Mesoscale MRI in the living brain with simultaneous multi-contrast encoding

Magnetic resonance imaging (MRI) is a crucial tool for examining the living brain in health and disease non-invasively. However, we cannot achieve the kind of spatial resolution which is available with microscopes: neuroimaging data typically has voxel dimensions of approximately one millimetre, and anything much smaller than this is difficult to resolve - let alone quantify accurately - due to motion during acquisition. This misses important opportunities for capturing early changes in neurodegenerative diseases (e.g. Parkinson’s, Alzheimer’s), where pathology is evident in sub-millimetre nuclei tens of years before symptoms emerge. In this proposal, I put forward a series of technical developments in the way that we can acquire and reconstruct images from MRI scanners. They take advantage of signals that are usually ignored or discarded during the acquisition process, and with an understanding of the underlying physics, turn them into free additional sources of information about tissue microstructure and brain motion. I plan to exploit this additional information to develop new approaches which make MRI more efficient and motion-robust, before applying these in some of the world’s most powerful systems. With this, I aim to extend the achievable spatial resolution of quantitative MRI in the living brain to the limits of feasibility.