An integrative and functional framework for the study of animal emotion and mood
Open accessAbstract
A better understanding of animal emotion is an important goal in disciplines ranging from neuroscience to animal welfare science. The conscious experience of emotion cannot be assessed directly, but neural, behavioural and physiological indicators of emotion can be measured. Researchers have used these measures to characterize how animals respond to situations assumed to induce discrete emotional states (e.g. fear). While advancing our understanding of specific emotions, this discrete emotion approach lacks an overarching framework that can incorporate and integrate the wide range of possible emotional states. Dimensional approaches that conceptualize emotions in terms of universal core affective characteristics (e.g. valence (positivity versus negativity) and arousal) can provide such a framework. Here, we bring together discrete and dimensional approaches to: (i) offer a structure for integrating different discrete emotions that provides a functional perspective on the adaptive value of emotional states, (ii) suggest how long-term mood states arise from short-term discrete emotions, how they also influence these discrete emotions through a bi-directional relationship and how they may function to guide decision-making, and (iii) generate novel hypothesis-driven measures of animal emotion and mood.
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Fecal corticosterone may reflect an increased state of arousal, but the arousal may not be negative.
“Although fecal corticosterone may reflect an increased state of arousal, the arousal may not be negative.29”
From Ultrasonic Vocalization Analysis as a Novel Metric to Assess Cage Enrichment in Rats (2022) · cites this paper as [29]
Section 4, “Implications for the Measurement of Animal Emotion” (page unavailable), says physiological measures, including hypothalamic-pituitary-adrenal activity, may reflect arousal without distinguishing positive from negative states. The paper does not specifically discuss fecal corticosterone, so it supports the general caution but not its application to that measure. (LLM, conf=0.85)
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- Authors
- Mendl, M., Burman, O. H. P., & Paul, E. S.
- Affiliations
- University of Bristol (GB)
- Venue
- Proceedings of the Royal Society B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 2010-08-04
- Volume
- 277
- Issue
- 1696
- Pages
- 2895-2904
- ISSN
- 0080-4649 (ISSN-L)
- 0962-8452
- 1471-2954
- PMC
- PMC2982018
- OpenAlex
- W2127099931
- Cited by
- 944
- References
- 14
- Citations by year
- 2026: 63 · 2025: 120 · 2024: 76 · 2023: 67 · 2022: 70 · 2021: 85 · 2020: 74 · 2019: 67 · 2018: 67 · 2017: 54 · 2016: 43 · 2015: 38 · 2014: 38 · 2013: 28 · 2012: 26
- FWCI
- 4.94
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the Royal Society B Biological Sciences (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (publishedVersion)
- Lincoln Repository (University of Lincoln) (acceptedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- Biotechnology and Biological Sciences Research Council (BB/C518949/1)
- Topics
- Health Sciences › Veterinary › Small Animals › Animal Behavior and Welfare Studies
- Social Sciences › Psychology › Social Psychology › Primate Behavior and Ecology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- animal emotions, discrete emotions, dimensional emotion models, valence, arousal, core affect, decision-making, animal welfare, emotion measurement
- MeSH terms
- Affect, Animals, Emotions, Motivation, Research Design, Reward
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