We probe the physical and functional architecture of memory across biological systems, spanning from microcircuits to cognition in humans and animal models. By combining neurophysiology and behavioural work in animal models and humans, our labs map how brain networks shape learning and related cognitive processes. This multi-level approach allows us to trace the continuum of memory from cellular and synaptic modifications up to complex human adaptive behaviour.

We sit at the rapidly evolving frontier where biological brain science meets artificial intelligence. Integrating Bayesian modelling, machine learning, and mechanistic interpretability, we explore how the brain computes under uncertainty, how biological rules can design fairer and more robust AI, and how deep learning can decode complex neural data. We also engage with urgent ethical considerations emerging at the intersection of NeuroAI and synthetic intelligence.

We translate insights from neuroscience, psychology and computer science into therapeutic and technological impact. Our work focuses on understanding the mechanisms underlying cognitive function and decline to advance diagnostics, biomarkers and treatments for neurodegenerative disorders. In parallel, we apply machine learning and explainable AI to improve digital health tools and treatment optimisation, alongside research into novel interventions for mental health.