init

PDToolkit/old

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+%% define a new subject 
+s(1) = PDSubject('/Users/marsman/Documents/Werk/NIC/Teaching/Studenten/Nora_Parigi/data/Subject 5');
+s(2) = PDSubject('/Users/marsman/Documents/Werk/NIC/Teaching/Studenten/Nora_Parigi/data/Subject 4')
+%% load data
+
+s(1) = s(1).loadData();
+s(2) = s(2).loadData();
+
+
+%% define trial markers
+s = s.setPattern('trial start', 'Fixation6s starting');
+s = s.setPatternRelativeToPattern('trial start', 'trial end', +10.5e3); % dependency of trial_start
+
+%s = s.setPattern('trial end',   'Fixation15s starting');
+s = s.setPattern('stimulus onset',  'Stimulus Presentation');
+s = s.setPattern('stimulus offset', 'Fixation15s ending');
+
+s = s.setLabel('information', 'Valence %s');
+s = s.setLabel('information', 'TRIAL_VAR stim %s');
+
+% s = s.setPattern('baseline start');
+% s = s.setPattern('baseline end');
+
+%% parse trials
+s = s.rebuild;
+
+
+% baseline is defined based on minimum value for baseline signal
+
+e = PDExperiment(s, 'Min');
+
+% baseline is defined based on average value for baseline signal
+% e = PDExperiment(s, 'Average');
+
+% calculate baseline corrected and filtered signals
+e = PDExperiment(s, 'Average');
+e = e.preprocess();
+
+
+plot(e); %% plot trials of the experiment
+
+e = build_averages(e);