interpolation fix

Author: DouweHorsthuis

README.md

@@ -101,7 +101,7 @@ After that we use [pop_rejcont](https://github.com/wojzaremba/active-delays/blob
 
 **note** for the Aging group, we use the [pop_rejcont](https://github.com/wojzaremba/active-delays/blob/master/external_tools/eeglab11_0_4_3b/functions/popfunc/pop_rejcont.m) function also right before the ICA. This is because the data was too noisy for more than 50% of the participants to find eye components. 
 
-#### F_interpolate
+#### F_preprocces4
 This script loads a file with all the original channels, deletes the externals and uses these file locations to interpolate the channels of the corresponding's subjects data.  
 In the case of 160 channel data, it uses the [transform_n_channels](https://github.com/CognitiveNeuroLab/Interpolating_160ch_to_64ch_eeglab) function to interpolate the remaining channels not to the original 160, but to 64 channel data so that it is the same as all the other data. For this to work Matlab needs to know the location of 2 things, the trannsform_n_channel.m file and the EEG files called 64.set and 64.fdt.
 

src/B_preprocess1.m

@@ -64,16 +64,15 @@
         end
         %adding channel location
         if EEG.nbchan >63 && EEG.nbchan < 95 %64chan cap (can be a lot of externals, this makes sure that it includes a everything that is under 96 channels, which could be an extra ribbon)
-            EEG=pop_chanedit(EEG, 'lookup',[home_path 'standard-10-5-cap385.elp']); %make sure you put here the location of this file for your computer
-            EEG = pop_saveset( EEG, 'filename',[subject_list{s} '_info.set'],'filepath', data_path);
+            EEG=pop_chanedit(EEG, 'lookup',[home_path 'standard-10-5-cap385.elp']); %make sure you put here the location of this file for your computer  
         elseif EEG.nbchan >159 && EEG.nbchan < 191 %160chan cap
             if isempty(EEG.chanlocs) && EEG.nbchan==160
                 EEG = pop_editset(EEG, 'chanlocs', [home_path 'Cap160_fromBESAWebpage.sfp']); %need to first load any sort of sfp file with the correct channels (the locations will be overwritten to the correct ones later)
             else
-                EEG=pop_chanedit(EEG, 'lookup',[home_path 'Cap160_fromBESAWebpage.sfp']); %make sure you put here the location of this file for your computer
-                EEG = pop_saveset( EEG, 'filename',[subject_list{s} '_info.set'],'filepath', data_path);
+                EEG=pop_chanedit(EEG, 'lookup',[home_path 'Cap160_fromBESAWebpage.sfp']); %make sure you put here the location of this file for your computer  
             end
         end
+        EEG = pop_saveset( EEG, 'filename',[subject_list{s} '_info.set'],'filepath', data_path);
         old_n_chan = EEG.nbchan;
         EEG = clean_artifacts(EEG, 'FlatlineCriterion',5,'ChannelCriterion',0.8,'LineNoiseCriterion',4,'Highpass','off','BurstCriterion','off','WindowCriterion','off','BurstRejection','on','Distance','Euclidian');
         new_n_chan = EEG.nbchan;

src/F_interpolate.m renamed to src/F_preprocces4.m

@@ -5,7 +5,7 @@
 clear variables
 eeglab
 close all
-Group = {'Aging' 'ASD' };%'Control'
+Group = {'Aging' 'ASD'};%'Control'
 name_paradigm = 'restingstate'; % this is needed for saving the table at the end
 for g=1:length(Group)
     switch Group{g}
@@ -20,20 +20,14 @@
             subject_list = {'12022' '12023' '12031' '12081' '12094' '12188' '12255' '12335' '12339' '12362' '12364' '12372' '12376' '12390' '12398' '12407' '12408' '12451' '12454' '12457' '12458' '12459' '12468' '12478' '12498' '12510' '12517' '12532' '12564' '12631' '12633' '12634' '12636' '12665' '12670' '12696' '12719' '12724' '12751' '12763' '12769' '12776' '12790' '12806' '12814' '12823' '12830' '12847' '12851' '12855' '12856' '12857' '12859' '12871' '12872' '12892'};
     end
 
-    participant_badchan = string(zeros(length(subject_list), 2)); %prealocationg space for speed
+    participant_badchan = string(zeros(length(subject_list), 5)); %prealocationg space for speed
     for s=1:length(subject_list)
         fprintf('\n******\nProcessing subject %s\n******\n\n', subject_list{s});
         clear labels_all labels_good lables_del data_subj
         data_path  = [home_path subject_list{s} ''];% Path to the folder containing the current subject's data
         % Load original dataset
         fprintf('\n\n\n**** %s: Loading dataset ****\n\n\n', subject_list{s});
         EEGinter = pop_loadset('filename', [subject_list{s} '_info.set'], 'filepath', data_path);%loading participant file with 64 channels
-        %For the aging 
-        if strcmp(Group{g},'Aging') && EEGinter.nbchan==160 && isempty(EEGinter.chanlocs)
-            EEGinter = pop_editset(EEGinter, 'chanlocs', [home_path 'Cap160_fromBESAWebpage.sfp']); %need to first load any sort of sfp file with the correct channels (the locations will be overwritten to the correct ones later)
-        elseif strcmp(Group{g},'Aging') && EEGinter.nbchan==64 && isempty(EEGinter.chanlocs)
-             EEGinter = pop_editset(EEGinter, 'chanlocs', [home_path 'BioSemi64.sfp']); %need to first load any sort of sfp file with the correct channels (the locations will be overwritten to the correct ones later)
-        end
         %saving the original amount of total channels
         labels_all = {EEGinter.chanlocs.labels}.'; %stores all the labels in a new matrix
         %interpolating the 160channels to 64 channels
@@ -57,16 +51,16 @@
             disp(EEG.nbchan); %writes down how many channels are there
             EEG = pop_interp(EEG, EEGinter.chanlocs, 'spherical');%interpolates the data
         end
-        clear EEG_temp EEGinter
         EEG = eeg_checkset( EEG );
         EEG = pop_saveset( EEG, 'filename', [subject_list{s} '_inter.set'], 'filepath', data_path); %saves data
         disp(EEG.nbchan)
         %this part saves all the bad channels + ID numbers
         lables_del                 = setdiff(labels_all,labels_good); %only stores the deleted channels
         All_bad_chan               = strjoin(lables_del); %puts them in one string rather than individual strings
         ID                         = string(subject_list{s});%keeps all the IDs
-        data_subj                  = [ID, All_bad_chan]; %combines IDs and Bad channels
+        data_subj                  = [ID, length(lables_del),EEGinter.nbchan, All_bad_chan, EEG.nbchan]; %combines IDs and Bad channels, total channels at the end
         participant_badchan(s,:)   = data_subj;%combine new data with old data
+        clear EEG_temp EEGinter
     end
     save([home_path name_paradigm '_participant_interpolation_info'], 'participant_badchan');
 end