Decoding the Nature of Emotion in the Brain

Abstract

A central, unresolved problem in affective neuroscience is understanding how emotions are represented in nervous system activity. After prior localization approaches largely failed, researchers began applying multivariate statistical tools to reconceptualize how emotion constructs might be embedded in large-scale brain networks. Findings from pattern analyses of neuroimaging data show that affective dimensions and emotion categories are uniquely represented in the activity of distributed neural systems that span cortical and subcortical regions. Results from multiple-category decoding studies are incompatible with theories postulating that specific emotions emerge from the neural coding of valence and arousal. This 'new look' into emotion representation promises to improve and reformulate neurobiological models of affect.

Keywords: affect; emotion; fMRI; multivariate pattern analysis; neural decoding; valence.