Eleanor Holton (starting July 2027)

Ph.D., University of Oxford, 2024

Computational cognitive and neural mechanisms supporting learning, memory and motivation 

I study how our minds adapt processes of learning, memory and motivation to the environments we experience. I use computational modelling to understand and make predictions about the interplay between environments and the computations needed for adaptive behaviour. I test these theories with behavioural experiments, and use neuroimaging to understand the underlying neural mechanisms and representations.  

A central theme I’m interested in is how we balance inherent computational trade-offs in the way we learn, structure memories, and make decisions. For example, how do we balance immersion in a current task against the flexibility needed to process other information in the environment? How do we balance forms of memory that help us robustly retrieve details against those that help us generalize to new situations? I’m interested in whether individual differences in how people balance these trade-offs relate to the particular environments they’re exposed to, and predict symptoms of mental health. In a separate line of research, I study how the features of modern online environments (such as the structure and reward dynamics of social media) shape how people balance these trade-offs in everyday life.

E Holton, L Braun, JAF Thompson, J Grohn, C Summerfield (2026). Humans and neural networks show similar patterns of transfer and interference during continual learning. Nature Human Behaviour 10, 111–125. 

E Holton, Y Niv, J O'Reilly. The adaptive value of stubborn goals (2025). Trends in Cognitive Science 30(4), 379–390. 

E Holton, J Grohn, H Ward, S Manohar, J O'Reilly, N Kolling (2024). Goal commitment is supported by vmPFC through selective attention. Nature Human Behaviour 8, 1351–1365.