Correction of ocular artifacts in EEGs using an autoregressive model to describe the EEG; a pilot study

Berg-Lenssen, M.M.C. van den; Brunia, C.H.M.; Blom, J. A.

doi:10.1016/0013-4694(89)90021-7

Cited by 39 publications

(17 citation statements)

References 23 publications

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“…The eye movement records were used off-line to correct the event-related potentials for electrical contamination of both vertical and horizontal ocular artifacts using the autoregression method of Van den Berg-Lenssen et al (1989). This method relies on an eye movement calibration trial that was recorded before each block in order to estimate the correction parameters for that block.…”

Section: Recording and Analysis Of Psychophysiological Signalsmentioning

confidence: 99%

A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm

Boxtel

Molen

Jennings

et al. 2001

Biological Psychology

249

179

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A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm van Boxtel, Geert; van der Molen, M.; Jennings, J.R.; Brunia, Cees General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.-Users may download and print one copy of any publication from the public portal for the purpose of private study or research -You may not further distribute the material or use it for any profit-making activity or commercial gain -You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright, please contact us providing details, and we will remove access to the work immediately and investigate your claim. AbstractWe examined two potential inhibitory mechanisms for stopping a motor response. Participants performed a standard visual two-choice task in which visual stop signals and no-go signals were presented on a small proportion of the trials. Psychophysiological measures were taken during task performance to examine the time course of response activation and inhibition. The results were consistent with a horse race model previously proposed to account for data obtained using a stop-signal paradigm. The pattern of psychophysiological responses was similar on stop-signal and no-go trials suggesting that the same mechanism may initiate inhibitory control in both situations. We found a distinct frontal brain wave suggesting that inhibitory motor control is instigated from the frontal cortex. The results are best explained in terms of a single, centrally located inhibition mechanism. Results are discussed in terms of current neurophysiological knowledge.

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Section: Recording and Analysis Of Psychophysiological Signalsmentioning

confidence: 99%

A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm

Boxtel

Molen

Jennings

et al. 2001

Biological Psychology

249

179

View full text Add to dashboard Cite

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“…Instead of nontrivial linear combinations and/or products of signals obtained from the electrodes near the eyes we instead use the raw signals themselves for the exogenous inputs. Doing so encompasses most previous models found in the literature (see, e.g., [5], [8], [9], [10], [11]). …”

Section: Subtraction Ocular Artifact Removal Methods Subtraction Meth-mentioning

confidence: 99%

“…The regression model of (1) usually assumes the following: A1 The background EEG w(n) is uncorrelated (white) noise with zero mean ( [5], [11]); A2 All frequencies of the EOG have the same propagation characteristics. In other words, y(n) is not dependent on u i (t) for t < n ( [12], [11], [5]); A3 The EOG u i (n), i ∈ {1, .…”

Section: Subtraction Ocular Artifact Removal Methods Subtraction Meth-mentioning

confidence: 99%

“…In other words, y(n) is not dependent on u i (t) for t < n ( [12], [11], [5]); A3 The EOG u i (n), i ∈ {1, . .…”

Section: Subtraction Ocular Artifact Removal Methods Subtraction Meth-mentioning

confidence: 99%

“…In practice A1 does not hold because the underlying brainwave activity is significantly correlated [15], [16], [17]. To account for this correlation, van den Berg-Lenssen in [11] proposed to model the background EEG as the moving average of uncorrelated noise, i.e. (1) becomes…”

Section: Subtraction Ocular Artifact Removal Methods Subtraction Meth-mentioning

confidence: 99%

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EEG ocular artifact removal through ARMAX model system identification using extended least squares

Haas

Frei²,

Osorio³

et al. 2003

Communications in Information and Systems

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Abstract. The removal of ocular artifact from scalp electroencephalograms (EEGs) is of considerable importance for both the automated and visual analysis of underlying brainwave activity. Traditionally, subtraction techniques use linear regression to estimate the influence of eye movements on the electrodes of interest. These methods are based on the assumption that the underlying brainwave activity is uncorrelated when, in general, it is not. Furthermore, regression methods assume that the ocular artifact propagation is frequency independent, i.e. all waveforms of the ocular artifact propagate similarly. In this paper, we examine relaxing these assumptions by using a more general autoregressive (AR) moving average (MA) exogenous (X) model and the extended least squares (ELS) algorithm to remove ocular artifact. We demonstrate that in some cases this general ARMAX model can decrease ocular artifact not removable by standard regression techniques. We also show that the incorporation of a forgetting factor to exponentially weight past data can improve ocular artifact removal even for the traditional subtraction method.

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Automatic Processing of EEG-EOG-EMG Artifacts in Sleep Stage Classification

et al. 2009

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Correction of ocular artifacts in EEGs using an autoregressive model to describe the EEG; a pilot study

Cited by 39 publications

References 23 publications

A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm

A psychophysiological analysis of inhibitory motor control in the stop-signal paradigm

EEG ocular artifact removal through ARMAX model system identification using extended least squares

Automatic Processing of EEG-EOG-EMG Artifacts in Sleep Stage Classification

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