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Chunk #125 — 3 Inverse solutions — 3.1 Non parametric optimization methods — 3.1.1 The Bayesian framework — Standardized low resolution brain electromagnetic tomography

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Review on solving the inverse problem in EEG source analysis.
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Standardized low resolution brain electromagnetic tomography (sLORETA) [32] sounds like a modification of LORETA but the concept is quite different and it does not use the Laplacian operator. It is a method in which localization is based on images of standardized current density. It uses the current density estimate given by the minimum norm estimate D^MNE and standardizes it by using its variance, which is hypothesized to be due to the actual source variance S D = I3p, and variation due to noisy measurements SMnoise = αI N . The electrical potential variance is S M = GS D G T + SMnoise and the variance of the estimated current density is SD^=TMNESMTMNET=GT[GGT+αIN]−1G. This is equivalent to the resolution matrix T MNE G. For the case of EEG with unknown current density vector, sLORETA gives the following estimate of standardized current density power: