A12: Quick Tutorial on Rejection

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Arrow.small.left.gif A11: BESA
Tutorial Outline
A13: Compiled EEGLAB Binary Arrow.small.right.gif


Quick tutorial on rejecting data artifacts with EEGLAB

Independent Component Analysis is a powerful tool for eliminating several important types of non-brain artifacts from EEG data. EEGLAB allows the user to reject many such artifacts in an efficient and user-friendly manner. This short tutorial is designed to guide impatient users who want to try using EEGLAB to remove artifacts from their data. The many other capabilities of EEGLAB are explained in detail in the main EEGLAB tutorial. To perform artifact rejection:

1) Start Matlab and EEGLAB, then import your data

Type >>  eeglab to start EEGLAB under Matlab. Select menu item File > Import data to import your data file in any of a variety of file formats including EGI and Neuroscan binary. See the Import data appendix for more details.

Scroll and check data using menu item Plot > Channel data (scroll).

2) Import a channel location file

Importing a channel location file is critical for visualizing the independent components of your data.

Select menu item Edit > Channel locations and press the button Read locations in the bottom right corner of the channel edit window. The program recognizes channel location files in most known formats (spherical BESA, polar Neuroscan, 3-D cartesian EGI, 3-D cartesian Polhemus, ...). Press OK after selecting the file and then press OK to have EEGLAB recognize the file format automatically from the file extension (Note: files with extension ".elp" are considered Polhemus files by default and not BESA files). Press OK in the channel edit window to import the channel locations into EEGLAB.

To check that your channel locations have been imported correctly, use menu item Plot > Channel locations > By name

3) Reject artifact-laden data

The quality of the data is critical for obtaining a good ICA decomposition. ICA can separate out certain types of artifacts -- only those associated with fixed scalp-amp projections. These include eye movements and eye blinks, temporal muscle activity and line noise. ICA may not be used to efficiently reject other types of artifacts -- those associated with a series of one-of-a-kind scalp maps. For example, if the subject were to scratch their EEG cap for several seconds, the result would be a long series of slightly different scalp maps associated with the channel and wire movements, etc. Therefore, such types of "non-stereotyped" or "paroxysmal" noise need to be removed by the user before performing ICA decomposition.

To reject “noisy channels “of either continuous or epoched data, select menu item Edit > select data.

To reject noisy portions of “continuous data”, select menu item Tools > Reject continuous data, then mark noisy portions of continuous data for reject by dragging the mouse horizontally with the left button held down. Press Reject when done. A new window pops up to ask for a name for the new dataset.

To reject noisy “data epochs”, select menu item Tools > Reject data epochs > Reject by inspection. Check the second checkbox to reject data at once (instead of simply marking epochs for rejection) and press OK. Then, in the scrolling window, click on data epochs you wish to reject. If you change your mind about a data epoch marked for rejection, click it again to un-select it. Press Reject when done. A new window pops up to ask for a name for the new dataset.

EEGLAB also has facilities to automatically suggest data channels, portions and/or epochs to reject. See menu item Tools > Reject data epochs > Reject data (all methods). See the Data rejection tutorial for more details.

4) Run ICA, select and reject artifactual components

Use menu Tools > Run ICA to run the ICA algorithm. To accept the default options, press OK.

Use menu Tools > Reject data using ICA > reject component by maps to select artifactual components. See the Data analysis (running ICA) tutorial for more details.

Select menu item Tools > Remove components to actually remove the selected component from the data.

See the Data analysis (running ICA) tutorial for more details and some hints on how to select artifactual components.

5) Further processing of and/or exporting the cleaned data

Your data has now hopefully been pruned of its major artifactual components. You may now proceed with further EEGLAB processing of the remaining non-artifactual independent components (see Data analysis (working with ICA components)).

You may also export your data by selecting menu item File > Export > Data and ICA activity to text file (EEGLAB v4.1). (Note: We believe Neuroscan versions 4.1 and higher can import data files in text format.)

Arrow.small.left.gif A11: BESA
Tutorial Outline
A13: Compiled EEGLAB Binary Arrow.small.right.gif