For adults and children with focal epilepsy, surgical removal of the brain region responsible for seizure generation is the only possible complete cure. This can remove dependence on medication, and dramatically improve quality of life. Surgical success relies on accurate localisation of the generators of epileptic activity via imaging techniques such as MRI and electroencephalography (EEG). These two key modalities can be combined; epileptic activity measured in EEG is used as a model of expected changes in functional MRI timeseries. This provides a high spatial resolution map showing the areas with signal changes associated with the epileptic activity that has been shown to be a useful localisation method(1). However, EEG-fMRI is limited by fMRI sensitivity that typically measures signal changes of 1-2%. Ultra-high field 7T MRI offers a solution because fMRI signal changes are substantially increased to 5-10% and this could dramatically improve the technique’s sensitivity and spatial specificity. However, simultaneous EEG-fMRI at 7T is a significant technical challenge.
This project will redesign and test EEG for use at within 7T MRI. This will allow its use in patient populations such as Epilepsy as described above, but also enable a wide range of neuroscience applications including the study of sleep at 7T. This will include design and testing to investigate tissue heating and EEG system design solutions to mitigate this risk. Further, the impact of each modality on the other in terms of data quality will be characterised and the EEG system hardware configuration redesigned to optimise signal quality. This may also encompass potential algorithmic development to improve image quality, including AI methods to improve upon current denoising approaches. Having optimised 7T EEG-fMRI an initial pilot investigation of its utility in epilepsy is envisaged.
This project benefits from being sponsored by and involving close collaboration with an industry partner (Brain Products, GmBH) the market leader in research EEG-fMRI equipment. In addition to providing hardware and expertise via PhD supervision they will also provide a unique opportunity for a placement embedded within their technical team. This will be designed to maximise the students experience and development with opportunities to work with the Brain Products team in Germany.
The student will have access to the extensive training resources provided by Brain Products for EEG-fMRI in addition to the technical and scientific support teams. This project will provide extensive training, opportunities, and technical knowledge in human brain imaging (MRI) and electrophysiology, signal processing and the application of machine learning and AI in this domain. The applicant will also gain experience of clinical neuroscience.
This project can suit a wide range of potential backgrounds from highly numerate and/or computer literate backgrounds including physics, engineering, maths, computer science or neuroscience.
Department:
School of Biomedical Engineering and Imaging Sciences
Funding:
The MRC DTP only offer 4-year fully funded studentship awards including a stipend, tuition fees, research training and support grant (RTSG) and a travel and conference allowance.
Stipend: The rate for academic year 22/23 is £22,168. This is a tax-free payment made to the student.
Tuition fees: The studentship award covers the full tuition fee amount.
Research training and support grant (RTSG): £6,400 per year. Can also be known as bench fees, which is a contribution towards consumable costs of training research students.
Travel and conference allowance: £300 per year. This is a contribution to the costs of attending scientific conferences, workshops, or visits to collaborators.
Flexible Supplement: Available to students funded by the MRC, this can help fund a wide range of research and training activities.
Funding source: This project is co-funded by the MRC and the Industry Partner Brain Products GmbH.
Application Web Page:
Full details on how to apply here: https://kcl-mrcdtp.com/apply/application-process/
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