Interlaced resolution scheme for the simultaneous analysis of brain electric activity and conductivity with combined EEGMEG diagnostics

Purpose The purpose of this paper is to evaluate the performances of a resolution scheme able to follow the dynamics of brain tissue properties in combined ElectroEncefaloGraphic EEG MagnetoEncefaloGraphic MEG techniques for the brain analysis, minimizing the computation burden. Designmethodologyapproach The estimation process in combined EEGMEG is performed by a MoorePenrose pseudoinverse computation. This is affected by the uncertain knowledge of the living tissues' electric properties. In principle, it is possible to estimate those properties from the EEGMEG signals. The estimation process becomes in this case nonlinear. A resolution scheme is proposed, based on the exploitation of the different dynamics characterizing sources and tissues properties. Findings The proposed resolution scheme provides a reasonable estimate of the sources for a computationally affordable frequency of nonliner estimations. Research limitationsimplications The proposed approach has not been tested yet on experimental data, and as such, its sensitivity to environmental uncertainty is not known yet. Practical implications The proposed strategy can be easily implemented to perform realistic measurement processing. Originalityvalue The paper presents a novel strategy to estimate tissues properties and EEGMEG signal sources based on the exploitation of their different dynamics, possibly taking advantages from an impedance tomography preliminary analysis for the tissue properties dynamics.