Localization of sources in electroencephalographic registers during working memory tasks

Abstract

EEG source localization is a non-invasive imaging technique developed to locate the anatomical sources recorded at the scalp during an EEG recording. The reconstruction of the sources can be computed by solving the so-called inverse problem. This is an ill-posed problem which aims in estimating the sources that fit the recorded measurements. There exist several powerful commercial and academic software packages that cover multiple methods on data processing, source localization, and statistical analysis. In this work, the open-source MNE-Python package was selected as the working environment used to address the challenge of characterizing and locating neural activation. This study provides a pipeline with practical steps on the EEG source localization technique. The results obtained in this project have been validated by experts in the Theoretical Neurobiology and Computational Neuroscience fields In this project, the EEG source localization has been computed over a group of encephalitic patients and a control group. The two groups had shown differences regarding the electrical activity in a working memory trial. This study aimed in localizing the anatomical brain regions that were responsible of the electrical differences. It has been observed that instants before the stimulus, the activated sites between control groups and encephalitic groups differ. In the case of the control group, the activated region was located at the frontal lobe of the left hemisphere. Whereas, in the case of the encephalitic group the activated region was located at the temporal lobe of the right hemisphere.