Using advanced imaging and novel mathematical approaches, you will identify spatio-temporal brain networks that show altered dynamics in adults with genetic risk for Alzheimer’s disease. This PhD project will provide grounding in network Neuroscience — an evolving field using complex network theories to study the brain across multiple scales and modalities.
To reduce the burden of cognitive decline in neurodegeneration, a key challenge is to understand genetic influences on brain functions at the preclinical stage. This PhD focuses on the strongest genetic risk factor for Alzheimer’s disease: the ε4 allele of the APOE gene. We will establish, decades before the onset of clinical symptoms, whether young APOE-ε4 carriers show selective changes in brain network dynamics compared to non-carriers. Novel findings of network alternations in young APOE-ε4 carriers could help develop preventative interventions in early life. Our innovative data-driven approach combines:
1. Unique resources from a longitudinal birth cohort
This project links to a multi-centre study, which recruits over 200 APOE-ε4 carriers and non-carriers for comprehensive brain-imaging and cognitive testing.
2. Cutting-edge brain-imaging
This project will integrate advanced multi-modal imaging to quantify brain networks: (1) high resolution (200 µm) structural MRI for precise segmentation of brain regions; (2) high-gradient diffusion-weighted MRI for modelling tissue microstructure and structural connectivity; and (3) high-field 7T functional MRI (fMRI) for measuring temporal networks during rest and movie viewing.
3. Exciting opportunities for new computational approaches
This project will use fMRI data during rest to quantify brain functional connectivity as time-varying networks. This allows measuring whole-brain functional connections as well as their dynamic changes over time. We will then use the temporal-topological structure of these networks to identify network dynamics that show alternations in APOE-ε4 carriers. By relating the network measures to fMRI data acquired during free-viewing of movies, this project will further identify the emergence of the atypical network dynamics essential to the known behavioural phenotype in APOE-ε4 carriers, thus contributing new knowledge on the systems level mechanisms by which genetic factors influence cognition.
Further added value includes (1) a supervisory team with interdisciplinary expertise in imaging (Cardiff University) and network dynamics (University of Exeter and University of Bath), (2) research visits to our international collaborators in the USA and Canada and (3) the strong feasibility from being linked to a large ongoing study, including support from geneticists and fieldworkers.
We encourage candidates from different disciplines (e.g., cognitive/computational neuroscience, psychology, computer science, engineering, mathematics or physics). You will receive multidisciplinary training in cognitive neuroscience, brain imaging and computational modelling. You will be based at Cardiff University Brain Research Imaging Centre (CUBRIC) and be part of a thriving research team. CUBRIC houses state-of-the-art brain imaging facilities and world-leading expertise, with 4 human MRI systems (2 x Siemens Prisma, 1 x Siemens Connectom, 1 x Siemens 7T), MEG, EEG, TMS, tDCS, clinical research units and testing labs. Further details can be found on our webpage (http://sites.cardiff.ac.uk/cubric
This PhD studentship is funded by the GW4 BioMed MRC Doctoral Training Partnership (https://www.gw4biomed.ac.uk
The studentship will commence in October 2020 and will cover your tuition fees (at UK/EU level) as well as a maintenance grant. In 2019-20, the maintenance grant for full-time students was £15,009 per annum. The studentship will also include a £5,000 research training support grant from the Doctoral Training Partnership as a contribution towards consumables. They also receive a computer, office space and access to courses offered by the University’s Doctoral Academy and become members of the University Doctoral Academy.