Magnetoencephalography: the art of finding a needle in a haystack

The brain's magnetic signals are much weaker than the magnetic disturbances inside the typical commercial magnetically-shielded room. Magnetic noise arises from far-field environmental sources (power lines, vehicles, etc.) and from near-field biological sources (electrically active tissues, such as muscle, heart, unwanted brain signals, etc.). Some form of inverse solution is generally used to solve for the sources that account for the MEG measurements. However, the inversion problem is non-unique and ill defined. Given the large amounts of noise and the non-uniqueness, how can MEG inversion succeed? One must provide methods for efficient attenuation of environmental noise, combined with MEG localization methods that are robust against the background clutter. Noise cancellation methods will be reviewed, and it will be shown that a combination of synthetic gradiometers, adaptive signal processing, and moderately shielded rooms can provide environmental noise attenuation in excess of 10(7). Two types of MEG signal analysis techniques will be discussed: those depending solely on prior noise cancellation (e.g., equivalent current dipole fit and minimum norm), and those intrinsically providing additional cancellation of far and near field noise (e.g. beamformers). The principles and behavior of beamformers for variations in signal and noise will be explained. Several beamformer classes will be discussed, and the presentation will conclude with examples of their clinical applications. (C) 2001 Elsevier Science B.V. All rights reserved.