Animal affect and decision-making

Michael Mendl*, Elizabeth S. Paul

*Corresponding author for this work

Research output: Contribution to journalReview article (Academic Journal)peer-review

14 Citations (Scopus)
137 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)144-163
Number of pages20
JournalNeuroscience and Biobehavioral Reviews
Early online date25 Jan 2020
Publication statusPublished - 1 May 2020


  • Decision-making
  • Affect
  • Emotion
  • Mood
  • Core Affect
  • Reinforcement Learning
  • Cognition
  • Cognitive Bias
  • Judgement Bias


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