add excluded channels back to data after preprocessing

gui/mainGUI.m

@@ -929,6 +929,7 @@ function createbutton_Callback(hObject, eventdata, handles)
 
     handles.params.ChannelReductionParams.tobeExcludedChans = ...
         str2num(get(handles.excludeedit, 'String'));
+    handles.params.ChannelReductionParams.readdExcludedChans = true; % hard coded for now!
 else
     handles.params.ChannelReductionParams = struct([]);
 end

preprocessing/RecommendedParameters.m

@@ -77,7 +77,8 @@
 
         DetrendingParams = struct();
 
-        ChannelReductionParams = struct('tobeExcludedChans', []);
+        ChannelReductionParams = struct('tobeExcludedChans', [], ...
+                                        'readdExcludedChans', false);
 
 
         EEGSystem = struct('name', 'Others',...

preprocessing/performETguidedICA.m

@@ -1,4 +1,4 @@
-function [EEG] = performETguidedICA(EEG, params)
+function [EEG, ET] = performETguidedICA(EEG, params)
 
 % For details see the underlying publication: Dimigen, 2020, NeuroImage
 
@@ -116,7 +116,12 @@
 % % 
 % EEG = pop_detecteyemovements(EEG,[LX LY],[RX RY],THRESH,MINDUR,DEG_PER_PIXEL,SMOOTH,0,25,2,PLOTFIG,WRITESAC,WRITEFIX);
 
-%% Create optimized data for ICA training (OPTICAT, Dimigen, 2018)
+%% keep ET data for reattaching it at the end of the preprocessing stream
+nbchan = length(ETparams.sync.importColumns);
+ET = EEG;
+ET.data = ET.data(end-nbchan+1:end, :); % keep only ET data
+ET.nbchan = nbchan;
+ET.chanlocs = ET.chanlocs(end-nbchan+1:end);
 
 OW_PROPORTION    = 1.0;          % overweighting proportion
 SACCADE_WINDOW   = [str2double(params.from_edit) str2double(params.to_edit)];  % time window to overweight (-20 to 10 ms is default)

preprocessing/performICLabel.m

@@ -1,4 +1,4 @@
-function EEG = performICLabel(EEG, varargin)
+function [EEG, ET] = performICLabel(EEG, varargin)
 % performICLabel  perform Independent Component Analysis (ICA) on the high
 %   passsed EEG and classifies bad components using ICLabel.
 %   This function applies a high pass filter before the ICA. But the output
@@ -114,8 +114,9 @@
 EEG_orig.automagic.iclabel.ETguidedICA.performed = 'no';
 try
     if ETguidedICA 
-        [~, EEG] = evalc('performETguidedICA(EEG, addETdataParams)');
-        EEG.data = EEG.data(1:size(EEG_orig.data, 1), :); % remove ET data
+        [~, EEG, ET] = evalc('performETguidedICA(EEG, addETdataParams)');
+        % remove ET data
+        EEG.data = EEG.data(1:size(EEG_orig.data, 1), :);
         EEG.nbchan = EEG_orig.nbchan;
         EEG.chanlocs = EEG_orig.chanlocs;
         EEG_orig.automagic.iclabel.ETguidedICA.performed = 'yes';
@@ -125,6 +126,10 @@
     fprintf('\n ET guided ICA skipped. Continue with the standard ICA... \n')
 end
 
+if ~exist('ET','var')
+    ET = [];
+end
+
 %% Run ICA
 [~, EEG, ~] = evalc('pop_runica(EEG, ''icatype'',''runica'',''chanind'',EEG.icachansind)');
 

preprocessing/preprocess.m

@@ -129,7 +129,6 @@
     ICLabelParams.addETdataParams = p.Results.addETdataParams;
 end
 
