Abstract

In recent decades, affective scientists have begun using concepts and tools from dynamical systems theory (DST) to characterise emotional processes. This article considers how the concept of emergence might be used to develop this approach. Emotions are explicated as ‘emergent products’ that diachronically constrain the operations of their parts in virtue of feedback loops (a classical feature of nonlinear dynamical systems). The explication is shown to be broadly consistent with what is sometimes called ‘pattern’ emergence. Casting emotions as emergent patterns is shown to shed light on a major conceptual and empirical challenge emotion theorists have faced over the past century: identifying and measuring the presence of emotional episodes (Lindquist et al., 2012; Hollenstein & Lanteigne, 2014), dubbed here the ‘boundary problem’ (following Colombetti, 2014). In particular, the explication suggests seeing the emotional ‘signatures’ thought to accompany emotional episodes as fragile and context-bound: likely to hold under a relevant class of interventions (Woodward, 2005), but not without exception beyond that class. This in turn may suggest a need to significantly revise the statistical methods currently used to measure the presence of emotional ‘signatures’. The casting of emotions as emergent patterns also functions as a further case study supporting the value of ‘pattern emergence’ (Winning & Bechtel, 2019) as a powerful vehicle for characterising the objects of investigation — compound and context-sensitive — ubiquitous in the biological sciences.