Affective Calculus: The Construction of Affect Through Information Integration Over Time

Humans receive a constant stream of input that potentially influence their affective experience. Despite intensive research on affect, it is still largely unknown how various sources of information are integrated into the single, unified affective features that accompany consciousness. Here, we aimed to investigate how a stream of evocative input we receive is dynamically represented in self-reported affect. In 4 experiments, participants viewed a number of sequentially presented images and reported their momentary affective experience on valence and arousal scales. The number and duration of images in a trial varied across studies. In Study 4, we also measured participants' physiological responses while they viewed images. We formulated and compared several models with respect to their capacity to predict self-reported affect based on normative image ratings, physiological measurements, and prior affective experience (measured in the previous trial). Our data best supported a model incorporating a temporally sensitive averaging mechanism for affective integration that assigns higher weights to effectively more potent and recently represented stimuli. Crucially, affective averaging of sensory information and prior affect accounted for distinct contributions to currently experienced affect. Taken together, the current study provides evidence that prior affect and integrated affective impact of stimuli partly shape currently experienced affect.