Literature DB >> 22019857

An integrative model of the neural systems supporting the comprehension of observed emotional behavior.

Robert P Spunt1, Matthew D Lieberman.   

Abstract

Understanding others' emotions requires both the identification of overt behaviors ("smiling") and the attribution of behaviors to a cause ("friendly disposition"). Previous research suggests that whereas emotion identification depends on a cortical mirror system that enables the embodiment of observed motor behavior within one's own motor system, causal attribution for emotion depends on a separate cortical mentalizing system, so-named because its function is associated with mental state representation. We used fMRI to test an Identification-Attribution model of mirror and mentalizing system contributions to the comprehension of emotional behavior. Normal volunteers watched a set of ecologically valid videos of human emotional displays. During each viewing, volunteers either identified an emotion-relevant motor behavior (explicit identification) or inferred a plausible social cause (explicit attribution). These explicit identification and attribution goals strongly distinguished activity in the mirror and mentalizing systems, respectively. However, frontal mirror areas, though preferentially engaged by the identification goal, nevertheless exhibited activation when observers possessed the attribution goal. One of these areas-right posterior inferior frontal gyrus-demonstrated effective connectivity with areas of the mentalizing system during attributional processing. These results support an integrative model of the neural systems supporting the comprehension of emotional behavior, where the mirror system helps facilitate the rapid identification of emotional expressions that then serve as inputs to attributional processing in the mentalizing system.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22019857     DOI: 10.1016/j.neuroimage.2011.10.005

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


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