New

README.md

@@ -177,27 +177,24 @@ We delete a channel if
 
 All of these settings are the standard settings and result in clean data, without losing excessive amount of channels.  
 
-**imporant for now**  
+**important for now**  
 Even though for now we cannot exclude externals from the cleaning process, and thus we need to delete them beforehand. [The EEGLAB people have said that they are working on a fix base on my request](https://github.com/sccn/clean_rawdata/issues/28). Currently (when manually updating the function) there are still errors when excluding externals from this cleaning, but hopefully quick this will be solved. So if you need to use externals, use the old cleaning functions, this one is still in the code. 
 
 
 
 These are the variables you NEED to change:
 ```matlab
 subject_list = {'some sort of ID' 'a different id for a different particpant'}; 
-eeglab_location = 'C:\Users\wherever\eeglab2019_1\'; %needed if using a 10-5-cap
+eeglab_location = 'C:\Users\wherever\eeglab2021.1\'; %needed if using a 10-5-cap
 scripts_location = 'C:\\Scripts\'; %needed if using 160channel data
 home_path  = 'the main folder where you store your data';
 ```
 
 These you can change if you want to change settings
 ```matlab
-EEG = pop_resample( EEG, 256); %downsampling
-EEG = pop_eegfiltnew(EEG, [],1,1690,1,[],1); % High pass filter
-EEG = pop_eegfiltnew(EEG, [],45,152,0,[],1); % Low  pass filter
-EEG = pop_chanedit(EEG, 'lookup',[eeglab_location 'plugins\dipfit\standard_BESA\standard-10-5-cap385.elp']); 
-EEG = pop_select( EEG,'nochannel',{'EXG1','EXG2','EXG3','EXG4','EXG5','EXG6','EXG7','EXG8'});% To delete different channels if needed 
-EEG = pop_rejchan(EEG,'elec', [1:64],'threshold',5,'norm','on','measure','kurt'); %the rejection threshold (standard is 5), [1:64 or 1:160 because you don't want to include the externals]
+downsample_to=256; % what is the sample rate you want to downsample to
+lowpass_filter_hz=45; %45hz filter
+highpass_filter_hz=1; %1hz filter
 ```  
 [Back to top](#eeg-pipeline-using-eeglab)  
 
