Ricerc@Sapienza

In the last decades, several studies have been carried on in order to extract the brain networks at the basis of mental processes, which are characterized by lots of interactions between different and differently specialized cortical and subcortical sites. Electroencephalography (EEG) is widely used in the study of the directed functional connectivity due to its high temporal resolution and low invasiveness but the meaning of the directed links detected at scalp level is not clear. The main open issue is related with the uncertainty introduced by two main evidences: i) the spread of the electrical field generated by neural activity and ii) the impossibility to associate one generator (source) to one sensors. Previous studies have already demonstrated the presence of a bias affecting all the brain connectivity measures related with the presence of the head volume conduction for different estimators and algorithms for the source reconstruction. A complete characterization and quantification of such investigated problem in different controlled experimental conditions in still missing. The first goal of the present project is to analyze and quantify the effects of the volume conduction on the brain connectivity estimates and to provide reliable solutions in order to increase their accuracy and their physiological interpretability. It will allow to increase the accuracy of widely used connectivity estimators and their value as neuro-physiological descriptors. The second aim of the work will be the extraction of synthetic connectivity-based measures able to catch the same local and global properties on the scalp and source level networks. Obtained results could lead to evidences proving the possibility to give a correct interpretation of the networks directly analyzed in the sensors domain.