Method and system for three dimensional tomography of activity and connectivity of brain and heart electromagnetic waves generators

A method for three dimensional tomography of activity and connectivity of brain electromagnetic waves generators, said method including the steps of:

• a) positioning a set of electrodes and magnetic sensors to detect and record brain electromagnetic signals representing physiological activity in the form of an electroencephalogram (EEG) and a magnetoencephalogram (MEG), and measuring exact positions of the electrodes and sensors with respect to a reference coordinate system determined by certain anatomical landmarks of a head of an experimental subject;
• b) amplifying the electromagnetic signals detected at each electrode and sensor by connecting an amplifier to each electrode and sensor;
• c) obtaining on-line digital spatio-temporal signals, consisting of said EEG and MEG, by connecting analog-digital converters to each amplifier, and digitizing all data as it is gathered;
• d) determining a parametric description for an anatomy of the experimental subject's head to obtain a descriptive parametric geometry;
• e) using said descriptive parametric geometry for constructing a head phantom with volume conductor properties of the experimental subject's head;
• f) performing EEG and MEG measurements on said head phantom due to known current dipoles located in a corresponding neural tissue volume, for determining a linear operator which transforms original EEG and MEG measurements into equivalent infinite homogeneous medium measurements (anatomical deconvolution);
• g) using said descriptive parametric geometry for determining anatomical and functional constraints for localizations, orientations, activities, and connectivities of the brain electromagnetic waves generators (generator constraints);
• h) digitally pre-processing the EEG and MEG for artifact and noise elimination, and for separation of EEG and MEG samples related to said fiducial markers, for obtaining event related components (ERCs);
• i) statistically analyzing said ERCs for determining the most adequate numerical description of spatio-temporal properties in terms of sufficient statistics;
• j) computing activities and connectivities of the ERCs generators, based on a static solution to an inverse electromagnetic problem, under said generator constraints, using sufficient statistics for the ERCs transformed to an infinite homogeneous medium by means of said anatomical deconvolution;
• k) in case said generator constraints do not allow a unique solution to the inverse problem, decreasing a number of ERCs generators sufficiently to allow for proper identifiability of the inverse problem;
• l) statistically evaluating a goodness of fit of the static solution, taking into account an existence of colored spatial and temporal noise, and including statistical hypotheses for testing an absence of activity and connectivity of the ERCs generators;
• and
• m) visually displaying three dimensional and two dimensional images corresponding to the localizations, orientations, activities, and connectivities of the ERCs generators.