2023-24-project-catalogue

###Development of MRI-compatible Graphene-based Probes for Rodent and Human Electrophysiology

Project ID: 2228bd1229 (You will need this ID for your application)

Research Theme: Healthcare Technologies

UCL Lead department: Queen Square Institute of Neurology

Department Website

Lead Supervisor: Louis Lemieux

Project Summary:

A common treatment for patients with severe, drug-resistant epilepsy is to surgically remove the abnormal brain tissue responsible for recurring seizures. The identification of the focus can be achieved by recording EEG within the brain using electrodes implanted surgically. However, in many cases it is still not easy to discover which part of the brain to remove partly because the electrodes currently used were developed prior to the MRI era, and contain a large amount of metal which results in large artefacts in MR images acquired after their implantation to verify their location. These artefacts obscure the electrodes’ location, making it difficult to visualise the brain tissue around them, a limitation with important clinical implications. Metal-based electrodes within the MR environment also pose several safety concerns that arise from interactions between the probe and the fields used in MRI. We recently showed that a new type of electrode, called graphene-based (Graphene Solution-Gated Field-Effect Transistors, or gSGFET) probes, have several advantages over existing electrodes, including a much reduced amount of metal that can interfere with MRI and the ability to record EEG in a radically new way due to their electronic design. In this project gSGFET probe design will be modified by the addition of features that are specifically conceived to make them visible and localisable with great precision in MRI images. We will perform experiments to improve and validate the new design, with the aim of obtaining sub-millimetric accuracy. We will then demonstrate the probes’ new capabilities in terms of localization and visualization. The aim of the PhD will be to devise a scheme to validate the localization accuracy that works for the upscaled, human versions of the probes.