The Representational Dynamics of Perceived Voice Emotions Evolve from Categories to Dimensions

Long-standing affective science theories conceive the perception of emotional stimuli either as discrete categories (e.g., an angry voice) or continuous dimensional attributes (e.g., an intense and negative vocal emotion). Which position provides a better account is still widely debated. Here, we contrast them to account for acoustics-independent perceptual and cerebral representational geometry of perceived voice emotions. We combined multimodal imaging of the cerebral response to heard vocal stimuli (functional magnetic resonance imaging – fMRI – and magneto-encephalography – MEG) with post-scanning behavioral assessment of voice emotion perception. By using representational similarity analysis (RSA), we find that categories prevail in perceptual and early (< 200ms) fronto-temporal cerebral representational geometries and that dimensions impinge predominantly on a later limbic-temporal network (240ms and > 500ms). These results reconcile the two long-opposing views by reframing the perception of emotions as the interplay of cerebral networks with different representational dynamics that emphasize either categories or dimensions.