-
 if isempty(Settings)
     Settings = Recs.Settings;
 end
@@ -144,12 +143,20 @@
 
 data_orig = data; % for plot with original data
 
-% Set system dependent parameters and eeparate EEG from EOG
-[EEG, EOG, EEGSystem, MARAParams] = ...
+% Set system dependent parameters and separate EEG from EOG
+[EEG, EOG, EXCLUDED, EEGSystem, MARAParams] = ...
     systemDependentParse(data, EEGSystem, ChannelReductionParams, ...
     MARAParams, ORIGINAL_FILE);
 EEGRef = EEG;
 
+% free memory if EXCLUDED channel data is not supposed to be reattached
+% later
+if ~isempty(ChannelReductionParams)
+    if ~ChannelReductionParams.readdExcludedChans
+        clear EXCLUDED
+    end
+end
+
 % Trim data
 EEG.automagic.TrimData.performed = 'no';
 if isfield(TrimDataParams, 'changeCheck')
@@ -305,7 +312,7 @@
 EEG.automagic.iclabel.performed = 'no';
 if ( ~isempty(ICLabelParams) )
     try
-        EEG = performICLabel(EEG, ICLabelParams);
+        [EEG, ET] = performICLabel(EEG, ICLabelParams);
         EEG.icachansind = find(~EEG.automagic.preprocessing.removedMask);
     catch ME
         message = ['ICLabel is not done on this subject, continue with the next steps: ' ...
@@ -413,14 +420,41 @@
     clear chan_nb re_chan;
 end
 
-% Write back output
+% Write back output (ref channel)
 if ~isempty(EEGSystem.refChan)
     removedChans(removedChans >= EEGSystem.refChan.idx)=removedChans(removedChans >= EEGSystem.refChan.idx)+1;
     EEG.automagic.autoBadChans = removedChans;
 
 else
     EEG.automagic.autoBadChans = removedChans;
 end
+
+% Put back excluded channels (only if wanted)
+if ~isempty(EEG.automagic.channelReduction.params)
+    if (EEG.automagic.channelReduction.params.readdExcludedChans && ...
+            ~isempty(EEG.automagic.channelReduction.excludedChannels))
+        excludedChans = sort(EEG.automagic.channelReduction.excludedChannels); % should be ordered (for step below)
+        for i_ch_excl = 1:length(excludedChans)
+            excluded_chan = excludedChans(i_ch_excl);
+            EEG.data = [EEG.data(1:excluded_chan-1,:); ...
+                EXCLUDED.data(i_ch_excl,:);...
+                EEG.data(excluded_chan:end,:)];
+            EXCLUDED.chanlocs(i_ch_excl).maraLabel = [];
+            EEG.chanlocs = [EEG.chanlocs(1:excluded_chan-1), ...
+                EXCLUDED.chanlocs(i_ch_excl), ...
+                EEG.chanlocs(excluded_chan:end)];
+        end
+        EEG.nbchan = size(EEG.data,1);
+        clear excluded_chan i_ch_excl
+
+        % Write back output (excluded channels)
+        for excluded_chan = excludedChans
+            removedChans(removedChans >= excluded_chan)=removedChans(removedChans >= excluded_chan)+1;
+        end
+    end
+end
+EEG.automagic.autoBadChans = removedChans;
+
 EEG.automagic.params = params;
 EEG.automagic = rmfield(EEG.automagic, 'preprocessing');
 
@@ -429,6 +463,26 @@
    allSteps.EEGFinal = EEG;
 end
 
+% attach Eyetracker data (if wanted)
+addETdata = true;
+EEG.automagic.channelReduction.params.addETdata = addETdata; % hard coded for now
+%addETevents = true; % might be seperately set, if preferred
+if exist('ET', 'var')
+    if ~isempty(ET) && EEG.automagic.channelReduction.params.addETdata
+        EEG.data = [EEG.data; ET.data]; % add to the very end, such that it doesnt affect any index
+        f = fieldnames(ET.chanlocs);
+        toKeep = fieldnames(EEG.chanlocs);
+        toRemove = f(~ismember(f,toKeep));
+        EEG.chanlocs = [EEG.chanlocs, rmfield(ET.chanlocs, toRemove)];
+        EEG.nbchan = size(EEG.data,1);
+%    end
+%    if ~isempty(ET) && addETevents
+        EEG.event = ET.event;
+        EEG.urevent = ET.urevent;
+        %EEG.eventdescription = ET.eventdescription;
+    end
+end
+
 %% Creating the final figure to save
 
