The objective of this project is to take the first step towards the definition of a model of visual-functional reconstruction of the brain's electrophysiologic activity without having access to patient-specific structural MRI. The proposed approach relies on the combination of electroencephalography (EEG) source localization and machine-learning algorithms for the definition of a standard based on the comparison of discriminating features between brain models. EEG source localization (ESI) aims at identifying the areas of the brain responsible for potential variations detected by electrodes placed on the scalp of the patient, and involves the resolution of two fundamental problems: the forward problem and the inverse problem.