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Statistical control of artifacts in dense array EEG/MEG studies

Published online by Cambridge University Press:  01 July 2000

MARKUS JUNGHÖFER
Affiliation:
Department of Psychology, University of Konstanz, Germany
THOMAS ELBERT
Affiliation:
Department of Psychology, University of Konstanz, Germany
DON M. TUCKER
Affiliation:
Department of Psychology, University of Oregon, Eugene, USA Electrical Geodesics, Inc., Eugene, Oregon, USA
BRIGITTE ROCKSTROH
Affiliation:
Department of Psychology, University of Konstanz, Germany
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Abstract

With the advent of dense sensor arrays (64–256 channels) in electroencephalography and magnetoencephalography studies, the probability increases that some recording channels are contaminated by artifact. If all channels are required to be artifact free, the number of acceptable trials may be unacceptably low. Precise artifact screening is necessary for accurate spatial mapping, for current density measures, for source analysis, and for accurate temporal analysis based on single-trial methods. Precise screening presents a number of problems given the large datasets. We propose a procedure for statistical correction of artifacts in dense array studies (SCADS), which (1) detects individual channel artifacts using the recording reference, (2) detects global artifacts using the average reference, (3) replaces artifact-contaminated sensors with spherical interpolation statistically weighted on the basis of all sensors, and (4) computes the variance of the signal across trials to document the stability of the averaged waveform. Examples from 128-channel recordings and from numerical simulations illustrate the importance of careful artifact review in the avoidance of analysis errors.

Type
Research Article
Copyright
2000 Society for Psychophysiological Research

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