Correction of EOG Artifacts in Event‐Related Potentials of the EEG: Aspects of Reliability and Validity

Verleger, Rolf; Gasser, Théo; Möcks, Joachim

doi:10.1111/j.1469-8986.1982.tb02509.x

Cited by 177 publications

(104 citation statements)

References 11 publications

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“…Regression methods were introduced by Quilter et al (1977) and subsequently by Verleger et al (1982), who proposed a regression method for estimating the scaling factors, in which only large EOG potentials are used for the computation. In the approach proposed by Verleger et aI., the scaling factors are computed separately for each epoch and then averaged together.…”

Section: Time Domain Techniquesmentioning

confidence: 99%

“…Provided that this is the case, it should be possible to compute the scaling factors by using standard linear regression methods, or other similar statistical or mathematical methods. Several investigators have proposed methods based on this approach (e.g., Elbert, Lutzenberger, Rockstroh, & Birbaumer, 1985;Fortgens & de Bruin, 1983;Gasser, Sroka, & Mocks, 1986;Gratton, Coles, & Donchin, 1983;Jervis, Nichols, Allen, Hudson, & Johnson, 1985;Quilter, McGillivray, & Wadbrook, 1977;Verleger, Gasser, & Mocks, 1982) . ' The assumption of instantanteous propagation of the EOG artifact through the head is based on the notion that the eyeball electric field is electrostatic in nature.…”

Section: Time Domain Techniquesmentioning

confidence: 99%

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Dealing with artifacts: The EOG contamination of the event-related brain potential

Gratton

1998

Behavior Research Methods, Instruments, & Computers

122

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Eye movements and blinks represent a major source of artifacts in the electroencephalogram (EEG) and event-related brain potentials (ERPs). The origin of this artifact is the large difference in potential that exists between the cornea and the retina. Eye movements and blinks produce shifts of the electric fields that propagate across the whole head and that can be several times larger than the activity generated by the brain, Ocular activity can be monitored by electrodes located near the eyes (electrooculogram, or EOG). The electric fields associated with eye movements and blinks are somewhat different. The simplest procedure for dealing with ocular artifacts is to eliminate trials on which EOG activity is detected (rejection). However, this technique may result in data loss and biased data samples, especially when one is comparing clinical populations or tasks involving large amounts of eye movements, Another approach involves estimation and correction of the ocular artifact on the EEG and ERP traces. Several techniques have been proposed. Some of them are reviewed in the present paper. Issues related to the accuracy of the various techniques, as well as other advantages and limitations, are also discussed. Finally, general guidelines for how to deal with ocular artifacts are proposed. 44The difference in electric potential between the front and the back ofthe eye generates a large dipole-like electric field (electro-oculogram, or EOG) that may interfere with the surface recording ofthe electrical activity of the brain (electroencephalogram, or EEG), If the EOG does not change over time, its effect on the EEG will be a constant. Since the EEG is measured as a change with respect to a baseline value, the effect of a constant EOG is null. Therefore, EOG contamination of the EEG trace occurs whenever the eyes move, or whenever the propagation ofthe EOG to the scalp electrodes varies over time. This type of contamination is labeled EOG artifact, ocular artifact, or eye-movement artifact.The EOG artifact is of great significance in the registration ofEEG and event-related brain potentials (ERPs). In fact, when measured at the scalp, especially at frontal locations close to the eyes, the EOG signal (several hundred microvolts in amplitude) can be several times larger than the brain-generated scalp potentials (typically, less than 50 JiV). Eye movements and blinks (both of which are associated with large EOG artifacts) are very frequent and may occur during the performance of various tasks or as the result of certain types ofstimulations. The frequency and size ofEOG artifacts may vary, depending I would like to thank Monica Fabiani and two anonymous reviewers for their comments on earlier versions of this manuscript. Send all correspondence to G. Gratton,

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Section: Time Domain Techniquesmentioning

confidence: 99%

Section: Time Domain Techniquesmentioning

confidence: 99%

Dealing with artifacts: The EOG contamination of the event-related brain potential

Gratton

1998

Behavior Research Methods, Instruments, & Computers

122

View full text Add to dashboard Cite

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“…Regression methods have been proposed using both time domain (Hillyard and Galambos, 1970;Verleger et al, 1982) and frequency domain techniques (Whitton et al, 1978;Woestenburg et al, 1983). All regression methods, whether in time or frequency domains, depend on having one or more clean reference channels (e.g.…”

Section: Introductionmentioning

confidence: 99%

Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects

Jung¹,

Makeig²,

Westerfield³

et al. 2000

Clinical Neurophysiology

1,221

721

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Objectives: Electrical potentials produced by blinks and eye movements present serious problems for electroencephalographic (EEG) and event-related potential (ERP) data interpretation and analysis, particularly for analysis of data from some clinical populations. Often, all epochs contaminated by large eye artifacts are rejected as unusable, though this may prove unacceptable when blinks and eye movements occur frequently.Methods: Frontal channels are often used as reference signals to regress out eye artifacts, but inevitably portions of relevant EEG signals also appearing in EOG channels are thereby eliminated or mixed into other scalp channels. A generally applicable adaptive method for removing artifacts from EEG records based on blind source separation by independent component analysis (ICA) (Neural Computation 7 (1995) 1129; Neural Computation 10(8) (1998) 2103; Neural Computation 11(2) (1999) 606) overcomes these limitations.Results: Results on EEG data collected from 28 normal controls and 22 clinical subjects performing a visual selective attention task show that ICA can be used to effectively detect, separate and remove ocular artifacts from even strongly contaminated EEG recordings. The results compare favorably to those obtained using rejection or regression methods.Conclusions: The ICA method can preserve ERP contributions from all of the recorded trials and all the recorded data channels, even when none of the single trials are artifact-free. q

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“…Several proposed methods for removing eye-movement artifacts are based on regression in the time domain~Gratton, Coles, & Donchin, 1983;Hillyard & Galambos, 1970;Verleger, Gasser, & Möcks, 1982! or frequency domain~Whitton, Lue, & Moldofsky, 1978Woestenburg, Verbaten, & Slangen, 1983!.…”

mentioning

confidence: 99%

Removing electroencephalographic artifacts by blind source separation

JUNG¹,

Makeig²,

Humphries³

et al. 2000

Psychophysiol.

1,507

1,313

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Correction of EOG Artifacts in Event‐Related Potentials of the EEG: Aspects of Reliability and Validity

Cited by 177 publications

References 11 publications

Dealing with artifacts: The EOG contamination of the event-related brain potential

Dealing with artifacts: The EOG contamination of the event-related brain potential

Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects

Removing electroencephalographic artifacts by blind source separation

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