Weighted RSA: An Improved Framework on the Perception of Audio-visual Affective Speech in Left Insula and Superior Temporal Gyrus

Being able to accurately perceive the emotion expressed by the facial or verbal expression from others is critical to successful social interaction. However, only few studies examined the multimodal interactions on speech emotion, and there is no consistence in studies on the speech emotion perception. It remains unclear, how the speech emotion of different valence is perceived on the multimodal stimuli by our human brain. In this paper, we conducted a functional magnetic resonance imaging (fMRI) study with an event-related design, using dynamic facial expressions and emotional speech stimuli to express different emotions, in order to explore the perception mechanism of speech emotion in audio-visual modality. The representational similarity analysis (RSA), whole-brain searchlight analysis, and conjunction analysis of emotion were used to interpret the representation of speech emotion in different aspects. Significantly, a weighted RSA approach was creatively proposed to evaluate the contribution of each candidate model to the best fitted model and provided a supplement to RSA. The results of weighted RSA indicated that the fitted models were superior to all candidate models and the weights could be used to explain the representation of ROIs. The bilateral amygdala has been shown to be associated with the processing of both positive and negative emotions except neutral emotion. It is indicated that the left posterior insula and the left anterior superior temporal gyrus (STG) play important roles in the perception of multimodal speech emotion.

Abstract Representations of Emotions Perceived From the Face, Body, and Whole-Person Expressions in the Left Postcentral Gyrus

Emotions can be perceived through the face, body, and whole-person, while previous studies on the abstract representations of emotions only focused on the emotions of the face and body. It remains unclear whether emotions can be represented at an abstract level regardless of all three sensory cues in specific brain regions. In this study, we used the representational similarity analysis (RSA) to explore the hypothesis that the emotion category is independent of all three stimulus types and can be decoded based on the activity patterns elicited by different emotions. Functional magnetic resonance imaging (fMRI) data were collected when participants classified emotions (angry, fearful, and happy) expressed by videos of faces, bodies, and whole-persons. An abstract emotion model was defined to estimate the neural representational structure in the whole-brain RSA, which assumed that the neural patterns were significantly correlated in within-emotion conditions ignoring the stimulus types but uncorrelated in between-emotion conditions. A neural representational dissimilarity matrix (RDM) for each voxel was then compared to the abstract emotion model to examine whether specific clusters could identify the abstract representation of emotions that generalized across stimulus types. The significantly positive correlations between neural RDMs and models suggested that the abstract representation of emotions could be successfully captured by the representational space of specific clusters. The whole-brain RSA revealed an emotion-specific but stimulus category-independent neural representation in the left postcentral gyrus, left inferior parietal lobe (IPL) and right superior temporal sulcus (STS). Further cluster-based MVPA revealed that only the left postcentral gyrus could successfully distinguish three types of emotions for the two stimulus type pairs (face-body and body-whole person) and happy versus angry/fearful, which could be considered as positive versus negative for three stimulus type pairs, when the cross-modal classification analysis was performed. Our study suggested that abstract representations of three emotions (angry, fearful, and happy) could extend from the face and body stimuli to whole-person stimuli and the findings of this study provide support for abstract representations of emotions in the left postcentral gyrus.