Microglia Dynamics
from Development to Disease

Mathematical modelling, Bayesian inference, and neuroimmunology

Microglia are highly dynamic cells whose behaviour changes substantially across development, homeostasis, ageing, and disease. In this project, I develop mathematical and computational models to investigate how microglial populations colonise the brain during postnatal development and subsequently maintain a stable homeostatic state.

A central part of the work focuses on combining mechanistic modelling with in vitro and in vivo experimental data. Bayesian inference is used to estimate biologically meaningful parameters and quantify uncertainty, allowing us to distinguish between competing hypotheses on the mechanisms regulating microglial population dynamics. Particular attention is devoted to the characterisation of cell-cycle progression, proliferation, cell loss, motility, and spatial organisation, as well as to the feedback mechanisms through which microglia respond to their local environment and regulate their own population.

Beyond population homeostasis, I am interested in connecting these models to changes in microglial functionality. This includes studying how alterations in microglial states and regulatory feedback may contribute to neurodegenerative processes and how microglia interact with pathological microenvironments.

A further research direction concerns the role of microglia in glioblastoma and cancer immunotherapy, where tumour cells, resident immune cells, and therapeutic interventions form a highly complex interacting system. Mathematical models provide a way to investigate how microglial phenotypes may influence tumour progression and therapeutic response, and to identify mechanisms that could potentially be exploited in treatment design.

This work is carried out in collaboration with Prof. Amanda Sierra and the Laboratory of Glial Cell Biology in Health and Disease at the Achucarro Basque Center for Neuroscience.

Main themes: population dynamics · Bayesian inference · parameter estimation · cell-cycle modelling · motility · feedback regulation · neurodegeneration · tumour–immune interactions · glioblastoma immunotherapy