The identification of behavioural indices of affective states in animals is central to assessing the benefits and costs of research and for efforts to refine methods and improve welfare. While affective signals do not directly indicate subjective experience, these potentially differentiate responses to negative stimuli more precisely (e.g. as fear or pain), than physiological or valence measures alone.
The proposed study aims to use detailed analyses of facial movement to examine subjective states in laboratory housed macaques. Human observers are disproportionately attentive to facial cues when assessing animal welfare; to exploit this bias requires both the validation of facial cues in the assessment of subjective states and the development evaluation tools that can be applied in the laboratory context. In humans and rodents, micro-analyses of facial movements indicate consistency in the expression of pain across individuals. We have developed a standardised tool for the measurement of facial expression in macaques (MaqFACS) and identified facial correlates of pain within a neuroscience laboratory. However, it is important to validate this method across contexts, with different types of procedures and surrounding protocols.
Given that facial expressions are also social signals, we expect the presence of conspecifics or animal care staff to impact upon both the form and frequency of expressions produced. Understanding this relationship is important for the application of behavioural methods in the assessment of pain.
Descovich KA et al. (2019). Opportunities for refinement in neuroscience: Indicators of wellness and post-operative pain in laboratory macaques. ALTEX 36(4):535-554. doi: 10.14573/altex.1811061
Descovich KA et al. (2016). Facial expression: An under-utilised tool for the assessment of welfare in mammals. ALTEX 34(3):409-29. doi: 10.14573/altex.1607161
Principal investigatorDr Sarah-Jane Vick
InstitutionUniversity of Stirling
Co-InvestigatorProfessor Hannah Buchanan-Smith
Professor Paul Flecknell
Dr Matthew Leach