Validation of ICA as a tool to remove eye movement artifacts from EEG/ERP

Abstract

Eye movement artifacts in electroencephalogram (EEG) recordings can greatly distort grand mean event-related potential (ERP) waveforms. Different techniques have been suggested to remove these artifacts prior to ERP analysis. Independent component analysis (ICA) is suggested as an alternative method to "filter" eye movement artifacts out of the EEG, preserving the brain activity of interest and preserving all trials. However, the identification of artifact components is not always straightforward. Here, we compared eye movement artifact removal by ICA compiled on 10 s of EEG, on eye movement epochs, or on the complete EEG recording to the removal of eye movement artifacts by rejecting trials or by the Gratton and Coles method. ICA performed as well as the Gratton and Coles method. By selecting only eye movement epochs for ICA compilation, we were able to facilitate the identification of components representing eye movement artifacts.