The forward model predicts how activity from candidate neural sources would appear in EEG or MEG measurements. This source-to-sensor relationship provides the link needed to estimate brain activity from recorded signals. By incorporating it into the inverse calculation, the method connects measured electrical or magnetic patterns with possible locations on the brain’s anatomy.
Source estimation is ill-posed, meaning that the measured sensor signals do not uniquely determine the underlying neural activity. Minimum-norm regularization addresses this ambiguity by favoring a controlled solution, while anatomical constraints restrict or weight the candidate sources. Together, these choices make the estimated currents more stable and anatomically interpretable.
Structural information from magnetic resonance imaging supplies an anatomical framework for candidate neural sources, typically along the cortex. The estimation can then restrict or weight possible currents according to that structure rather than treating source locations as anatomically unrestricted. This improves the ability to relate reconstructed activity to specific cortical regions.
The method combines the recorded sensor data with the sensor-to-brain relationship represented by the forward model and the anatomical structure supplied by imaging. The resulting source estimates indicate where activity may occur on the cortex and when it occurs. This gives EEG or MEG findings a more direct anatomical interpretation than sensor measurements alone.
An analysis begins with EEG or MEG measurements and anatomical information, typically obtained from magnetic resonance imaging. Researchers use the anatomy to define or weight candidate cortical sources, construct the sensor-to-brain forward relationship, and apply minimum-norm estimation with regularization. The resulting currents can then be examined for their timing and cortical locations.
The resulting estimates provide information about both the timing and anatomical distribution of neural activity. Instead of describing only patterns at measurement sensors, researchers can examine estimated currents in relation to cortical regions. This supports interpretation of how activity is organized across the brain during sensory processing, cognition, or neurological conditions.
Anatomically-constrained MNE is useful when researchers need to relate EEG- or MEG-measured activity to specific brain structures. Its source estimates support investigations of sensory processing and cognition, as well as studies of neurological disorders. The anatomical framework helps connect observed neural signals with questions about where activity occurs in the brain.