Emotions as computations. (January 2023)

• Record Type: Journal Article
• Authors: Emanuel, Aviv; Eldar, Eran
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 144(2023)
• Publication Date: 2023-01
• Subjects: Emotion -- Mood -- Computational modeling -- Reinforcement learning -- Reward; Psychophysiology -- Periodicals; Human behavior -- Periodicals; Animal behavior -- Periodicals; Neurology -- Periodicals; Behavior -- Periodicals; Ethology -- Periodicals; Neurology -- Periodicals; Psychophysiologie -- Périodiques; Comportement humain -- Périodiques; Animaux -- Mœurs et comportement -- Périodiques; Neurologie -- Périodiques; Animal behavior; Human behavior; Neurology; Psychophysiology; Periodicals; Electronic journals; 573.8
• DOI: 10.1016/j.neubiorev.2022.104977
• Languages: English
• ISSNs: 0149-7634

Abstract

Abstract: Emotions ubiquitously impact action, learning, and perception, yet their essence and role remain widely debated. Computational accounts of emotion aspire to answer these questions with greater conceptual precision informed by normative principles and neurobiological data. We examine recent progress in this regard and find that emotions may implement three classes of computations, which serve to evaluate states, actions, and uncertain prospects. For each of these, we use the formalism of reinforcement learning to offer a new formulation that better accounts for existing evidence. We then consider how these distinct computations may map onto distinct emotions and moods. Integrating extensive research on the causes and consequences of different emotions suggests a parsimonious one-to-one mapping, according to which emotions are integral to how we evaluate outcomes (pleasure & pain), learn to predict them (happiness & sadness), use them to inform our (frustration & content) and others' (anger & gratitude) actions, and plan in order to realize (desire & hope) or avoid (fear & anxiety) uncertain outcomes. Highlights: Emotions mediate computations that evaluate states, actions, and prospects. These three classes of computation map onto three familiar types of emotions. Prior expectations are mediated by three corresponding types of moods.