Understanding Brain Resilience, Vascular Health and early Neurodegeneration

About the project

About the Project Summary Why do some individuals remain cognitively healthy despite accumulating brain pathology and genetic risk, while others develop cognitive impairment and dementia? Our research aims to answer this question by investigating the mechanisms of brain resilience during ageing and early neurodegeneration. We combine multimodal neuroimaging, cognitive assessment, physiological measures of vascular health, genetic data, and large-scale longitudinal cohort studies to better understand how neural, vascular and genetic factors interact to influence cognitive ageing and dementia risk. Particular interests within the group include understanding how vascular health modifies genetic susceptibility to dementia, identifying biological pathways that promote resilience despite pathology, and developing imaging and computational markers that improve early detection and prediction of disease progression. Projects may focus on one or more of three closely related research themes: Brain resilience and the maintenance of cognition despite neurodegenerative pathology and genetic risk. Vascular contributions to cognitive ageing and dementia, including interactions between cardiovascular health and genetic susceptibility. Development of advanced statistical, computational, and AI methods for understanding disease heterogeneity and progression. Improving functional neuroimaging methods through the integration of vascular and neuronal measures. The student will work within an interdisciplinary research environment at the University of Cambridge, collaborating with neuroscientists, clinicians, computer scientists, engineers, and population health researchers. Depending on interests and background, there will be opportunities to develop projects centred on neuroimaging, vascular physiology, computational neuroscience, machine learning, or dementia research. Research Areas Brain resilience and cognitive maintenance despite neurodegeneration. Vascular and genetic influences on cognitive ageing and dementia risk. Multimodal neuroimaging of ageing, dementia, and brain health. AI and advanced statistical methods for disease prediction, subtyping, and biomarker discovery. Development of novel imaging and analytical approaches to improve measurement of brain function and resilience. Candidate Background The student should have experience in at least one quantitative area such as neuroscience, psychology, engineering, physics, mathematics, statistics, computer science, or a related discipline. Experience in programming (e.g. Python, R, MATLAB) and an interest in quantitative approaches to understanding brain health and disease are essential. (PhD and MPhil)

Research areas