Journal
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
Volume 112, Issue -, Pages 144-163Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.neubiorev.2020.01.025
Keywords
Decision-making; Affect; Emotion; Mood; Core affect; Reinforcement learning; Cognition; Cognitive bias; Judgement bias
Categories
Funding
- Universities Federation for Animal Welfare (UFAW)
- Biotechnology and Biological Sciences Research Council (BBSRC)
- National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs)
- Alice Richie Trust
- BBSRC [BB/P019218/1, BB/T002654/1]
- BBSRC [BB/P019218/1, BB/T002654/1] Funding Source: UKRI
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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.
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