  We localize the sources of brain activity of children with epilepsy based on
EEG recordings acquired during a visual discrimination working memory task. For
the numerical solution of the inverse problem, with the aid of age-specific MRI
scans processed from a publicly available database, we use and compare three
regularization numerical methods, namely the standarized Low Resolution
Electromagnetic Tomography (sLORETA), the weighted Minimum Norm Estimation
(wMNE) and the dynamic Statistical Parametric Mapping (dSPM). We show that all
three methods provide the same spatio-temporal patterns of differences between
epileptic and control children. In particular, our analysis reveals
statistically significant differences between the two groups in regions of the
Parietal Cortex indicating that these may serve as "biomarkers" for diagnostic
purposes and ultimately localized treatment.
