Disambiguating the roles of select medial prefrontal subregions in conscious and unconscious emotional processing.

摘要

A substantial body of previous research suggests that the medial prefrontal cortex (MPFC) plays an important role in multiple aspects of emotion. These aspects include, but are not limited to, (1) generating, (2) experiencing, and (3) regulating one's own emotional state, as well as (4) facilitating the use of emotion-related information within goal-directed cognition and action selection. However, there is considerable controversy with regard to the distinct functional roles of various MPFC subregions. In this dissertation, I first provide a review of the theoretical and experimental literature to date in order to defend a plausible model of the hierarchical neural processes associated with each of the aspects of emotion highlighted above. This model proposes that different MPFC subregions each play distinct, but interactive, roles at or near the top of the respective hierarchical systems associated with those aspects of emotion. After reviewing this model, I then provide a description of four experiments that test the predictions of this model's claims regarding the roles of three distinct MPFC subregions: the rostral anterior cingulate cortex (rACC), the dorsomedial prefrontal cortex (DMPFC), and the ventromedial prefrontal cortex (VMPFC). These experiments provide independent support for the claims that (1) rACC plays an important role in representing the conceptual meaning of one's felt emotional reactions, (2) DMPFC plays an important role in maintaining representations of one's own emotions within a consciously accessible state, and (3) VMPFC plays an important role in both appraising the emotional significance of one's current situation and triggering the somatic/visceral reactions associated with the generation of an emotional response. In the concluding section of the dissertation, I then integrate these findings together with the larger model and discuss important directions for future research as well as ways in which the model might be extended to include insights from recent advances in theoretical neuroscience associated with predictive coding.