→ Emerging line: AI-inspired biomarkers of brain structure and function

Emerging Line of the group: “Translational Imaging Biomarkers”

Understanding how the different scales of the brain interact to effectively function, and how disruption of that interaction can lead to neurodegenerative diseases, is a formidable challenge. Importantly, in an increasingly ageing society, this understanding can have a significant impact in developing methods to accurately diagnosing those neurodegenerative disease earlier than is available to conventional detection methods. To address this, the aim of this emergent research line is to leverage data science and mathematical tools to gain a deeper insight into the inner workings of the brain, both at micro (e.g. molecular dynamics and synaptic plasticity) and at macro scales (e.g. glial cell behaviour and brain inflammation).

Specifically, the main aim of the group, financed by a La Caixa Junior Leader project, will be to discover meaningful biomarkers by leveraging dynamical systems theory and machine learning alongside advanced non-invasive magnetic resonance imaging techniques. By combining experimental and theoretical approaches, we aim to work in an interdisciplinary fashion to develop computational models to pinpoint these biomarkers early in life, offering a glimpse into the potential onset of disorders such as Alzheimer’s and multiple sclerosis.

Further research topics, in collaboration with partners at the Uniklinikum Bonn and the Okinawa Institute of Technology, Japan, include building mathematical models to explore the molecular basis of synaptic plasticity and its role in memory formation, investigating the emergence of efficient communication between animals using machine learning, and developing an open-source, graphical user interface-based tool for the swift, reproducible analysis of calcium images of synapses and dendrites.