The field of cognition and emotion has grown considerably over the past 30 years, with an increased emphasis on the relationships between emotional and motivational components and how they contribute to basic perceptual, cognitive, and neural processes. For instance, research has revealed that emotion often influences these processes via emotion’s relationship with motivational dimensions, as when positive emotions low versus high in approach motivational intensity have different influences on attentional and other cognitive processes. Research has also revealed that motivational direction (...) (approach vs. withdrawal) and affective valence (positive vs. negative) are not as closely related as once was theorised; that is, positive affect is not inevitably associated with approach motivation and negative affect is not inevitably associated with withdrawal motivation. These and other lines of research with anger have suggested that the field needs to move beyond a focus on affective valence and it needs to consider an integration of dimensional and discrete models of emotion. The article also includes some suggestions for improving methods of measuring and inducing emotions and some recommendations for future researchers. (shrink)

Despite the fact that human daily emotions are co-occurring by nature, most neuroscience studies have primarily adopted a univariate approach to identify the neural representation of emotion (emotion experience within a single emotion category) without adequate consideration of the co-occurrence of different emotions (emotion experience across different emotion categories simultaneously). To investigate the neural representations of multivariate emotion experience, this study employed the inter-situation representational similarity analysis (RSA) method. Researchers used an EEG dataset of 78 participants who watched 28 video (...) clips and rated their experience on eight emotion categories. The EEG-based electrophysiological representation was extracted as the power spectral density (PSD) feature per channel in the five frequency bands. The inter-situation RSA method revealed significant correlations between the multivariate emotion experience ratings and PSD features in the Alpha and Beta bands, primarily over the frontal and parietal-occipital brain regions. The study found the identified EEG representations to be reliable with sufficient situations and participants. Moreover, through a series of ablation analyses, the inter-situation RSA further demonstrated the stability and specificity of the EEG representations for multivariate emotion experience. These findings highlight the importance of adopting a multivariate perspective for a comprehensive understanding of the neural representation of human emotion experience. (shrink)