3D statistical parametric mapping of EEG source spectra by means of Variable Resolution Electromagnetic Tomography (VARETA)

This article describes a new method for 3D QEEG tomography in the frequency domain. A variant of Statistical Parametric Mapping is presented for sourc e log spectra. Sources are estimated by means of a Discrete Spline EEG inve rse solution known as Variable Resolution Electromagnetic Tomography (VARET A). Anatomical constraints are incorporated by the use of the Montreal Neur ological Institute (MNI) probabilistic brain atlas. Efficient methods are d eveloped for frequency domain VARETA in order to estimate the source spectr a for the set of 10(3)-10(5) voxels that comprise an EEG/MEG inverse soluti on. High resolution source Z spectra are then defined with respect to the a ge dependent mean and standard deviations of each voxel, which are summariz ed as regression equations calculated from the Cuban EEG normative database . The statistical issues involved are addressed by the use of extreme value statistics. Examples are shown that illustrate the potential clinical util ity of the methods herein developed.