What and where in electromagnetic brain imaging

To understand the brain, we need to observe the nature and dynamics of the activity (the “what”), and the location or distribution of its sources (the “where”). This paper proposes a new approach in which these two elements are derived in parallel from separate columns of a data-driven analysis matrix. A subset of columns enhances the activity of interest, and its complement defines spatial filters that suppress that activity (null filters). Each null filter is combined with an anatomy-dependent source model to estimate a set of locations within the sources space in which the source might reside (the “zero set” of that filter) and the final estimate is derived from the intersection of zero sets. There is no theoretical limit to the accuracy with which the location of a source can be estimated in this way, but practical limits may arise from noise in the data, imperfect calibration, or an incomplete or inaccurate source model. The method is illustrated with simulated and real data from EEG, MEG and SEEG.