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 source log spectra. Sources are estimated by means of a Discrete Spline EEG inverse solution known as Variable Resolution Electromagnetic Tomography (VARETA). Anatomical constraints are incorporated by the use of the Montreal Neurological Institute (MNI) probabilistic brain atlas. Efficient methods are developed for frequency domain VARETA in order to estimate the source spectra for the set of 10(3)-10(5) voxels that comprise an EEG/MEG inverse solution. High resolution source Z spectra are then defined with respect to the age dependent mean and standard deviations of each voxel, which are summarized 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 utility of the methods herein developed.

Localization error in biomedical imaging.

Measures of false positive (FP) and false negative (FN) localization error are defined to assess the accuracy of diagnostic imaging procedures. These measures involve the weighting of FP and FN pixels in accordance to their distances from the true localization of the lesion and the region detected as abnormal by the classifier. The distance-based localization receiver operating characteristic (DL-ROC) curve is defined to describe the dependence of the FP and FN localization measures on the classifier's decision threshold. A computer system is presented for the analysis of localization experiments according to these concepts. As an illustration, the accuracy of two types of brain electric topographic montage is studied in the localization of brain tumors and sites of stroke.