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Updated ERP code
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‎code/preprocessing-eeg/create_mat.m‎

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%
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% Modified on 2024/04/11 to process thrive dataset flanker data
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%
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% This script was created by George Buzzell for the NDC Lab EEG Training
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% Workshop on 02/22. This script uses parts of the "set up" structure from
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% the MADE preprocessing pipeline (Debnath, Buzzell, et. al., 2020)
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clear % clear matlab workspace
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clc % clear matlab command window
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%% Setting up other things
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%Location of MADE and ADJUSTED-ADJUST scripts
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% addpath(genpath([main_dir filesep 'MADE-EEG-preprocessing-pipeline']));% enter the path of the EEGLAB folder in this line
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addpath(genpath('/home/data/NDClab/tools/lab-devOps/scripts/MADE_pipeline_standard/eeg_preprocessing'));% enter the path of the folder in this line
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%Location of "EEG
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% addpath(genpath([main_dir filesep 'eeglab13_4_4b']));% enter the path of the EEGLAB folder in this line
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addpath(genpath('/home/data/NDClab/tools/lab-devOps/scripts/MADE_pipeline_standard/eeglab13_4_4b'));% enter the path of the EEGLAB folder in this line
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%remove path to octave functions inside matlab to prevent errors when
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% rmpath([main_dir filesep 'eeglab13_4_4b' filesep 'functions' filesep 'octavefunc' filesep 'signal'])
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rmpath(['/home/data/NDClab/tools/lab-devOps/scripts/MADE_pipeline_standard/eeglab13_4_4b' filesep 'functions' filesep 'octavefunc' filesep 'signal'])
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%% setup; run this section before any other section below
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%location of analysis folder
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% analysis_dir = '/Users/fzaki001/thrive-theta-ddm';
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analysis_dir = '/home/data/NDClab/analyses/thrive-theta-ddm';
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%location of dataset folder
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% dataset_dir = '/Users/fzaki001/thrive-theta-ddm';
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dataset_dir = '/home/data/NDClab/datasets/thrive-dataset/derivatives/preprocessed/';
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% summary_csv_path = '/Users/fzaki001/thrive-theta-ddm/derivatives/behavior/summary.csv';
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summary_csv_path = '/home/data/NDClab/analyses/thrive-theta-ddm/derivatives/behavior/summary-eeg.csv';
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% Setting up other things
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% 1. Enter the path of the folder that has the data to be analyzed
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data_location = [dataset_dir filesep 'derivatives' filesep 'preprocessed'];
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% 2. Enter the path of the folder where you want to save the postprocessing outputs
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output_location = [analysis_dir filesep 'derivatives' filesep 'preprocessed/erp_check'];
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% 3. this is the correct channel location file BUT INCORRECT PATH!
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% channel_locations = loadbvef('/Users/fzaki001/Downloads/thrive/code/CACS-128-X7-FIXED-64only.bvef');
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channel_locations = loadbvef('/home/data/NDClab/tools/lab-devOps/scripts/MADE_pipeline_standard/eeg_preprocessing/chan_locs_files/electrode_locs_files/CACS-128-X7-FIXED-64only.bvef');
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% %specify parameters of data to process
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%modifying above, to account for files named differently
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%specify parameters of data to process
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task = 'all';
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procStage = 'processed_data';
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visitDirName = 's1_r1'; %visit folder does not list "e1"
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visitFileName = 's1_r1_e1'; %file names include "e1" designation
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% Read files to analyses
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datafile_info=dir([data_location filesep 'sub-*' filesep visitDirName filesep 'eeg' filesep 'sub-*_' task '_eeg_*' procStage '_' visitFileName '.set']);
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datafile_info=datafile_info(~ismember({datafile_info.name},{'.', '..', '.DS_Store'}));
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datafile_names={datafile_info.name};
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datafile_paths={datafile_info.folder};
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[filepath,name,ext] = fileparts(char(datafile_names{1}));
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% Check whether EEGLAB and all necessary plugins are in Matlab path.
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if exist('eeglab','file')==0
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error(['Please make sure EEGLAB is on your Matlab path. Please see EEGLAB' ...
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'wiki page for download and instalation instructions']);
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end
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% Create output folders to save data
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if exist(output_location, 'dir') == 0
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mkdir(output_location)
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end
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%% Count trials
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subjects = [50, 53, 60, 62, 64, 66] % these are just ids to put to the resulting csv, they are not used for computations
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% n_subjects = length(subjects) % this number will be used for loops because the initial subjects list may be changed based on num of trials
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% switch to output directory
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cd(output_location);
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% %create variable names for count trials output and write to disk
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% outputHeader = {'id, s_resp_incon_error, s_resp_incon_corr, ns_resp_incon_error, ns_resp_incon_corr'};
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% dlmwrite(strcat('thrive_trialCounts_respOnly', date, '.csv'), outputHeader, 'delimiter', '', '-append');
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for subject=1:length(datafile_names)
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EEG=[];
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fprintf('\n\n\n*** Processing subject %d (%s) ***\n\n\n', subject, datafile_names{subject});
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%load in raw data that is alread in eeglab (.set) format)
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EEG = pop_loadset( 'filename', datafile_names{subject}, 'filepath', datafile_paths{subject});
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EEG = eeg_checkset(EEG);
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%convert subject name to number
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%note:would be nice to modify line below to not be hard-coded for finding
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%location of subject id. eg, use some combination of strtok instead
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subIdNum = str2double(datafile_names{subject}(5:11));
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%remove all the non-stim-locking markers (should have done already...)
