Source localization vs. source imaging
The localization approach to MEG/EEG source estimation considers that brain activity at any time instant is generated by a relatively small number (a handful, at most) of brain regions. Each source is therefore represented by an elementary model, such as an ECD, that captures local distributions of neural currents. Ultimately, each elementary source is back projected or constrained to the subject’s brain volume or an MRI anatomical template, for further interpretation. In a nutshell, localization models are essentially compact, in terms of number of generators involved and their surface extension (from point-like to small cortical surface patches).
The alternative imaging approaches to MEG/EEG source modeling were originally inspired by the plethoric research in image restoration and reconstruction in other domains (early digital imaging, geophysics, and other biomedical imaging techniques). The resulting image source models do not yield small sets of local elementary models but rather the distribution of ‘all’ neural currents. This results in stacks of images where brain currents are estimated wherever elementary current sources had been previously positioned. This is typically achieved using a dense grid of current dipoles over the entire brain volume or limited to the cortical gray matter surface. These dipoles are fixed in location and generally, orientation, and are homologous to pixels in a digital image. The imaging procedure proceeds to the estimation of the amplitudes of all these elementary currents at once. Hence contrarily to the localization model, there is no intrinsic sense of distinct, active source regions per se. Explicit identification of activity issued from discrete brain regions usually necessitates complementary analysis, such as empirical or inference-driven amplitude thresholding, to discard elementary sources of non-significant contribution according to the statistical appraisal. In that respect, MEG/EEG source images are very similar in essence to the activation maps obtained in fMRI, with the benefit of time resolution however.
Inverse modeling: the localization (a) vs. imaging (b) approaches. Source modeling through localization consists in decomposing the MEG/EEG generators in a handful of elementary source contributions; the simplest source model in this situation being the equivalent current dipole (ECD). This is illustrated here from experimental data testing the somatotopic organization of primary cortical representations of hand fingers. The parameters of the single ECD have been adjusted on the [20, 40] ms time window following stimulus onset. The ECD was found to localize along the contralateral central sulcus as revealed from the 3D rendering obtained after the source location has been registered to the individual anatomy. In the imaging approach, the source model is spatially-distributed using a large number of ECD’s. Here, a surface model of MEG/EEG generators was constrained to the individual brain surface extracted from T1-weighted MR images. Elemental source amplitudes are interpolated onto the cortex, which yields an image-like distribution of the amplitudes of cortical currents.