  Magnetoencephalography (MEG) provides dynamic spatial-temporal insight of
neural activities in the cortex. Because the number of possible sources is far
greater than the number of MEG detectors, the proposition to localize sources
directly from MEG data is notoriously ill-posed. Here we develop an approach
based on data processing procedures including clustering, forward and backward
filtering, and the method of maximum entropy. We show that taking as a starting
point the assumption that the sources lie in the general area of the auditory
cortex (an area of about 40 mm by 15 mm), our approach is capable of achieving
reasonable success in pinpointing active sources concentrated in an area of a
few mm's across, while limiting the spatial distribution and number of false
positives.
