This tutorial shows you how to process EEG and ERP data using ERPLAB Classic, which is an EEGLAB plugin. We have a separate tutorial for ERPLAB Studio, a standalone program that provides a more intuitive and easy-to-use interfact to the same underlying EEGLAB and ERPLAB functions.

In this tutorial, we provide step-by-step instructions for processing a simple data set. The goal will be to view and measure ERPs from each subject, from the provided simple EEG datasets.

More documentation is provided for specific functions in the ERPLAB User Manual.

• Getting Started, Loading an EEG dataset
  
• Attaching an EventList
  
• Assigning trials to bins
  
• Extract bin-based EEG Epochs
  
• Artifact detection
  
• Creating Averaged ERPs
  
  

• ERP Viewer tool
• Plotting ERPs
• Measuring ERPs
• Viewing data quality measures
  
  

• Combining subjects in to Grand Averages
  
• Combining bins for diff waves with Bin Ops
  
• Combining channels with Chan Ops, channel labels
  
• Filtering, on EEG sets and ERP sets
  
• Typical pipelines, order-of-processing, and scripting
  
  
  

The EEG data saved from a subject in an experiment is typically 'continuous EEG' - that is, EEG data that is arranged in a format of (number of electrodes) * (number of time-points). When running ERP experiment, we often wish to compare the event-related potential in response to one event compared to another - perhaps rarely-shown stimulus compared to frequently-shown stimulus for a P300 experiment. To get from continuous EEG to plotting and measuring ERPs, several steps are necessary:

We need to know when the events occurred within the time course of the EEG data. For this we construct an EventList structure. This has a list of what events occurred when, and in a way that we can edit, and group events in to Bins.

For your analysis, different sets of trials/events may need be grouped together for different comparisons. In this tutorial example experiment, we want to group together trials with frequent stimuli (indicated with event codes of {11,122,22,111}) and also group together trials that had rare stimuli (indicated with event codes of {21,112,12,121}).

ERPLAB has flexible tools for assigning event to bins, including Binlister which allows detailed specification of bin event criteria.

With an Eventlist and bin-criteria, the continuous EEG can be extracted to bin-based epochs. Epochs are short stretches of EEG data, perhaps 1 second long. Epochs will be anchored around specific event markers, with some time before and after. Rather than the previous continuous EEG data stored in the format of

(number of electrodes) * (number of time-points)

epoched EEG data will now be stored in the format of

(number of electrodes) * (number of time-points in epoch) * (number of epochs/trials)

From this bin-epoched EEG set, we create a new structure that explicitly has the averaged ERP. Averaging each bin in the above bin-epoched EEG data give us ERP data in the format:

(number of electrodes) * (number of time-points in epoch) * (number of bins)

With the data prepared in this ERP set, we can access and plot the data from each condition:

Tutorial list

Getting Started, loading EEG data