KEYWORDS: Magnetoencephalography, Signal to noise ratio, Signal detection, Sensors, Iterative methods, Brain activation, Brain, Head, Magnetic resonance imaging, Inverse problems
Magnetoencephalography (MEG) is a neuroimaging technique for brain activation detection. This
technique does not provide a unique solution due to ill-posedness of its inverse solution. Several
methods are proposed to improve the MEG inverse solution. Minimum Norm (MN) is a simple
method whose solution is distributed and biased toward the superficial sources. In addition, its
solution is sensitive to the noise. Several methods are proposed to improve performance of the MN
method. In this paper, we propose a method whose solution is less sensitive to the noise and spatially
unbiased toward the superficial sources. Control of focal solution properties is achieved by
specifying a parameter in the proposed method. Performance of the proposed method is compared to
others using simulation studies consisting of single and multiple dipole sources as well as an
extended source model. Proposed method has superior performance compared to non-iterative
methods. Its performance is similar to the iterative methods but its computational load is lower.
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