PhD in Individual Expectations and Emotional State / Animal Welfare

Opening a biscuit tin when hungry only to discover sewing equipment is an example of a prediction error: the mismatch between our predictions and outcomes. Both theory and experimental evidence suggest that learning from these prediction errors is important for maintaining a reliable model of the world. In both humans and animals there is also evidence, beyond anecdotal reports of biscuit-tin-disappoint, that prediction errors can influence an individual’s emotional (affective) state and welfare. Short-term unexpected rewards and losses can generate states of elation and disappointment respectively, and recent analyses of human decision-making suggest that decision outcomes that are better than predicted more strongly influence reported happiness than the total experience of positive outcomes per se. In the longer-term, loss of desired resources generates negative states and poor animal welfare, whilst addition of such resources has the opposite effect. What is needed in this field is a coherent framework, across humans and animal studies, that explains relationships between expectations, gains and losses, and emotional states and welfare.

To this end, this project will investigate the influence of short- and longer-term changes in the environment on emotional state and welfare, because the accuracy of predictions is influenced by the variability of the environment. Subjects will be studied in short-term decision-making tasks (humans and rodents) and long-term housing environments (rodents) characterised by high or low rates of change, matched for absolute levels of reward and loss. Measures of emotional state and wellbeing will be made (e.g. subjective report (humans); preference for environments; behavioural and physiological markers) allowing analysis of how cumulative experience of reward, and whether things are going better or worse than predicted, influence affective state. There will be opportunities to design environments that generate positive prediction errors to see if these can enhance affect and welfare, and to investigate how individual/personality differences in how fast predictions are updated influence responses to the different environments.

Findings will have theoretical impact and also practical implications for the design and management of animal housing to improve welfare. The student will receive training in animal behaviour and welfare science, decision-making psychology, and computational analyses of decision-making data. They will learn experimental design, behaviour and welfare research methods, and statistical/computational analysis approaches.

Salary: £15,609 to £24,090 p.a.

Closing date: 06/12/2021

Further information can be found here.