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Neurocognitive profile of healthy ageing

Primary Supervisor: Dr Pia Rotshtein, School of Psychology

Secondary supervisor: Akram Hossieni

PhD project title: Neurocognitive profile of healthy ageing

University of Registration: University of Birmingham

Project outline:

Background: Variability is a hallmark of ageing. While some in their 70ies has the capacity and resources to lead the world, others experience high frailty and struggle with completing even simple daily activities. BrainAge (Frank & Gaser, Front Neurol. 2019 10:789) is one emerging framework that aimed to bridge the gap between individual chronological age and their cognitive abilities. BrainAge approach uses multivariate methods to model chronological age using features typically extracted from MRI T1-weighted images. A Brain-Age of an individual is computed as the distance of their MR features from the model prediction based on their chronological age (e.g. BrainAge gap). However, T1-weighted images are primarily affected by levels of atrophy. Atrophy is likely predated by multiple functional pathological processes. Examining processed that pre-date atrophy will aid the understanding of causes for neural aging and death.

The current project aims to identify neuroimaging markers associated with cognitive abilities in healthy aging, with a specific focus on next generation of neuroimaging marker. We will specifically focus on four MRI markers that have been previously associated with mild and severe cognitive impairments as manifested in dementia (Ruan et al., BMC Geriatric, 2016 16:104): hypo-prefusion, increase in Iron deposition, increase in blood brain barrier leakage and reduced functional connectivity within and across resting state networks.

Methods: In the first project, student will work with an existing database (Can-Cam, https://camcan-archive.mrc-cbu.cam.ac.uk/dataaccess/). Can-Cam is an open sources dataset which contain cognitive, demographic and MRI measures from over 600 individuals aged 18-90 years old. The aim of this project will be to create BrainAge models. Two models will be created: one based on T1-wieghted images and a second based on resting state data. The relevance of BrainAge to health and cognition will be assessed using cognitive and health data available from Can-Cam.

In the second project, student will join an ongoing project: the ‘Next Generation Imaging for Precision Medicine in Cognitive Disorders’ (PI: Hosseini, coPI: Rotshtein). The project collect behavioral, clinical and imaging data from mild cognitively impaired and neurologically healthy individual. Imaging data is collected using 3T and 7T scanners. The student will use this data to assess whether the new MR markers can improve predictions of cognitive abilities made by the BrainAge alone.

BBSRC Strategic Research Priority: Integrated Understanding of Health:Ageing

    Techniques that will be undertaken during the project:

    Data acquisition:

    • 3T MRI: T1-weighted (structural MRI), resting stated fMRI, quantitative susceptibility mapping (Iron deposition), Arterial Spin Labelling, dynamic contrast-enhanced MRI (BBB leakage).
    • 7T MRI: T1-Weighted images (structural MRI), quantitative susceptibility mapping (Iron deposition)
    • Cognitive ability: Birmingham Cognitive Screen,
    • Computerised tasks from Cam-Can for comparison.
    • Self -reported questionaries demographic and health

    Contact: Dr Pia Rotshtein, University of Birmingham