Recently developed synthetic aperture magnetometry (SAM) is a new MEG signal analysis introducing a high performance spatial filtering technique. SAM is not an inverse solution like dipole analysis, but rather an adaptive beamformer for estimating source activity at each selected voxel inside of the brain. SAM can estimate source changes as a function of time, or power changes subjected to statistical analysis from the non-averaged raw MEG data. Thus this method enables to display the regional currentodensitogram of the arbitrary selected brain tissue as if depth electrodes were inserted (SAM virtual sensor), and to detect the origin of epileptic discharges and their spread. By applying statistical discrimination, SAM can also demonstrate the spatial distribution of event-related changes of brain rhythm (SAM statistical method), in other words activated cerebral cortex during task performance. We will present the usefulness of noninvasive SAM methods in epilepsy surgery detecting the epileptogenic zone by SAM virtual sensor method as well as eloquent brain by SAM statistical method.
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