Emotion Dynamics: Mapping the structure and function of emotional variability

Emotion is a dynamic phenomenon that involves multiple interacting systems whose responses unfold over multiple timescales. However, many methodological and quantitative approaches employed to study emotion are ill-equipped to capture their multivariate and temporal expression. Expanding experimental/quantitative tools to study emotion’s dynamic features can (i) improve the common practices for how researchers approach this topic, (ii) enrich theories on the structure/function of emotion and, (iii) inform clinical approaches treating emotion-related disorders (e.g., psychopathology, cardiovascular disease). As a part of this collection, we invite authors to submit empirical articles that capture emotion across multiple response variables and/or emotional dynamics across time. By emotion, we refer to emotional experience, emotional expression, and/or emotional regulation. Special preference is given to papers that employ biological measures of the brain, autonomic nervous system, somatic nervous system, and/or endocrine system. Special preference is also given to longitudinal and multi-method approaches that rigorously investigate the multivariate structure (e.g., cluster analysis, coherence, machine learning) and/or temporal change (e.g., Fourier analysis, autocorrelation, wavelet analysis) of emotion variables. This may include dyadic or group studies that examine correlations in emotional variables such as physiology between individuals.

We especially welcome papers that address nonlinear relationships and/or multiple timescales of change (e.g., second-to-second and day-to-day shifts in emotion).