Brain areas and time course of emotional processing.

The aims of the present study were to identify brain regions involved in emotional processing as well as to follow the time sequence of these processes in the millisecond-range resolution using low resolution brain electromagnetic tomography (LORETA). Different emotional (happy, sad, angry, fearful, and disgust) and neutral faces were presented to 17 healthy, right-handed volunteers on a computer screen while 25-channel EEG data were recorded. Subjects were instructed to generate the same emotion as shown in the presented faces. Event-related potentials (ERPs) were computed for each emotion and neutral condition, and analyzed as sequences of potential distribution maps. Paired topographic analysis of variance tests of the ERP maps identified time segments of significant differences between responses to emotional and neutral faces. For these significant segments, statistical analyses of functional LORETA images were performed to identify active brain regions for the different emotions. Significant differences occurred in different time segments within the first 500 ms after stimulus onset. Each emotional condition showed specific activation patterns in different brain regions, changing over time. In the majority of significant time segments, activation was highest in the right frontal areas. Strongest activation was found in the happy, sad, and disgust conditions in extended fronto-temporal areas. Happy, sad, and disgust conditions also produced earlier and more widely distributed differences than anger and fear. Our findings are in good agreement with other brain-imaging studies (PET/fMRI). But unlike other imaging techniques, LORETA allows to follow the time sequence in the millisecond-range resolution.

Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review.

This paper reviews several recent publications that have successfully used the functional brain imaging method known as LORETA. Emphasis is placed on the electrophysiological and neuroanatomical basis of the method, on the localization properties of the method, and on the validation of the method in real experimental human data. Papers that criticize LORETA are briefly discussed. LORETA publications in the 1994-1997 period based localization inference on images of raw electric neuronal activity. In 1998, a series of papers appeared that based localization inference on the statistical parametric mapping methodology applied to high-time resolution LORETA images. Starting in 1999, quantitative neuroanatomy was added to the methodology, based on the digitized Talairach atlas provided by the Brain Imaging Centre, Montreal Neurological Institute. The combination of these methodological developments has placed LORETA at a level that compares favorably to the more classical functional imaging methods, such as PET and fMRI.