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

4 year funded PhD studentship - Deadline 8th December 2022

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

A 4-year funded PhD studentship in Engineering, Physics, Neuroscience, 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 (£19,062 p.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 and so treat seizures with intelligent closed loop deep brain electrical stimulation.

Research aims: 

The goal is to produce images of fast and slow functional activity anywhere in the brain during epileptic seizures or normal brain activity. 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. Images of circuit activity will inform dynamical models of seizure initiation and propagation. These will be used to inform disruption of pending seizure activity with intelligent closed loop electrical deep brain stimulation. If successful, this could provide a ground-breaking 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 engineering, physics, neuroscience 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. This studentship is jointly funded with industry

Application Deadline: 8^th December 2022

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: 23010 in the email subject line.
• Make a formal application to via the UCL Application Portal. Please select the programme code Medical Imaging TMRMEISING01 and enter Project Code 23010 under ‘Name of Award 1’ 

If shortlisted, you will be invited for an interview.