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Updated: Jul 23, 2026

Brain Imaging Investigation of the Neural Correlates of Emotional Autobiographical Recollection
Published on: August 26, 2011
Brain areas and time course of emotional processing
M Esslen1, R D Pascual-Marqui, D Hell
1The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, CH-8029 Zurich, Switzerland. m.esslen@psychologie.unizh.ch
Abstract:
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.
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