Animal affect and decision-making. (May 2020)

• Record Type: Journal Article
• Authors: Mendl, Michael; Paul, Elizabeth S.
• Is Part Of: Neuroscience and biobehavioral reviews. Volume 112(2020)
• Page Start: 144
• Page End: 163
• Publication Date: 2020-05
• Subjects: Decision-making -- Affect -- Emotion -- Mood -- Core affect -- Reinforcement learning -- Cognition -- Cognitive bias -- Judgement bias; 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.2020.01.025
• Languages: English
• ISSNs: 0149-7634

Abstract

Graphical abstract: Highlights: A reinforcement-based definition of animal affect aligns with the core affect concept. A model rooted in decision theory shows how core affect processes influence decisions. Variation in ambiguity or uncertainty moderates affective influences on decisions. Affective influences differ under model-free and model-based control of decisions. The model integrates animal affect and decision theory and is applicable across taxa. Abstract: The scientific study of animal affect (emotion) is an area of growing interest. Whilst research on mechanism and causation has predominated, the study of function is less advanced. This is not due to a lack of hypotheses; in both humans and animals, affective states are frequently proposed to play a pivotal role in coordinating adaptive responses and decisions. However, exactly how they might do this (what processes might implement this function) is often left rather vague. Here we propose a framework for integrating animal affect and decision-making that is couched in modern decision theory and employs an operational definition that aligns with dimensional concepts of core affect and renders animal affect empirically tractable. We develop a model of how core affect, including short-term (emotion-like) and longer-term (mood-like) states, influence decision-making via processes that we label affective options, affective predictions, and affective outcomes and which correspond to similar concepts in schema of the links between human emotion and decision-making. Our framework is generalisable across species and generates questions for future research.