Computational Analysis, Appraised Concern-Relevance, and the Amygdala: The Algorithmic Value of Appraisal Processes in Emotion

In this commentary, we focus on two central notions of the core proposal of the human affectome framework according to which algorithms addressing affective concerns indicate the relevance of objects. First, we address the very notion of such “algorithms” in emotion theories. Second, we address the notion of appraised concern-relevance as an algorithmic solution to the computational problem of inferring the relevance of objects. Finally, we illustrate the algorithmic value of appraisal processes in emotional learning.