 %%% Find the colormap selected
@@ -491,6 +545,8 @@
 else
     final_idx = 1:size(EEG.data, 1);
 end
+% only keep original EEG channels (no ET, no excluded channels)
+final_idx = final_idx(ismember(final_idx, EEG.automagic.channelReduction.usedEEGChannels));
 
 %eeg figure
 subplot(13,1,2:3)
@@ -726,6 +782,9 @@
 else
     final_idx = 1:size(EEG.data, 1);
 end
+% only keep original EEG channels (no ET, no excluded channels)
+final_idx = final_idx(ismember(final_idx, EEG.automagic.channelReduction.usedEEGChannels));
+
 fig2 = figure('visible', 'off');
 ax = gca;
 % outerpos = ax.OuterPosition;

preprocessing/systemDependentParse.m

@@ -1,4 +1,4 @@
-function [EEG, EOG, EEGSystem, MARAParams] = ...
+function [EEG, EOG, EXCLUDED, EEGSystem, MARAParams] = ...
                         systemDependentParse(EEG, EEGSystem, ...
                         ChannelReductionParams, MARAParams, ORIGINAL_FILE) %#ok<INUSD>
 % systemDependentParse parse EEG input depending on the EEG system.
@@ -449,9 +449,13 @@
     clear all_chans;
 end
 
+% Store excluded channel data for later retrieval
+[~, EXCLUDED] = evalc('pop_select( EEG , ''channel'', tobeExcludedChans)');
+
 % Seperate EEG channels from EOG channels
 [~, EOG] = evalc('pop_select( EEG , ''channel'', eog_channels)');
 [~, EEG] = evalc('pop_select( EEG , ''channel'', eeg_channels)');
+
 % Map original channel lists to new ones after the above separation
 if ~isempty(EEGSystem.refChan)
     [~, idx] = ismember(EEGSystem.refChan.idx, eeg_channels);
@@ -463,6 +467,7 @@
 if chanSize(2) == 1
     EEG.chanlocs = EEG.chanlocs';
     EOG.chanlocs = EOG.chanlocs';
+    EXCLUDED.chanlocs = EXCLUDED.chanlocs';
 end
 clear chanSize;
 

src/Block.m

@@ -528,8 +528,17 @@ function excludeChannelsFromRBC(self, exclude_chans)
             if(isempty(EEG))
                 return;
             end
+            % index EEG channels for quality asssessment
+            eeg_chans = 1:EEG.nbchan;
+            if isfield(EEG.automagic, 'channelReduction')
+                if EEG.automagic.channelReduction.params.readdExcludedChans % in this case take original eeg indices. ET is also excluded by default
+                    eeg_chans = EEG.automagic.channelReduction.usedEEGChannels;
+                elseif EEG.automagic.channelReduction.params.addETdata % in this case, original eeg indices dont work, but we have to excluce the ET channels at the end
+                    eeg_chans = 1:EEG.nbchan-6; % hard coded for now
+                end
+            end
             rating_badchans = [];
-            qScore  = calcQuality(EEG, rating_badchans, ...
+            qScore  = calcQuality(EEG, eeg_chans, rating_badchans, ...
                 self.project.qualityThresholds); 
             qScoreIdx.OHA = arrayfun(@(x) ceil(length(x.OHA)/2), qScore);
             qScoreIdx.THV = arrayfun(@(x) ceil(length(x.THV)/2), qScore);
@@ -610,29 +619,43 @@ function interpolate(self)
                 InterpolationParams = self.params.InterpolationParams;
             end
 
