source localization methods in general aim at estimating brain
activity inside the skull based on a signal measured outside the skull,
the EEG or MEG. They have to solve the so called 'inverse problem':
with a given surface signal and with the brain activity unknown. The
other way around, the 'forward problem', with the brain activity given,
and the surface signal unknown, is a lot easier, but simply the other
side of the coin. Thus if a model can give you an inverse solution, it
can also give you a forward solution, for instance for simulation
purposes. That is the reason, why source localization and generation of
synthetic data is presented together in the present section.
Brain activity is most often estimated in terms of 'dipole
activations'. That is because electrical dipoles ( generators that have
one Plus and one Minus pole ) are the main generators of a measured EEG
and MEG, as the have a considerably spread electrical and magnetic
field. Other electrical sources (e.g. a circular set of Plus and a
central Minus Pole ) have a much more closed electrical and magnetic
field, and therefore will not contribute much to the EEG and MEG
signal. Moreover, postsynaptic potentials on pyramidal
cells of the cortex, the main source of the EEG and MEG signal, are
classical dipoles in this sense.
Different source localization methods differ concerning the number of
dipoles that are used, concerning the degree of realism of the used
head model (it's shape, it's conductivity properties etc. ), and
concerning the additional assumptions, that are used to solve the
inverse problem.
Emegs offers a source localization method that works with multiple
distributed sources (dipoles) and a spherical head model. This
method solves the (in this case underdetermined) inverse problem,
by using the additional constraint of preferring the solution with the
least overall energy, and therefore is called as this constraint 
minimum norm solution.
Using a forward solution with the same head model, emegs offers a
tool for generating
synthetic data based on user defined dipoles.
Emegs also lets you perform a related method, the
curent source
density estimation, which aims at improving the spatial resolution
of scalp EEG without making any assumptions about a head model and
dipole locations. Moreover, it allows to estimate the potential
distributiont on the cortical
surface.