MEG (Magnetoencephalography) Program

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Electromagnetic neural source imaging

The quantitative analysis of MEG/EEG sensor data is a source of vast possibilities to characterize time-resolved brain activity. Some studies however may require a more direct assessment of the anatomical origins of the effects detected at the sensor level. It is also likely that some effects may not even be revealed using scalp measures, because of severe mixing and smearing due to the relative large distance from sources to sensors and volume conduction effects.

Electromagnetic source imaging addresses this issue by characterizing these latter elements (the head shape and size, relative position and properties of sensors, noise statistics, etc.) in a principled manner and by suggesting a model for the generators responsible for the signals in the data. Ultimately, models of electrical source activity are produced and need to be analyzed in a multitude of dimensions: amplitude maps, time/frequency properties, connectivity, etc., using statistical assessment techniques. The rest of this chapter details most of the steps required, while skipping technical details, which can be found in the references cited.
 

(1) A modeling problem

From a methodological standpoint, MEG/EEG source modeling is referred to as an ‘inverse problem’, an ubiquitous concept, well-known to physicists and mathematicians in a wide variety of scientific fields: from medical imaging to geophysics and particle physics.

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(2) Ill-posed inverse problems

A methodological detour on MEG/EEG source modeling as an inverse problem that accepts multiple solutions, which are models that equivalently predict the observations and how to tackle this issue.

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(3) Models of neural generators

The canonical source model of the net primary intracellular currents within a neural assembly is the electric current dipole.

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(4) Modeling the sensor array

The details of the sensor geometry and pick-up technology can be modeled for further accuracy of the imaging process.

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(5) Modeling head tissues

Predicting the electromagnetic fields produced by an elementary source model at a given sensor array requires head modeling: another modeling step, which concerns a large part of the MEG/EEG literature.

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(6) MEG/EEG source estimation and imaging

Technical aspects of MEG/EEG source imaging from sensor data.

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