University of Sussex - PhD Neuroscience

Life Sciences PhD Neuroscience: Task responses in the mouse somatosensory cortex during flexible behaviour (2022)

What you get

This School-funded position covers Home tuition fees and a stipend at standard UKRI rates. Applicants with overseas fee status will need to fund the difference between Home and International tuition fees.

Type of award

Postgraduate Research

PhD project

Mammals have strikingly flexible and adaptable behaviour. When facing new surroundings or a new task, they can extract the situation’s underlying structure (e.g. the relationships between objects, locations and behavioural goals) and deploy this knowledge when confronting a new variation. An identical stimulus may have different meanings in different situations or locations, e.g., during foraging or nest building, and mammals readily make sense of these contextual effects. These traits form the basis of our own experience of the world, and understanding their neuronal underpinnings is a key goal in neuroscience.

The cerebral cortex is central to learning and performing flexible behaviour. Classical textbook understanding of cortex holds that sensory processing, decision making, and motor control are neatly parcelled out in distinct regions. In contrast, recent evidence from our lab and multiple others shows that, in naturalistic behaviours, neuronal activity reflecting sensory signals, decisions and actions interacts intricately in the cortex. For example, neurons in “sensory” cortex can reflect information about forthcoming actions, actual and expected rewards, or the animal’s location. There is a great need to understand how these “task responses” are organised and how they contribute to flexible behaviour.

The aim of this project is to understand how task responses in the somatosensory cortex vary with the task being performed, how they differ across cell types, and how they contribute to an animal’s behaviour. To this end the PhD candidate will develop behavioural tasks for mice, and record and manipulate activity in targeted groups of neurons while measuring task performance.

Our lab is developing novel tasks in which mice accumulate and use sensory evidence to decide between actions, e.g. during exploration of a maze. Mice are trained to recognise associations between sequences of stimuli and potential rewards. The student will track behaviour using deep-learning tools while monitoring activity in targeted neuronal subsets using two-photon microscopy (in head-fixed task versions) or electrophysiology (in freely moving mice). This approach will enable them to answer long-standing questions about how the brain flexibly converts sensory information into decisions.

Our lab provides an inclusive and supportive environment. Students interact with other members of the close-knit sensory neuroscience community and further opportunities for interaction and training are provided by the Sussex Neuroscience research programme, https://www.sussex.ac.uk/sussexneuroscience. Students in our lab have gone on to a diversity of careers inside and outside academia.

Eligibility

Ideal candidates will have recently received an MSc and/or a First or high 2:1 BSc in a relevant field, i.e. Neuroscience or a related, preferably quantitative, subject. Eligible applicants will hold a 2:1 BSc in a relevant subject. Candidates for whom English is not their first language will require an IELTS score of 6.5 overall, with not less than 6.0 in any section.

Deadline

How to apply

Please submit a formal application using our online system at www.sussex.ac.uk/study/phd/apply attaching a CV, degree transcripts and certificates, statement of interest and two academic references.

On the application system select Programme of Study – PhD Neuroscience. Please ensure you state the project title under funding and include the proposed supervisor’s name where required.

Contact us

For enquiries about the application process, contact Emma Chorley: lifesci-rec@sussex.ac.uk

For enquiries about the project, contact supervisor: m.maravall@sussex.ac.uk.

Web page: http://www.sussex.ac.uk/lifesci/maravalllab