LORETA (Low Resolution Electromagnetic Tomography) was developed by Roberta Domingo, Marquis Pascal in the mid 1990's. This technique is based on the best of the inverse solutions which allows quantification and visualization of intracortical activity including paleocortical activity derived from scalp electrodes. Areas that can be evaluated include the cingulate gyrus, orbital-frontal medial and lateral cortices, subcalossal-septal area, parahippocampal gyrus and possibility regions associated with the amygdala. This regions can be identified for any EEG band pass, many sampling rates and visualized on standardized MRI sections. The method divides the cortex into 2,394 7 x 7 x 7 millimeter voxels (cubes). The inverse solution can be obtained from 19 electrodes and is very comparable to that obtained with denser surface electrode arrays. With LORETA it is possible to look at individual versus group differences or group versus group differences with appropriate statistical comparisons.In this workshop I will demonstrate the advantages of LORETA, show how data can be very accurately artifact rejected and analyzed with LORETA with direct demonstrations of the technique. I will illustrate different disorders and show relationships between LORETA images and quantitative EEG. I will present some background theory and the assumptions that this technique employs in a benign non or very lightly mathematical way.Recently LORETA has been co-validated or co-registered with MRI and PET scan findings. This is very important since LORETA is a technique that neurotherapists can learn to use and is compatible with ASCII files, Lexicor DAT files and probably many other EEG formats. The technique is easy to use and produces rapid image formation. Since LORETA is new there are many questions that need to be explored. I would like to invite meaningful interaction to help move this new technique further along and to show how it is useful in extending our ability to evaluate and treat a variety of disorders employing neurofeedback techniques. Advanced Lecture