When using a magnetoencephalographic (MEG) record, as a research or clinical tool, the investigator may face a problem of extracting the essential features of the neuromagnetic signals in the presence of artifacts. The amplitude of the disturbance may be higher than that of the brain signals, and the artifacts may resemble pathological signals in shape. For example, the heart's electrical activity, captured by the lowest sensors of a whole-scalp magnetometer array, may resemble epileptic spikes and slow waves [Jousmäki and HariJousmäki and Hari1996].
The identification and eventual removal of artifacts is a common problem in electroencephalography (EEG), but has been very infrequently discussed in context to MEG [HariHari1993,Berg and SchergBerg and Scherg1994].
The simplest and eventually most commonly used artifact correction method is rejection, based on discarding portions of MEG that coincide with those artifacts. Other methods tend to restrict the subject from producing the artifacts (e.g. by asking the subject to fix the eyes on a target to avoid eye-related artifacts, or to relax to avoid muscular artifacts). The effectiveness of those methods can be questionable in studies of neurological patients, or other non-co-operative subjects. In eye artifact canceling, other methods are available and have recently been reviewed by vigario whose method is close to the one presented here, and in jung.
This paper introduces a new method to separate brain activity from artifacts, based on the assumption that the brain activity and the artifacts are anatomically and physiologically separate processes, and that their independence is reflected in the statistical relation between the magnetic signals generated by those processes.
The remaining of the paper will include an introduction to the independent component analysis, with a presentation of the algorithm employed and some justification of this approach. Experimental data are used to illustrate the feasibility of the technique, followed by a discussion on the results.