☳ Neuroscience and Ageing Research
My research interests focus on the neuroscience of ageing, combining insights from biomedical sciences, exercise science, computational methods, and applied mathematics. This interdisciplinary effort facilitates a more comprehensive understanding of how age-related changes in brain structure and function are linked to cognitive decline. The findings contribute to the development of strategies to support cognitive health and reduce the risk of neurodegenerative conditions.
Biomedical Mechanisms of Brain Ageing
My work in this area focuses on the biological processes that contribute to brain ageing, with particular attention to cellular, molecular, and systemic mechanisms. I investigate key factors (e.g., oxidative stress, neuroinflammation, cerebrovascular dysfunction, glymphatic impairment) and their roles in age-related cognitive decline and neurodegenerative conditions (i.e., Alzheimer’s disease). The overarching aim is to identify early biomarkers and mechanistic pathways that may inform prevention and intervention strategies for healthy brain ageing.
Exercise Neuroscience and Cognitive Health
My work in this area examines how physical activity influences brain health and cognitive function in older adults. I explore the effects of structured exercise interventions (e.g., aerobic training, resistance exercise, mind–body practices such as Tai Chi) on neuroplasticity, executive function, mood, and sleep regulation. The research integrates behavioural assessments, actigraphy, and neuroimaging to evaluate exercise as a non-pharmacological approach for enhancing cognitive resilience and overall brain function in later life.
Computational Neuroscience and Neurotechnologies in Ageing
My work in this area involves the application of computational methods and neurotechnological tools to investigate age-related changes in brain structure and function. I work with multimodal datasets (e.g., MRI, EEG, actigraphy) and apply analytical techniques (e.g., machine learning, signal processing, network analysis) to identify neural patterns, model trajectories of decline, and evaluate the impact of interventions. The aim is to enhance understanding of brain ageing through robust, data-driven approaches.
Mathematical Neuroscience and Theoretical Modelling of Ageing
My work in this area centres on the development of mathematical models to represent and simulate the complex dynamics of brain ageing. I apply formal methods (e.g., dynamical systems, graph theory, probabilistic modelling) to explore neural connectivity, physiological regulation, and cognitive trajectories. These models are grounded in empirical data (i.e., drawn from observational and interventional studies) and aim to offer theoretical insight that supports hypothesis-driven research in the neuroscience of ageing.
