

This project seeks to explore how memory evolves in response to the ecological tasks that animals face in their natural environment. Associative memory exists in some form in almost all animal species that have been tested, and is one of the fundamental building blocks of the animal mind. However, it is far from a singular, uniform entity that fades gradually over time. Instead, memories are stored through a complex interplay of multiple, semi-independent phases that operate in parallel, each with its own triggers, storing memories in various forms with differing levels of stability. These processes- particularly short-term memory (STM) and long-term memory (LTM)- have been hypothesized to play different roles in the ecological world, but in reality we do not understand whether selection can act on them independently. In this project, we will establish how selection on associative LTM affects STM, and more widely, performance in other tasks, using experimental evolution approaches in fruit fly models. Working closely within a team of researchers all of whom will be exploring different aspects of the evolution of memory, you will create Drosophila lines that have undergone selection for STM or LTM, and explore impacts on (a) performance in assays of the selected and non-selected trait (b) performance in different real-world tasks (c) evolutionary changes in cognitive genes and gene expression.
Depending upon their previous experience, the student will be trained in (a) experimental evolution methodologies (b) transcriptomics and RNA-seq (c) application of ecological statistics approaches (d) fundamentals of animal behaviour (a) insect care and husbandry. This will be achieved in-house through interaction with other team members in both supervisors’ research groups (complementary relevant expertise: insect cognition and behaviour (EL), evolutionary biology of Drosophila (FC)), and particularly with an ERC-funded postdoctoral fellow and technician who will be exploring a similar framework. Formal training in data science, if required, will be available through modules on UCL’s Ecology and Data Science MSc. The student will also be trained in presentation skills, scientific writing and critique through lab meetings, department-based initiatives (e.g. CBER writing retreats), attending annual national conferences and at least one international conference.
The project will provide core training in evolutionary theory (alongside scientific leadership and collegiality) that will support careers in academia, but also neuroscience-relevant training, molecular biology, model insect husbandry and data science skills that will support many other career pathways within private and public sector. In addition, the generic skills gained (presentation skills, project management, people management) will evidence competencies for students who choose career trajectories in the scientific support sectors (publishing; communication) and further afield.