = pop_resample( EEG, 250);
    
        %High-pass filter
        %%% The filter works as follows: 
        %%% EEG  = pop_basicfilter( EEG,  [HOW MANY ELECTODES - ie. 1:67, OR 1:34],
        %%% 'Boundary', 'boundary', 'Cutoff',  [THE HALF-AMP CUT-OFF YOU WANT, i.e. 0.01, OR 0.1], 
        %%% 'Design', '[WHICH TYPE OF FILTER]', 'Filter', '[HIGHPASS OR LOWPASS]', 'Order',  [FILTER ORDER] ); 
        EEG  = pop_basicfilter( EEG,  1:67 , 'Boundary', 'boundary', 'Cutoff',  0.1, 'Design', 'butter', 'Filter', 'highpass', 'Order',  2 ); 
       
        %Re-reference 
        
        %%% To mastoids
        %%% Here it is important that you know which channels your mastoids
        %%% were. Often these will be EXG channels as below, but they may
        %%% also be labelled M1/M2.
        channels = arrayfun( @(x)(EEG.chanlocs(x).labels), 1:EEG.nbchan , 'UniformOutput', false);
        mastoids_idx = find(strcmpi('EXG1', channels) | strcmpi('EXG2', channels));
        EEG = pop_reref( EEG, mastoids_idx ,'keepref','on');
        
        %%% OR
        
        %%% To global average
        EEG = pop_reref( EEG, []);
        
        %Save the dataset
        EEG = pop_saveset( EEG, 'filename',[subject '_section1.set'],'filepath',[pathtodata '\' subject '\']);
        [ALLEEG EEG] = eeg_store(ALLEEG, EEG, CURRENTSET);
        ALLEEG = pop_delset( ALLEEG, [1] );
        
end;

%% Data cleaning
%%% Section 2 runs on the dataset that Section 1 output.
%%% Importantly,between the two sections you will need to clean your data
%%% (i.e., the _section1.set file that the above section produces). In
%%% order to move on to Section 2 below, you will need to run the first 
%%% part of this script, which sets up the structures (the content pre-Section 1). 

%%% To do this, place your cursor anywhere in the pre-content, hold down
%%% cntrl and press enter. You can then scross back down to Section 2 and
%%% do the same.

%% Section 2
for n = 1:length(subjects)
    
    subject = subjects{n}

        %%% Open EEGLAB
        eeglab
        
        %Load data - note we're now reading the .set, not the .cnt
        [ALLEEG EEG CURRENTSET ALLCOM] = eeglab;
        EEG = pop_loadset('filename',[subject '_section1.set'],'filepath',[pathtodata subject '\']);
        [ALLEEG, EEG, CURRENTSET] = eeg_store( ALLEEG, EEG, 0, 'setname',subject,'gui','off' );
        EEG = eeg_checkset( EEG );        
 
%%% NEW CONTENT
        
           %ICA
        %%% This first little bit of code identifies a participant's bad channels, as per
        %%% the electrode names entered in the 'badchans' structure above,
        %%% The second line then assigns these electrodes to the structure
        %%% 'bad_idx'. And the third line groups the mastoids as 'mastoids_idx'.
        %%% This means these electrodes can be exluded from the ICA
        temp = cellfun(@(x)(strcmpi(x, arrayfun(@(x)(EEG.chanlocs(x).labels),1:EEG.nbchan,'UniformOutput',false) ) ), badchans.(subject),'UniformOutput',false);
        bad_idx = cellfun( @find, temp );

        %%% This first line creates a structure called 'chans', which lists
        %%% all the channels in your dataset
        chans = 1:EEG.nbchan;
        %%% this next line will remove bad channels, mastoids, and the last
        %%% channel (which is trigger)
        goodchans = chans( find( ~ismember(chans, [bad_idx mastoids_idx EEG.nbchan]) ) );
        EEG = pop_runica(EEG, 'extended',1, 'pca', EEG.nbchan-length(badchans.(subject))-3, 'interupt','off', 'chanind', goodchans);
        EEG = eeg_checkset( EEG );
        
        %Save the dataset
        EEG = pop_saveset( EEG, 'filename',[subject '_script6.set'],'filepath',[pathtodata '\' subject '\']);
        [ALLEEG EEG] = eeg_store(ALLEEG, EEG, CURRENTSET);
        ALLEEG = pop_delset( ALLEEG, [1] );
end;