-            %save old ica data which gets corrupted in eeg_interp method:
-            orig_icasphere=EEG.icasphere;
-            orig_icachansind=EEG.icachansind;
-            orig_icaweights=EEG.icaweights;
-            orig_icawinv=EEG.icawinv;
+            % to avoid excluded misc and ET channels going into the interpolation,
+            % we also let the misc channels be interpolated (temporarily).
+            % draw info from automagic params
+            EEGtoInterp = EEG;
+            misc_chans = [];
+            if isfield(automagic, 'channelReduction')
+                usedEEGChannels = automagic.channelReduction.usedEEGChannels;
+                %misc_chans = [1:EEG.nbchan];
+                misc_chans = find(~cellfun('isempty', { EEGtoInterp.chanlocs.theta })); % only those with loc info, as others are ignored by interpolation function anyway..
+                misc_chans = misc_chans(~ismember(misc_chans, usedEEGChannels));
+            end
+
+            % do interpolation
             if size(EEG.data,1)==length(interpolate_chans)
                 disp('All channels are bad. Skipping interpolation...');
                 filenamE = strsplit(EEG.comments,filesep);
                 filenamE = filenamE{end};
                 automagic.error_msg = ['Interpolation skipped because all channels are bad: ',filenamE];
             else
-                EEG = eeg_interp(EEG ,interpolate_chans , InterpolationParams.method);
+                EEGtoInterp = eeg_interp(EEGtoInterp ,[interpolate_chans misc_chans], InterpolationParams.method);
             end
-			%put the original icadata back into the structure
-            EEG.icasphere=orig_icasphere;
-            EEG.icachansind=orig_icachansind;
-            EEG.icaweights= orig_icaweights;
-            EEG.icawinv=orig_icawinv;
+            % now add only the interpolated EEG channels back to EEG struct
+            EEG.data(interpolate_chans,:) = EEGtoInterp.data(interpolate_chans,:);
 
             rating_badchans = unique([self.finalBadChans interpolate_chans]);
             rating_badchans = setdiff(rating_badchans, ...
                                 self.project.manuallyExcludedRBCChans);
-            qScore  = calcQuality(EEG, rating_badchans, ...
+            % index EEG channels for quality asssessment
+            eeg_chans = 1:EEG.nbchan;
+            if isfield(automagic, 'channelReduction')
+                if automagic.channelReduction.params.readdExcludedChans % in this case take original eeg indices. ET is also excluded by default
+                    eeg_chans = automagic.channelReduction.usedEEGChannels;
+                elseif automagic.channelReduction.params.addETdata % in this case, original eeg indices dont work, but we have to excluce the ET channels at the end
+                    eeg_chans = [1:EEG.nbchan-6]; % hard coded for now
+                end
+            end
+            qScore  = calcQuality(EEG, eeg_chans, rating_badchans, ...
                 self.project.qualityThresholds);
             qScoreIdx.OHA = arrayfun(@(x) ceil(length(x.OHA)/2), qScore);
             qScoreIdx.THV = arrayfun(@(x) ceil(length(x.THV)/2), qScore);

src/calcQuality.m

@@ -1,4 +1,4 @@
-function Q = calcQuality(EEG, bad_chans, varargin)
+function Q = calcQuality(EEG, eeg_chans, bad_chans, varargin)
 % Calculates quality measures of a dataset based on the following metrics:
 %
 % -  The ratio of data points that exceed the absolute value a certain
@@ -61,8 +61,13 @@
     disp('No bad channel information...')
 end
 %% Data preparation
-% Data
+% only rate data that was actually prepocessed (without excluded and
+% readded channels, or added ET channels)
+
+% remove readded EXCLUDED and ET channels from data (have to remove it from EEG, as calcCHV uses it)
+EEG.data = EEG.data(eeg_chans,:); % i think its not necessary to shift around bad_chans indices, as they are not used specifically?!
 X = EEG.data;
+
 % Get dimensions of data
 t = size(X,2);
 c = size(X,1);