Imaging plays a key role in identifying Alzheimer’s disease (AD)
: different magnetic resonance imaging (MRI) modalities measure the brain network. Diffusion tensor imaging connects directed local neural fibre segments into neuronal tracts. Functional MRI connects pairs of regions with similar oxygen-based activity contrast. Grey matter networks connect cortical regions with similar morphology that subserve related functions. All these networks have provided exciting results as potential early AD biomarkers but these networks have not yet been combined into a single multi-layer brain connectivity model.
In this project, you will develop a multi-layer brain network model that integrates all these networks measured with MRI, to detect the earliest connectivity changes associated with AD. The aims of this project are 1)
to specify differences between patients in terms of the connections between these layers, 2)
to validate these connection changes as biomarkers of AD, by relating them to established biomarkers in an external cohort, and 3)
to make the brain network model and the new biomarkers available as open-source software.
You will work with the available multi-modal and multi-centre MRI dataset of EPAD
consortium and compute structural, functional and morphological brain networks.
- Find combination of networks that better separate participants based on clinical characteristics;
- Create a novel biological-informed biomarker of multi-modal network disruption using Insight46, an AD imaging study in the UK;
- Validate this biomarker in several external datasets and make the method available for other studies/clinical settings.
With your brain network model, you will detect changes in dynamic between functional and structural brain network properties in early, pre-symptomatic stages of AD.