%% Pre-processing pipeline pseudocode
%% Everything run in MATLAB
%% Necessary extensions - eeglab, preppipeline, AMICA, corrmap, CSD

% Preprocessing
    read in data
    re-reference to average
    remove baseline
    insert channel locations 'MMN_ElectrodeCoords_MA2.ced)'
    High Pass Filter - 'pop_eegfiltnew( EEG, 1, [], [], [0], 0, 0, 0);'
    Run preppipeline
        intpChans = setxor(1:64, [5 27 38 60]); % which channels to use for interpolation; exclude EOG channels
        params = struct('name', [vhdr{1} 'snum' num2str(sx) '.' num2str(nf)], ...
                    'lineFrequencies', [60:60:300], ...    % Line frequencies to remove
                    'referenceChannels', intpChans, ...    % Channels to be used for re-referencing
                    'evaluationChannels', intpChans, ...   % Channels to be used for interpolation
                    'rereferencedChannels', [1:64], ...    % Channels to be linenoise removed and referenced
                    'detrendChannels', [1:64], ...         % Channels to detrend
                    'lineNoiseChannels', [1:64], ...       % Channels to remove line noise from
                    'ignoreBoundaryEvents', true, ...      % ??? not sure why it doesn't work without
                    'detrendType', 'none', ...             % Use high pass filter to detrend channels
                    'detrendCutoff', 1, ...                % High pass filter frequency cut off
                    'referenceType', 'robust', ...         % Robust reference
                    'meanEstimateType', 'median', ...      % Use median for robust reference
                    'interpolationOrder', 'post-reference', ... % Interpolate channels after robust referencing
                    'keepFiltered', true);                % Retain filtering?                   
        EEG = prepPipeline(EEG, params);
    Low Pass Filter - 
        pop_eegfiltnew( EEG, [], 50, [], [0], 0, 0, 0);
    Epoch to -1.5 - 3 seconds around stimulus using these triggers 
        [111:114 121:124 211:214 221:224]
    Remove large artifacts using pop_autorej 
        pop_autorej(EEG, 'nogui','on','threshold',500, 'startprob',5,'maxrej',5);
    Downsample to 500 Hz 
        pop_resample( EEG, 500 );
    Run AMICA using the following
        [EEG.icaweights, EEG.icasphere, EEG.icamods] = runamica15(EEG.data(:,:), ...
            'max_iter', 10000, 'writestep', 500, 'pcakeep', 42, 'do_reject', 1,  ...
            'max_threads', 12, 'rejsig', 4);
    Create eeglab 'STUDY' structure
    Precompute topography to extract EOG using STUDY
        std_precomp(STUDY, ALLEEG, 'components','allcomps','on','recompute','on','scalp','on');
    Find prototypical VEOG artifact and run 'corrmap' to identify all VEOG components
        corrmap(STUDY, ALLEEG, indx, 1, 'ics',1,'pl', 'both','clname','VEOG','badcomps','no', 'resetclusters','on');
    Reject epochs by trend and component spectra, exclude for VEOG artifact
        pop_rejtrend( EEG, 0, include, size(EEG.times,2), 5, 0.3, 0, 0, 0);
        pop_rejspec(  EEG, 0, 'elecrange', include ,'threshold',[-50 45;-100 30],'freqlimits',[0 3;20 50],'eegplotcom','','eegplotplotallrej',0,'eegplotreject',0);
        EEG.reject.sum = (EEG.reject.icarejfreq + EEG.reject.icarejconst) > 0;
        pop_select( EEG, 'notrial', find(EEG.reject.sum));
    Run second round ICA on cleaner data
        [EEG.icaweights, EEG.icasphere, EEG.icamods] = runamica15(EEG.data(:,:), ...
            'max_iter', 10000, 'writestep', 500, 'pcakeep', 42, 'do_reject', 1,  ...
            'max_threads', 12, 'rejsig', 4);
    Identify VEM, HEOG and VEOG artifacts and run corrmap again to identify
    Subtract artifacts from EEG
        pop_subcomp( EEG, [VEM HEOG VEOG], 0); % Check this
    Final clean up - re-baseline correct to 100 ms epoch baseline and remove large noisy epochs
        pop_rmbase( EEG, [-100 0]);
        pop_eegthresh(  EEG, 1, [1:64], -90, 90, -1.5, 3, 0, 1);
    Run CSD transformation
        Remove eye channels
        ConvertLocations
        ExtractMontage for CSD
        Check Montage (MapMontage(M))
        Set CSD: [G,H] = GetGH(M, 4);
        Run CSD: CSD(EEG.data(:,:), G, H, 1.0e-5, 10);
                 reshape(EEG.CSDdata, size(EEG.data));