Emotions have multiple components such as facial and bodily expressions, autonomic reactions, and cognitive appraisals.  Many of these components may exist without us being aware that we “feel”.  The question we ask is how do we become consciously aware of (and able to report about) our feelings?

Already in 1884, William James suggested that emotional feelings are a type of sensory perception.  We take this “perceptual hypothesis” very seriously and show that models describing perceptual decisions are just as suitable to explain perceptual decisions as they are suitable to describe “usual” perceptual decisions.  In the talk, we will specifically show that the Linear Ballistic Accumulator model of Brown and Heathcote (2008), originating the perceptual-decision literature, is suitable to describe the dynamics of reports about emotional feelings (mostly pleasantness). We will further show that the model is supported by results showing selective influence: i.e., manipulations/individual differences that selectively and predictably influence only specific parameters of the model including reappraisal (reality challenge), anticipated efforts, and sex-differences.

This supported model does not only serve as a process model, but also as a measurement model, since its core parameter, the rate of evidence accumulation (drift-rate) provides a ratio-scale for the intensity of emotional feelings.  Equipped with this model, we will present two lines of evidence which very strongly support the Perceptual Hypothesis: 1. Pleasantness feelings obey the most fundamental Law of Sensation: Weber’s Law, stating the uncertainty increases proportionally with intensity; and 2. Aberrant (counter-normative) reports about emotion resemble perceptual decision errors in terms of their reaction-time distribution, sensitivity to speed-accuracy tradeoff, post-error slowing, and lack-of error-related negativity in the EEG