Understanding the rules of life

Category: Standard Studentships

Risky decision-making: revealing the neural mechanisms of behaviour selection that maximize survival

Project No.2253

Primary Supervisor

Prof Kevin Staras- University of Sussex

Co-Supervisor(s)

Dr Arjuna Ratnayaka – University of Southampton

 

Summary

Understanding how animals make critical decisions to maximize their suvival changes is a major topic in neuroscience.

By exploiting new imaging, electrophysiological and cutting-edge behavioural analysis techniques it is now possible to examine this question at the level of the key control circuits in the CNS that actually compute these decisions.

This project will use the remarkably well-understood invertebrate system, Lymnaea, whose six principal behaviours (feeding, locomotion, reproduction, withdrawal, respiration, heart control) have been extensively characterised down to the level of the individual identified neurons that control them. This provides the opportunity to monitor the key survival-linked decision-making events ‘online’ as the system processes information about both its internal and external state.

The planned work program will focus on the open question of how animals compute responses when faced with conflicting threats e.g. predation and starvation. With increased hunger, a re-prioritization of behaviours towards food-finding must be balanced against other elevated risks. The behavioural and neural mechanisms that underlie this are fascinating but completely uncharacteristic. We now have preliminary evidence to indicate that a small circuit of neurons in the central nervous system represents the ‘master-controller’ – assessing the impacts and computing the risk. The project will test the idea that the same circuit also connects to the networks that control the animal’s principal behaviours and thus acts to set the priorities of action selection.

The research will be engaging, challenging and highly varied and the student will develop cutting-edge skills in targeted and high-density multi-electrode recording, and machine-learning based behavioural quantification. A key objective will be to establish new optical imaging methods based on voltage-sensitive dyes allowing remote readout of circuits across the brain. This expertise is highly-translatable and will set the PhD student up extremely well for a career in a broad range of neuroscience research disciplines. Support will be available from an experienced postdoctoral researcher funded on a parallel BBSRC grant who will work alongside the student. There is also wider expertise available from other postdoctoral researchers, and other PhD students in the lab, who use similar techniques in a variety of systems, including vertebrates. We fully expect the outputs from this project to be ground-breaking and high-impact, consistent with our recent work in related topic areas (Nat Commun 2016, 7:11793; Sci Adv 2018 eaau9180; Sci Adv 2018 eaat1357; Cell Reports 2020 30:2006-2017; Sci Adv 2023 eadd3403).