Dynamical emotions

The field of emotion theory has been described as ‘one of the last strongholds of orthodox cognitivism’ (Lewis & Granic, 2000, p. 3). However, some researchers have begun to dismantle the broadly computationalist framework that has dominated the field by applying formal and conceptual tools from dynamic systems theory (DST). On a DST approach, emotions are emergent products of complex causal interactions among more primitive physiological and psychological functions, identifiable by transient synchronised patterns. My PhD thesis contrasted this new approach against more orthodox approaches, and explored some unresolved issues in the application of DST to emotion theory.

Importantly, dynamical approaches provide an alternative to the view that emotions are ‘natural kinds’, meaning that every instance of the kind looks the same and shares a collection of features or properties that always co-occur (Barrett, 2006). Natural kind approaches to emotion have three main limitations. First, they cannot explain natural variation in how people respond emotionally to identical triggers. Second, they struggle to explain emotional development (how people develop habitual and idiosyncratic patterns of emotional response that tend to persist across the lifespan). Three, they ignore the deep context-sensitivity of emotional responses. Dynamical approaches have resources to accommodate these features of emotion and spur novel work in the science of emotion.

Right: A simple dynamical representation of emotion (Rasa, Leonidas & Gintautas, 2020). Here, different emotion kinds are demarcated on the basis of covarying patterns of arousal (high or low) and valence (positive or negative). Each emotion kind has a distinctive pattern, and the system can move between different emotion kinds, as arousal and valence patterns shift.