Abstract
Objective. Multiple facets of human emotion underlie diverse and sparse neural mechanisms. Among the many existing models of emotion, the two-dimensional circumplex model of emotion is an important theory. The use of the circumplex model allows us to model variable aspects of emotion; however, such momentary expressions of one’s internal mental state still lacks a notion of the third dimension of time. Here, we report an exploratory attempt to build a three-axis model of human emotion to model our sense of anticipatory excitement, ‘Waku-Waku’ (in Japanese), in which people predictively code upcoming emotional events. Approach. Electroencephalography (EEG) data were recorded from 28 young adult participants while they mentalized upcoming emotional pictures. Three auditory tones were used as indicative cues, predicting the likelihood of the valence of an upcoming picture: positive, negative, or unknown. While seeing an image, the participants judged its emotional valence during the task and subsequently rated their subjective experiences on valence, arousal, expectation, and Waku-Waku immediately after the experiment. The collected EEG data were then analyzed to identify contributory neural signatures for each of the three axes. Main results. A three-axis model was built to quantify Waku-Waku. As expected, this model revealed the considerable contribution of the third dimension over the classical two-dimensional model. Distinctive EEG components were identified. Furthermore, a novel brain-emotion interface was proposed and validated within the scope of limitations. Significance. The proposed notion may shed new light on the theories of emotion and support multiplex dimensions of emotion. With the introduction of the cognitive domain for a brain-computer interface, we propose a novel brain-emotion interface. Limitations of the study and potential applications of this interface are discussed.
Highlights
Human emotions are complex and constructed of multiple facets of separable components
We proposed a prototypical model of BEI to quantify “Waku-Waku” towards upcoming visual images using EEG neural markers incorporating a three-dimensional psychological model
We proposed a prototype of BEI based on a multi-axis, 3-dimensional model of emotion to quantify our anticipatory excitement using EEG
Summary
Human emotions are complex and constructed of multiple facets of separable components. Amongst many models of emotion, a two-dimensional circumplex model comprised of valence and arousal axes originally proposed by Russell [1] is widely examined as a ubiquitous model across diversities of cultures [2,3]. Other theories, such as discrete categorical theory exist [4,5]; the majority of models agreeably assumes that our emotion is a product of a momentarily affective state. Some studies conceptualize our emotion as an ‘affective working memory system’ that defines emotion as dynamic and active interactions between cognition and affect [7,8]. Our affective awareness may be an interactive state between cognitive and emotional functions, and it may not be necessarily composed of a unitary function [see 13 for review]
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