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Pros And Cons Of Artifact Correction

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Pros And Cons Of Artifact Correction
INTRODUCTION
Although EEG is designed to record cerebral activity, it also records electrical activities arising from sites other than the brain. These unwanted chunks of electrical activity are termed artifacts and may be divided into physiological and non-physiological artifacts. Physiological artifacts are generated from sources other than the brain (i.e., any other part of the body like the eyes, other voluntary and involuntary muscles) and involve head or limb motion and muscular tension. On the other hand, non-physiological artifacts arise from outside the body (i.e., equipment, environment etc.) and involve electromagnetic perturbations from other devices used in the experiment and/or leaking power line contamination, etc.
The chances
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Specific Participant Populations – There are some groups of subjects (e.g. children and psychiatric patients) who cannot easily control their blinking, eye movements and/or muscular movements (e.g. epileptic and Parkinson patients) making it difficult to obtain a sufficient number of artifact-free trials. Such populations are in fact more likely to exhibit exaggerated movement.

Cons of Artifact Correction
Researchers have developed several artifact correction procedures (Berg & Scherg, 1991a, 1994; Gratton, Coles, & Donchin, 1983; Lins et al., 1993b; Verleger, Gasser, & Moecks, 1982).
The approach of subtracting voltages from ERP waveforms can be a problematic one. Specifically, the EOG recording contains brain activity in addition to true ocular activity and, as a result, the subtraction procedure ends up subtracting away part of the brain’s response as well as the ocular artifacts.
Although most artifact correction techniques can be useful or even indispensable for certain tasks and certain types of subjects, they have some significant
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Some of these techniques can significantly distort the ERP waveforms and scalp distributions, making the data difficult to interpret. A newer and promising approach is the independent components analysis (ICA). This approach is well justified mathematically, and recent studies demonstrated that this technique works very well at removing blinks, eye movements and even electrical noise. However, this approach assumes that the time course of the artifacts is independent of the time course of the ERP activity, which may not always be a correct assumption. Until an independent laboratory rigorously tests this technique, it will be difficult to know whether this sort of situation leads to significant distortions.
2. Artifact correction techniques may require significant additional effort. For example, Lins et al. recommended that recordings should be obtained from at least seven electrodes near the eyes. In addition, one must conduct a set of calibration runs for each subject and carry out extensive signal processing on the data. Thus, it is important to weigh the time saved by using artifact correction procedures against the time required to satisfactorily implement these


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