NOW CLOSED - Imaging fast electrical circuit activity in the brain with EIT

4 year funded PhD studentship - Early start-date preferred but flexible up to September 2022 depending on the successful candidate. NOW CLOSED.

Primary Supervisor: Dr Kiril Aristovich
Subsidiary Supervisor: Dr Lorenzo Fabrizi
IndustrialSupervisor: Professor David Holder

A 4 year funded PhD studentship in Neuroscience, Physiology, Medicine or similar background is available in the UCL Department of Medical Physics and Biomedical Engineering in an interdisciplinary Bioengineering/Neuroscience group to work on imaging fast neural circuit activity in the brain in epilepsy with Electrical Impedance Tomography (EIT). 

Funding will be at least at the UCL minimum stipend (£17,609p.a) and home tuition fees. 

The successful candidate will join the UCL CDT in Intelligent, Integrated Imaging in Healthcare (i4health) cohort and benefit from the activities and events organised by the centre.

Project Background: 

Electrical Impedance Tomography is a new medical imaging method which enables 3D images of fast electrical circuit activity in the brain or nerves over milliseconds in 3D. It can also image slower changes over seconds, similar to fMRI. The hardware currently resembles an EEG system, similar to a small-form PC. This links to flexible silicone rubber electrode mats placed surgically on the brain or ultrathin depth electrode shanks. Images are acquired by averaging over a few minutes in response to a repeated stimulus such as a flashing light or epileptic seizures. These have a resolution of 1 msec in time and <0.2 mm in space in the brain. Its applications in Neuroscience have been pioneered by a bioengineering/neurophysiology research group in Medical Physics at University College London, headed by Prof. David Holder, a Neurologist and Biophysicist, and Dr. Kirill Aristovich, a Bioengineer. The group is interdisciplinary, with researchers with backgrounds in biology, medicine, physics and engineering. Proof of principle has been established in computer and physiological studies. The purpose of this project is to extend its use to improving the treatment of epilepsy by using EIT to image fast neural circuit activity in human patients.

https://www.ucl.ac.uk/medical-physics-biomedical-engineering/research/re...

Research aims: 
The goal is to produce images of fast and slow functional activity anywhere in the brain during normal cognition or epileptic seizures. It will be in anaesthetised rats and then in human subjects with epilepsy, with implanted intracranial electrodes or a novel EIT cycle helmet like electrode and magnetometer array under development. A secondary goal is to use the EIT to enable better targeted closed loop treatment of epileptic seizures using implanted deep brain electrodes. The researcher will work in a multidisciplinary team with an engineer. If successful, this could provide a groundbreaking new method for management of severe epilepsy. 

Application Details:

Applications are sought from outstanding candidates with a 1st class or upper second degree or MSc in neuroscience, biology or medicine but applications from students with other backgrounds relevant to this work are also welcome. It is only definitely funded for students who would qualify for UK PhD fees; it may include overseas fees for outstanding international applicants. It will suit candidates who and are interested in the application of cutting edge developments in technology to improve functional medical imaging to neuroscience and the treatment of neurological disease. This research will be based in Medical Physics at UCL, but include studies in human subjects at nearby hospitals in London. It is jointly funded by with industry.

How to apply:

Please complete the following steps to apply.

•    Send an expression of interest and current CV to: d.holder@ucl.ac.uk and cdtadmin@ucl.ac.uk
Please quote Project Code: 22003 in the email subject line.
•    Make a formal application to via the UCL application portal https://www.ucl.ac.uk/prospective-students/graduate/apply . Please select the programme code Medical Imaging TMRMEISING01 and enter Project Code 22003 under ‘Name of Award 1’ 

Application Deadline: 4th February 2022
If shortlisted, you will be invited for an interview.

Early start-date preferred but flexible up to September 2022 depending on the successful candidate.