Search for: All records

Abstract Research in affective science includes over one hundred thousand articles, the vast majority of which have been published in only the past two decades. The size and rapid growth of this field have led to unique challenges for the twenty-first-century scientist including how to develop both breadth and depth of scholarship, curb siloing and promote integrative and interdisciplinary framework, and represent and monitor the field in its entirety. Here, we help address these issues by compactly mapping out this enormous field using citation network analysis (CNA). We generated a citation matrix of over 100,000 publications and over 1 million citations since the seminal works on emotion by Charles Darwin (1872) and William James (1884). Using graph theory metric and content analysis of titles and abstracts, we identified and characterized the contents of 69 research communities, their most influential articles, and their interconnectedness with each other. We further identified potential “missed connections” between communities that share similar content but do not have strong citation-based connections. In doing so, we establish the first, low-dimensional representation, or field-wide map, of a substantial portion of the affective sciences literature. This panoramic view of the field provides affective and non-affective scientists alike with the means to rapidly survey dozens of major research communities and topics in the field, guide scholarship development, and identify gaps and connections for developing an integrative science. 

Abstract Although emotion words such as “anger,” “disgust,” “happiness,” or “pride” are often thought of as mere labels, increasing evidence points to language as being important for emotion perception and experience. Emotion words may be particularly important for facilitating access to the emotion concepts. Indeed, deficits in semantic processing or impaired access to emotion words interfere with emotion perception. Yet, it is unclear what these behavioral findings mean for affective neuroscience. Thus, we examined the brain areas that support processing of emotion words using representational similarity analysis of functional magnetic resonance imaging data (N = 25). In the task, participants saw 10 emotion words (e.g. “anger,” “happiness”) while in the scanner. Participants rated each word based on its valence on a continuous scale ranging from 0 (Pleasant/Good) to 1 (Unpleasant/Bad) scale to ensure they were processing the words. Our results revealed that a diverse range of brain areas including prefrontal, midline cortical, and sensorimotor regions contained information about emotion words. Notably, our results overlapped with many regions implicated in decoding emotion experience by prior studies. Our results raise questions about what processes are being supported by these regions during emotion experience. 

Affective abstraction refers to how people conceptualize affective states in terms of category-level re- presentations that generalize across speci!c situations (e.g., “fear” as evoked by heights, predators, and haunted houses). Here, we develop a novel task for assessing affective abstraction and test its relations with trait alexithymia, depression, and autism spectrum quotient. In a preregistered online study, participants completed a set of tasks in which they matched a cue image with one of two probe images based on similarity of affective experience. In a discrete emotion version of the task, the cue and target probe matched on a discrete emotion category while controlling for valence. In a valence version of the task, the cue and target probe matched on valence (i.e., pleasantness or unpleasantness). We further varied the degree of abstraction such that some judgments crossed semantic categories (e.g., a house cue with animal probes). Accuracy, as indexed by the proportion of choices that accorded with norms, predicted trait measures of alexithymia, depression, and autism quotient with medium effect sizes. We conducted an integrative data analysis by including data from three other (nonpreregistered) samples (N = 435) and found substantial moderation by sampling population (Amazon Mechanical Turk, college students) and partial moderation by gender identity. Additional constraints on generalization include that our sample included predominantly White American adults between the ages of 23 and 64. These results provide preliminary support for the notion that affective abstraction may re"ect a transdiagnostic psychological process of broad relevance to individual differences in affective processing.