Investigating Emotional Similarity: A Comment on Riberto, Pobric, and Talmi (2019).

A recent review of the neuroimaging literature on emotional similarity brought to light some of the drawbacks of the latest studies. The authors discussed important methodological considerations for future work in this field, which predominantly involved stimulus selection. In general, we feel that their suggestions are valuable, but we hold that, depending on the specific scientific question(s) under investigation (e.g., individual differences), some of the suggestions may not meaningfully contribute to the scope of the study and might even introduce artificial constraints that could reduce the researchers' ability to discover effects of interest. Here we indicate one way to potentially circumvent such stimulus-related issues in neuroimaging studies and furthermore present a few scenarios in which additional controlling of the stimulus set may not be necessary or possible when investigating individual differences. This commentary serves to supplement the important methodological points raised by the authors by providing a caveat in potentially applying such points to all future experiments investigating emotional similarity.

Linking Personality Traits to Individual Differences in Affective Spaces.

Different individuals respond differently to emotional stimuli in their environment. Therefore, to understand how emotions are represented mentally will ultimately require investigations into individual-level information. Here we tasked participants with freely arranging emotionally charged images on a computer screen according to their subjective emotional similarity (yielding a unique affective space for each participant) and subsequently sought external validity of the layout of the individuals' affective spaces through the five-factor personality model (Neuroticism, Extraversion, Openness to Experience, Agreeableness, Conscientiousness) assessed via the NEO Five-Factor Inventory. Applying agglomerative hierarchical clustering to the group-level affective space revealed a set of underlying affective clusters whose within-cluster dissimilarity, per individual, was then correlated with individuals' personality scores. These cluster-based analyses predominantly revealed that the dispersion of the negative cluster showed a positive relationship with Neuroticism and a negative relationship with Conscientiousness, a finding that would be predicted by prior work. Such results demonstrate the non-spurious structure of individualized emotion information revealed by data-driven analyses of a behavioral task (and validated by incorporating psychological measures of personality) and corroborate prior knowledge of the interaction between affect and personality. Future investigations can similarly combine hypothesis- and data-driven methods to extend such findings, potentially yielding new perspectives on underlying cognitive processes, disease susceptibility, or even diagnostic/prognostic markers for mental disorders involving emotion dysregulation.

The neural representation of an individualized relational affective space.

Humans experience emotions every day. Traditionally, psychology has described emotions through discrete labels (e.g. happy, afraid) or standardized affective dimensions (e.g. valence, arousal), and neuroscience has more recently sought the neurobiological basis of emotions via functional neuroimaging. However, by treating emotions similarly among everyone, we neglect that emotions are individualized; thus the overall relational structure of an individual's emotion information may be vital in understanding how the brain represents emotions. Combining behavioral and functional MRI experiments with similarity analyses, we demonstrate that neural activity patterns in the left insula correspond to the multi-dimensional arrangement of individuals' affective spaces, despite interindividual differences, better than to a group-averaged model of affective space, a standardized valence-arousal space, a semantic category space, and a visual similarity space. This finding suggests that the insula may underlie individual-level affective information processing that is specific to one's own affective states, which offers new opportunities for functional neuroimaging to inform clinical approaches of disorders involving emotion dysregulation.