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Cortex. 2010 Feb;46(2):161-9. doi: 10.1016/j.cortex.2008.06.008. Epub 2008 Jun 29.

Integration of cross-modal emotional information in the human brain: an fMRI study.

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Interdisciplinary Program in Cognitive Science, Seoul National University, Seoul, Republic of Korea.


The interaction of information derived from the voice and facial expression of a speaker contributes to the interpretation of the emotional state of the speaker and to the formation of inferences about information that may have been merely implied in the verbal communication. Therefore, we investigated the brain processes responsible for the integration of emotional information originating from different sources. Although several studies have reported possible sites for integration, further investigation using a neutral emotional condition is required to locate emotion-specific networks. Using functional magnetic resonance imaging (fMRI), we explored the brain regions involved in the integration of emotional information from different modalities in comparison to those involved in integrating emotionally neutral information. There was significant activation in the superior temporal gyrus (STG); inferior frontal gyrus (IFG); and parahippocampal gyrus, including the amygdala, under the bimodal versus the unimodal condition, irrespective of the emotional content. We confirmed the results of previous studies by finding that the bimodal emotional condition elicited strong activation in the left middle temporal gyrus (MTG), and we extended this finding to locate the effects of emotional factors by using a neutral condition in the experimental design. We found anger-specific activation in the posterior cingulate, fusiform gyrus, and cerebellum, whereas we found happiness-specific activation in the MTG, parahippocampal gyrus, hippocampus, claustrum, inferior parietal lobule, cuneus, middle frontal gyrus (MFG), IFG, and anterior cingulate. These emotion-specific activations suggest that each emotion uses a separate network to integrate bimodal information and shares a common network for cross-modal integration.

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