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EEG = pop_selectevent( EEG, 'latency','-.1 <= .1','deleteevents','on');
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EEG = eeg_checkset( EEG );
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% latency
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% duration
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% channel
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% bvtime
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% bvmknum
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% visible
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% type
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% code
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% urevent
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% observation
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% eventType
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% targetDir
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% congruency
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% responded
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% accuracy
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% rt
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% validRt
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% extraResponse
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% validTrial
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% prevTargetDir
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% prevCongruency
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% prevResponded
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% prevAccuracy
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% prevRt
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% prevValidRt
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% prevExtraResponse
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% prevValidTrial
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% nextTargetDir
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% nextCongruency
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% nextResponded
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% nextAccuracy
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% nextRt
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% nextValidRt
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% nextExtraResponse
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% nextValidTrial
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% epoch
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%count how many of each event type (combination of event types) of
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%interest are present
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s_resp_incon_error = length(find( (strcmp({EEG.event.observation}, "s")) & (strcmp({EEG.event.eventType}, "resp")) & (strcmp({EEG.event.congruency}, "i")) & ([EEG.event.accuracy] == 0) & ([EEG.event.responded] == 1) & ([EEG.event.validRt] == 1) ));
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s_resp_incon_corr = length(find( (strcmp({EEG.event.observation}, "s")) & (strcmp({EEG.event.eventType}, "resp")) & (strcmp({EEG.event.congruency}, "i")) & ([EEG.event.accuracy] == 1) & ([EEG.event.responded] == 1) & ([EEG.event.validRt] == 1) ));
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ns_resp_incon_error = length(find( (strcmp({EEG.event.observation}, "ns")) & (strcmp({EEG.event.eventType}, "resp")) & (strcmp({EEG.event.congruency}, "i")) & ([EEG.event.accuracy] == 0) & ([EEG.event.responded] == 1) & ([EEG.event.validRt] == 1) ));
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ns_resp_incon_corr = length(find( (strcmp({EEG.event.observation}, "ns")) & (strcmp({EEG.event.eventType}, "resp")) & (strcmp({EEG.event.congruency}, "i")) & ([EEG.event.accuracy] == 1) & ([EEG.event.responded] == 1) & ([EEG.event.validRt] == 1) ));
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s_stim_incon_corr = length(find( (strcmp({EEG.event.observation}, "s")) & (strcmp({EEG.event.eventType}, "stim")) & (strcmp({EEG.event.congruency}, "i")) & ([EEG.event.accuracy] == 1) & ([EEG.event.responded] == 1) & ([EEG.event.validRt] == 1) ));
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s_stim_con_corr = length(find( (strcmp({EEG.event.observation}, "s")) & (strcmp({EEG.event.eventType}, "stim")) & (strcmp({EEG.event.congruency}, "c")) & ([EEG.event.accuracy] == 1) & ([EEG.event.responded] == 1) & ([EEG.event.validRt] == 1) ));
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ns_stim_incon_corr = length(find( (strcmp({EEG.event.observation}, "ns")) & (strcmp({EEG.event.eventType}, "stim")) & (strcmp({EEG.event.congruency}, "i")) & ([EEG.event.accuracy] == 1) & ([EEG.event.responded] == 1) & ([EEG.event.validRt] == 1) ));
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ns_stim_con_corr = length(find( (strcmp({EEG.event.observation}, "ns")) & (strcmp({EEG.event.eventType}, "stim")) & (strcmp({EEG.event.congruency}, "c")) & ([EEG.event.accuracy] == 1) & ([EEG.event.responded] == 1) & ([EEG.event.validRt] == 1) ));
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%Create the trial counts table for trial counts
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counts_table=table({datafile_names{subject}}, {s_resp_incon_error}, {s_resp_incon_corr}, {ns_resp_incon_error}, {ns_resp_incon_corr}, {s_stim_incon_corr}, {s_stim_con_corr}, {ns_stim_incon_corr}, {ns_stim_con_corr});
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%create variable names for count trials output and write to disk
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counts_table.Properties.VariableNames = {'fileName', 's_resp_incon_error', 's_resp_incon_corr', 'ns_resp_incon_error', 'ns_resp_incon_corr', 's_stim_incon_corr', 's_stim_con_corr', 'ns_stim_incon_corr', 'ns_stim_con_corr'};
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%write/append table to disk
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writetable(counts_table, [output_location filesep 'thrive_trialCounts_RespAndStim_', date, '.csv'], "WriteMode", "append");
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end

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