@@ -216,7 +213,9 @@ This shows up in Matlab. Replace the filter number with the number 1. followed b
 ```matlab
 EEG = pop_eegfiltnew(EEG, [],0.01,168960,1,[],1); %this 0.01hz filter changes like this: 
 EEG = pop_eegfiltnew(EEG, [],1,1690,0,[],1); %into a 1 hz filter
-```
+```  
+
+**3/1/2022 update, we won't need to add filter order anymore**. It is very important to know the filter order (which is [ the width of the sliding window in data points](https://sccn.ucsd.edu/wiki/Makoto's_preprocessing_pipeline#Dependency_across_the_preprocessing_stages_.2807.2F05.2F2019_updated.29) or [see this EEGLAB information about this](https://eeglab.org/others/Firfilt_FAQ.html#q-what-is-the-difference-between-filter-length-and-filter-order))
 
 ##### What filter should I choose
 Choosing what filters to use will have a big impact on your data. There are a couple things to consider because filters will have impact in several different ways on your data. 

src/A_merge_sets.m

@@ -1,17 +1,10 @@
 % EEGLAB merge sets, and creates .set file
-% by Douwe Horsthuis updated on 12/22/2021
+% by Douwe Horsthuis updated on 6/21/2021
 % ------------------------------------------------
-clear variables
-eeglab
-%% Subject info for each script
-% This defines the set of subjects
-subject_list = {'some sort of ID' 'a different id for a different particpant'};
-% Path to the parent folder, which contains the data folders for all subjects
-home_path  = 'the main folder where you store your data';
-%% info needed for this script specific
+subject_list = {'some sort of ID' 'a different id for a different particpant'}; %all the IDs for the indivual particpants
 filename     = 'the_rest_of_the_file_name'; % if your bdf file has a name besides the ID of the participant (e.g. oddball_paradigm)
+home_path    = 'path_where_to_load_in_pc'; %place data is (something like 'C:\data\')
 blocks       = 5; % the amount of BDF files. if different participant have different amounts of blocks, run those participant separate
-%% Loop through all subjects
 for s = 1:length(subject_list)
     clear ALLEEG
     eeglab

src/B_downs_filter_chaninfo_exclchan.m

@@ -1,45 +1,40 @@
 % Combination of EEGLAB downsample and filter, and reject channel script by Ana on 2017-07-11
-% Combined and updated by Douwe Horsthuis last updated on 2/14/2022
+% Combined and updated by Douwe Horsthuis last update 11/5/2021
 % ------------------------------------------------
-clear variables
-eeglab
-%% Subject info for each script
+
 % This defines the set of subjects
 subject_list = {'some sort of ID' 'a different id for a different particpant'};
+eeglab_location = 'C:\Users\wherever\eeglab2021.1\'; %needed if using a 10-5-cap
+scripts_location = 'C:\\Scripts\'; %needed if using 160channel data
 % Path to the parent folder, which contains the data folders for all subjects
 home_path  = 'the main folder where you store your data';
-%% info needed for this script specific
-%locations
-eeglab_location = 'C:\Users\wherever\eeglab2021.1\'; %needed if using a 10-20
-scripts_location = 'C:\\Scripts\'; %needed if using 160channel data
-% filter info
 downsample_to=256; % what is the sample rate you want to downsample to
 lowpass_filter_hz=45; %45hz filter
-lowpass_filter_order=152;%this is the suggested value produced by EEGlab
 highpass_filter_hz=1; %1hz filter
-highpass_filter_order=1690;%this is the suggested value produced by EEGlab
-%% Loop through all subjects
+% Loop through all subjects
 for s=1:length(subject_list)
     fprintf('\n******\nProcessing subject %s\n******\n\n', subject_list{s});
     data_path  = [home_path subject_list{s} '\\'];
     % Load original dataset (created by previous script)
     fprintf('\n\n\n**** %s: Loading dataset ****\n\n\n', subject_list{s});
     EEG = pop_loadset('filename', [subject_list{s} '.set'], 'filepath', data_path);
     EEG = eeg_checkset( EEG );
+    %getting some basic info before pre-processing (avg ampl 3x, length in sec, channels
+    EEG.info=table(mean(EEG.data(33,:)), mean(EEG.data(48,:)), mean(EEG.data(28,:)), EEG.xmax, {{EEG.chanlocs.labels}},  'VariableNames',{'Avg Ampl FPz', 'Avg Ampl Cz', 'Avg Ampl Iz', 'full amount of time in sec', 'channels'},'RowNames',{'Before pre-processing'}); %creating table with column names);
+    EEG.subject = subject_list{s};
     %downsample
     EEG = pop_resample( EEG, downsample_to);
     EEG = eeg_checkset( EEG );
     %filtering
-    EEG.filter=table(lowpass_filter_hz,lowpass_filter_order,highpass_filter_hz,highpass_filter_order); %adding it to subject EEG file
-    EEG = pop_eegfiltnew(EEG, [],highpass_filter_hz,highpass_filter_order,1,[],1); % 1hz filter
+    EEG.filter=table(lowpass_filter_hz,highpass_filter_hz); %adding it to subject EEG file
+    EEG = pop_eegfiltnew(EEG, 'locutoff',highpass_filter_hz);
     EEG = eeg_checkset( EEG );
-    EEG= pop_eegfiltnew(EEG, [],lowpass_filter_hz,lowpass_filter_order,0,[],1); 
+    EEG = pop_eegfiltnew(EEG, 'hicutoff',lowpass_filter_hz);
     EEG = eeg_checkset( EEG );
     EEG = pop_saveset( EEG, 'filename',[subject_list{s} '_downft.set'],'filepath', data_path);
