Basic ERPLAB Processing Steps

This section provides an outline of the typical sequence of operations for analyzing an ERP experiment using the combination of EEGLAB and ERPLAB.  The details will be found in later sections, but it is useful to have an overview of the whole process.

1.     Import an EEG file into EEGLAB, where it becomes a dataset. Once you have imported the raw EEG, you should view it with Plot > Channel data (scroll) to make sure everything looks OK.  The original EEG file can come from one of the many different commercial EEG recording systems supported by EEGLAB (including Neuroscan, EGI, and Biosemi; see the EEGLAB documentation for the supported file types.)  The ERPSS RAW format is supported by EEGLAB but apparently does not work well at this time.  Any of the EEGLAB functions that operate on continuous data (e.g., filtering the data, ICA-based artifact correction) can be applied at this point.

2.     There are several EEGLAB routines that you may wish to run at this point (or after epoching).  For example, if you wish to filter the EEG, you can select Tools > Filter the data.  Alternatively you may wish to use ERPLABÕs filter routines (see ERPLAB > Filter & Frequency Tools), which we think are better for most conventional ERP applications.  You may also wish to enter electrode location coordinates at this point (which will be useful later for topographic mapping).  This can be accomplished with Edit > Channel locations, which allows you to automatically choose standard locations on the basis of the electrode names (or enter custom coordinates).

3.     Create the EVENTLIST structure from the current dataset using ERPLAB > EventList > Create EEG EventList (basic or advanced). The EVENTLIST structure will ordinarily be attached to the EEG structure.  It stores information about ERPLABÕs event processing and bin assignments. It can also be saved as a text file, allowing you to insert, modify, or delete events and then import the new events back into the dataset.  At this point, you can assign text labels for each numeric event code (or assign numeric event codes if your datafile contains text labels instead of numeric codes).  You can even assign bins for the events if there is a simple 1:1 mapping between event codes and bins.

4.     If you need to specify a more complex mapping between events and bins, you will do this using ERPLAB > Assign Bins (BINLISTER). This involves creating a Bin Descriptor File (BDF), a text file that provides an abstract description of the events that will be averaged together (just as in ERPSS).  For example, you can specify that Bin 3 will consist of targets that were preceded by a nontarget and followed 200-1500 ms later by a left-hand button-press response.  This step can also be configured to extract reaction times, which are saved in the bdf field of the EVENTLIST structure and can be exported to a text file with ERPLAB > EventList > Export Reaction Times to Text from EEG.

5.     Convert the continuous EEG data in the dataset into a set of fixed-length epochs around each event using ERPLAB > Extract Bin-Based Epochs. (Note that this differs from EEGLABÕs Tools > Extract epochs function in several ways, so you should not use the EEGLAB epoching function in conjunction with ERPLAB.)  Any of the EEGLAB functions that operate on epoched data can be applied at this point.

6.     Perform artifact detection on the epoched dataset, marking problematic EEG segments so they can be excluded during the averaging process. Prior to artifact detection, you may wish to create new channels in the dataset (e.g., a bipolar HEOG channel from separate HEOG-left and HEOG-right channels).  This is accomplished with ERPLAB > EEG Channel Operations.  After you have performed artifact detection, you can use Plot > Channel data (scroll) to see which epochs have been marked for rejection and to manually mark and unmark specific epochs.  You can, of course, use EEGLABÕs ICA-based artifact correction instead of, or in addition to, artifact rejection.  EEGLAB also contains artifact detection routines, which you can use in conjunction with ERPLABÕs routines.

7.     Average together the epochs that have been assigned to each bin using ERPLAB > Compute Averaged ERPs.  The averaged data are stored in ERP.bindata field of the ERP structure, which is basically an Electrodes x Time x Bins matrix.  Other fields within the ERP structure describe the subject, sampling rate, electrode names, etc.  The new ERP structure becomes the current ERPset, and you can save it to disk as a binary file (a Ò.erpÓ extension is recommended, but it is really  a Matlab Ò.matÓ file).  You can also export this to a text file  by using ERPLAB > Export ERP to Text (readable by ERPSS) or ERPLAB > Export ERP to Text (universal).  Note that the ERP structure also contains a copy of the EVENTLIST structure from the EEG structure that was used to provide the data that were averaged together to create the ERP structure.  This can be used to perform behavioral analyses that include only the trials included in the averaged ERPs (e.g., the trials that did not contain artifacts, etc.).

8.     You can filter your ERP data with ERPLAB > Filter & Frequency Tools.

9.     You can also create new/modified bins (e.g., difference waves) using ERPLAB > ERP Bin Operations or new/modified channels (e.g., re-referenced channels) using ERPLAB > ERP Channel Operations.

10.  Plot the averaged ERP waveforms using ERPLAB > Plot ERP Waveforms or plot topographic maps of voltage using ERPLAB > Plot 2D ERP Map.  These plots can be exported (in vector format) as PDF files, which can then be imported into and edited by a variety of illustration programs.

11.  Once you have done the above steps for each subject, creating a separate ERPset for each subject, you can create a grand average across subjects using ERPLAB > Average Across ERPsets.  Note that you may want to process the first 1-3 subjects using the GUI and then write a script for processing subsequent subjects.  A history of the functions called by your GUI actions can be obtained by typing eegh or EEG.history and erph or ERP.history in the command window, and this can provide an excellent starting point for writing a script.

12.  Perform ERP measurements, such as mean amplitude and peak latency using ERPLAB > ERP Measurement Tool.  The measurements are saved in a text file in a manner that is easily imported by Excel or SPSS.

 

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