The fast without the spurious: developing a system for robust and rapid simultaneous EEG-fMRI measurements

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To increase our understanding of how the brain works and how it goes wrong in people with neurological conditions such as epilepsy we need to develop better systems for making measurements of brain activity. Electroencephalography (EEG) is an important modality in clinical and experimental neuroscience capable of measuring electrical changes occurring with sub-millisecond temporal resolution and a spatial resolution of centimetres while functional Magnetic Resonance Imaging (fMRI) can map haemodynamic changes over the entire the brain at a time-scale of seconds and spatial resolution of a few millimetres or better. Therefore together they can perform measurements across a greater range of brain activity occurring either at faster temporal or smaller spatial scales. However, during simultaneous EEG-fMRI acquisitions these both methods signal are degraded by noise related to motion, thereby significantly limiting the sensitivity of this type of study so far.The purpose of this application is to build a robust system that can perform these simultaneous EEG and fMRI measurements of brain activity. To achieve this goal we will integrate new fast fMRI pulse sequences because images obtained in shorter time intervals are intrinsically less motion sensitive (like a faster shutter speed on a camera). Also better modelling of motion will be possible if we obtain more images per unit time because we can better separate and model the different sources of signal and noise that occur in different frequency ranges. In addition, we will optimise motion detection and prospective motion correction (PMC) using a camera system that tracks the subject's motion and updates the image acquisition process so that patient motion is supressed. When using these improvements to fMRI data acquisition we will need to develop novel EEG artefact correction methods for simultaneous in-scanner EEG recording which currently rely on the repetitive nature of the artefact in time. Both motion and PMC are likely to make the artefact more variable and so will require the development of novel correction methods. Once we have developed this system we will apply it to ten patients with hard to treat epilepsy from Great Ormond Street Hospital who are being assessed for epilepsy surgery. This assessment aims to identify the epileptic brain regions and EEG-fMRI is a tool to help obtain this information. We will compare our current standard EEG-fMRI protocol which often suffers from degradation due to motion (particularly in young children) to our new robust EEG-fMRI incorporating PMC, fast fMRI and improved EEG artefact correction.