About the Project
Distinguishing self-generated from externally generated sensory input is crucial for guiding behaviour [1]. This ability is thought to be impaired in conditions such as schizophrenia, where sensory disturbances may arise from a failure to correctly attribute sensory input to its self-generated causes. Yet our basic understanding of how the brain supports this perceptual ability remains at an early stage.
The neocortex is emerging as a key brain area underpinning this ability. Neurons in layer 2/3 of the visual cortex have recently been shown to signal unexpected perturbations in the visual motion generated by locomotion, and these responses depend acutely on visuomotor experience and local plasticity [2–4]. How the activity of these neurons supports perception and behaviour remains unclear, however, in part because no method has been established for probing the ability of mice to distinguish self-generated from externally generated visual motion.
In this project, we will develop a new virtual reality task to measure how mice distinguish self-generated from external sources of visual motion. Once established, we will use it to determine how experience of self-generated motion shapes the capacity of both mice and the visual cortex to distinguish sources of motion.
Specifically, we aim to:
- Establish a behavioural task in which mice detect moving objects, comparing performance under open-loop and closed-loop conditions to determine the perceptual benefit conferred when background visual motion is predictable from behaviour.
- Use two-photon imaging and computational approaches to determine how neurons in the visual cortex support task performance by combining self-motion and visual motion input to form distinct representations of self-generated and externally generated motion.
- Assess how long-term visuomotor experience affects (a) the ability of mice to perform the task, and (b) the cortical representation of external motion.
Across the project, the student will acquire general skills essential to conducting and disseminating research, alongside specialist training in designing and implementing head-fixed virtual reality behavioural tasks, performing in vivo two-photon imaging of neuronal activity, and applying computational approaches to infer how neuronal representations develop to support behaviour.
This 4 year PhD project is part of a competition funded by EASTBIO BBSRC Doctoral Training Partnership (DTP). Detailed guidance on the application process, and the EASTBIO Application and Reference Forms can be found at How to Apply | Biology.
Please send your completed EASTBIO Application Form along with a copy of your academic transcripts (as a pdf) to INCR.Postgraduate@ed.ac.uk You should also contact your referees and ask them to submit their references (on the EASTBIO reference form template) to INCR.Postgraduate@ed.ac.uk by the application deadline of 16th November 2026.
Funding Notes
This opportunity is open to UK and international students and provides funding covering stipend and UK level tuition fees. The University of Edinburgh covers the difference between home and international fees meaning that the EASTBIO DTP offers fully-funded studentships to all appointees. There is a cap on the number of international students the DTP recruits. It is therefore important for us to know from the outset which fees status category applicants will fall under when applying to our University.
Please refer to UKRI website and Annex B of the UKRI Training Grant Terms and Conditions for full eligibility criteria.
References
- Crapse, T. B. & Sommer, M. A. Nat. Rev. Neurosci. 9, 587–600 (2008).
- Jordan, R. & Keller, G. B. eLife 12, RP85111 (2023).
- Jordan, R. & Keller, G. B. Neuron (2020) doi:10.1016/j.neuron.2020.09.024.
- Vasilevskaya, A., Widmer, F. C., Keller, G. B. & Jordan, R. Cell Rep. 42, 112096 (2023).