As FNRS Research Follow, Lucas Stordeur is interested in reconfiguration of biological neural networks using closed-loop stimulation
His background
In July 2025, Lucas Stordeur has obtained a degree in biomedical civil engineering, specializing in Neural Systems, summa cum laude with the congratulations from the jury. During his final year of my master's degree, he did an internship at Imec (Interuniversity microelectronics centre), where he worked on in vitro electrophysiology experiments conducted on neuronal cultures. At the same time, he devoted his master thesis, supervised by Professors Pierre Sacré and Steve Majerus, to modeling a psychology task to study working memory. These two interdisciplinary projects greatly strengthened his interest in scientific research and made him want to pursue this path through a PhD.
In October 2025, as FNRS research follow, Lucas began my PhD at the « Neuroengineering » Laboratory at the University of Liège, directed by Professors Guillaume Drion, Alessio Franci (co-supervisor), and Pierre Sacré (supervisor), while continuing to collaborate with Imec.
His research
Lucas Stordeur’s doctoral project focuses on the reconfiguration of biological neural networks through principled closed-loop stimulation.
In certain pathologies such as epilepsy, Parkinson's disease, or depression, pharmacological treatments are sometimes ineffective. An alternative that has been used for several years is neurostimulation. This involves stimulating targeted areas of the brain in order to alleviate symptoms. Although often effective, this approach remains imperfect in the long term and can cause side effects.
The goal of his project is to exploit synaptic plasticity to remodel neural networks, allowing them to transition from a pathological state to a healthy functional state. Beyond this therapeutic application, this work also aims to improve our understanding of the mechanisms of synaptic plasticity at the network level, while paving the way for applications of these mechanisms in the field of artificial intelligence.
To control the reconfiguration of biological neural networks, the project combines the development of experimental protocols with the design of modeling tools. In this context, HD-MEAs (High-Density Microelectrode Arrays), composed of thousands of electrodes integrated on a CMOS (Complementary Metal Oxide Semiconductor) chip, offer a powerful means of recording the electrical activity of the network and stimulating it at a subcellular level. Combined with control theory and a closed-loop approach, these devices make it possible to adjust the electrical stimulation modalities according to the network's activity, paving the way for precise control of its reconfiguration.