     %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',[eeglab_location 'plugins\dipfit\standard_BESA\standard-10-5-cap385.elp']); %make sure you put here the location of this file for your computer
-        EEG=pop_chanedit(EEG, 'lookup',[eeglab_location 'plugins\dipfit\standard_BEM\elec\standard_1020.elc']); %make sure you put here the location of this file for your computer
+        EEG=pop_chanedit(EEG, 'lookup',[eeglab_location 'plugins\dipfit\standard_BESA\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);
         %deleting bad channels
         %EEG = pop_rejchan(EEG,'elec', [1:64],'threshold',5,'norm','on','measure','kurt');

src/D_reref_exclextrn_interp_avgref_ica_autoexcom.m

@@ -4,20 +4,18 @@
 % uses runica to do an Independent Component Analysis
 % uses IClabel to define the eye component
 % Deletes these and the components also get printed.
-% by Douwe Horsthuis updated on 12/22/2021
+% last edits done on by Douwe 11/5/2021
 % ------------------------------------------------
+
 clear variables
-eeglab
-%% Subject info for each script
+
 % This defines the set of subjects
 subject_list = {'some sort of ID' 'a different id for a different particpant'};
 % Path to the parent folder, which contains the data folders for all subjects
-home_path  = 'the main folder where you store your data';
-%% info needed for this script specific
+home_path  = 'the main folder where you store all the data';
 figure_path = 'the main folder where you store all the ic figures';
 components = num2cell(zeros(length(subject_list), 8)); %prealocationg space for speed
 refchan = { }; %if you want to re-ref to a channel add the name of the channel here, if empty won't re-ref to any specific channel (for example {'EXG3' 'EXG4'} or {'Cz'})
-%% Loop through all subjects
 for s=1:length(subject_list)
     fprintf('\n******\nProcessing subject %s\n******\n\n', subject_list{s});
     % Path to the folder containing the current subject's data

src/E_epoching.m

@@ -6,20 +6,18 @@
 % it can also record the RTs and put them in and excel, but it needs folder after the homepath called \All RT files\
 clear variables
 eeglab
-%% Subject info for each script
 % This defines the set of subjects
-subject_list = {'some sort of ID' 'a different id for a different particpant'};
-% Path to the parent folder, which contains the data folders for all subjects
-home_path  = 'the main folder where you store your data';
-%% info needed for this script specific 
+subject_list = {'some sort of ID' 'a different id for a different particpant'}; 
 name_paradigm = 'name'; % this is needed for saving the table at the end
 %participant_info_temp = []; % needed for creating matrix at the end
+% Path to the parent folder, which contains the data folders for all subjects
+home_path  = 'the main folder where you store your data\';
 binlist_location = 'the folder where you stored your binlist\'; %binlist should be named binlist.txt
 epoch_time = [-50 400];
 baseline_time = [-50 0];
 n_bins=3;% enter here the number of bins in your binlist
 participant_info_temp = string(zeros(length(subject_list), 2+n_bins)); %prealocationg space for speed
-%% Loop through all subjects
+% Loop through all subjects
 for s=1:length(subject_list)
     fprintf('\n******\nProcessing subject %s\n******\n\n', subject_list{s});
     clear data_subj

testing/scripts/A_merge_sets.m

@@ -1,9 +1,17 @@
-% Testing the scr code 6/21/2021
+% EEGLAB merge sets, and creates .set file
+% by Douwe Horsthuis updated on 2/22/2022
 % ------------------------------------------------
-subject_list = {'11' '14'}; %all the IDs for the indivual particpants
-filename     = 'IAPS'; % if your bdf file has a name besides the ID of the participant (e.g. oddball_paradigm)
-home_path    = 'C:\Users\dohorsth\Documents\GitHub\EEG_to_ERP_pipeline_stats_R\testing\data\'; %place data is (something like 'C:\data\')
-blocks       = 2; % the amount of BDF files. if different participant have different amounts of blocks, run those participant separate
+clear variables
+eeglab
+%% Subject info for each script
+% This defines the set of subjects
+subject_list = {'12377' '12494' '12565' '12666' '12675'};
+% Path to the parent folder, which contains the data folders for all subjects
+home_path  = 'D:\Restingstate_eyetracking\';
+%% info needed for this script specific
+filename     = 'rest_et'; % if your bdf file has a name besides the ID of the participant (e.g. oddball_paradigm)
+blocks       = 3; % the amount of BDF files. if different participant have different amounts of blocks, run those participant separate
+%% Loop through all subjects
 for s = 1:length(subject_list)
     clear ALLEEG
     eeglab
@@ -23,6 +31,9 @@
         %since there are more than 1 files, they need to be merged to one big .set file.
         EEG = pop_mergeset( ALLEEG, 1:blocks, 0);
     end
+    %adding info to the EEG structure
+    EEG.subject = subject_list{s}; %subject ID
     %save the bdf as a .set file
+
     EEG = pop_saveset( EEG, 'filename',[subject_list{s} '.set'],'filepath',data_path);
 end