A test of four EOG correction methods using an improved validation technique

Abstract

A group of methods that are employed for removing ocular artifact from the electroencephalogram (EEG) is referred to as electrooculogram (EOG) correction methods. These use least-square linear regression, and the relative success of these is yet to be established. Improving on previous EOG correction validation studies, we present a new validation technique (with greater face validity) and use it to compare four commonly employed EOG correction methods. Data consisted of ERP traces to auditory stimuli that were embedded in up, down, left and right eye movements (EMs), recorded from 24 subjects. A ‘Peak Difference’ validation measure was employed, which determined the magnitude of the difference of two auditory N100 peaks (those associated with EMs with opposing polarities). All correction methods produced data that was better than not correcting at all. EOG correction methods that accounted for vertical EM, horizontal EM and blink artifact separately using separate EOG channels, produced the best corrections, with some further advantage in methods that enhanced signal (EOG) to noise (EEG) ratios when calculating correction coefficients.