Neural Population Decoding Reveals the Intrinsic Positivity of the Self

Abstract

People are motivated to hold favorable views of themselves, which manifests as a positivity bias when evaluating their own performance and abilities. However, it remains an open question whether positive affect is an essential component of people's self-concept. Prior functional neuroimaging research demonstrated that similar regions of the brain support positive affect and self-referential processing, although a direct test of their shared representation has yet to be examined. Here we use functional magnetic resonance imaging in conjunction with multivariate pattern analysis in a cross-domain neural population decoding paradigm. We found that a multivariate pattern classifier model trained to dissociate neural responses to viewing positively and negatively valenced images can dissociate thinking about oneself from a close friend during a lexical trait-judgment task commonly used in the study of self-referential processing. Cross-domain classification accuracy was found to be highest in the ventral medial prefrontal cortex (vMPFC), a region previously implicated in both self-referential processing and positive affect. These results show that brain responses during self-referential processing can be decoded from multi-voxel activation patterns in the vMPFC when viewing positively valenced material, thereby providing evidence that positive affect may be a central component of the mental representation of the self.