The problem

Epilepsy affects people of all ages and backgrounds, with approximately 50 million people worldwide, making it one of the most common neurological disorders.

We still cannot reliably identify who will develop epilepsy after a first seizure or another brain insult, nor can we predict the course of disease or response to treatment. At the same time, epilepsy can arise from very different biological causes. The same alteration may cause severe epilepsy in one person and little or no disease in another.

This suggests that the cause alone does not determine the outcome. Different molecular, cellular and structural changes can converge on a similar epileptic tissue state. Understanding this convergence is the central question of my research.

What we want to understand

At the Kobow Lab, we study epilepsy as a systems problem. Rather than asking which individual mechanism causes epilepsy, we ask how different biological processes interact and how these interactions change the state of brain tissue over time.

Our current work focuses on processes that act across different spatial and temporal scales, including epigenetic ageing, circadian regulation and tissue mechanics. We are particularly interested in changes that precede spontaneous seizures and may distinguish a brain that will develop epilepsy from one that remains resilient.

This work is guided by two concepts. Degeneracy describes how different biological configurations can produce the same functional outcome, whereas convergence refers to the observation that distinct disease trajectories may nonetheless lead to shared, measurable biological features. Together, they provide a framework for studying epilepsy across different aetiologies without assuming a single (driving) disease mechanism.

What we want to achieve

Our research has two connected aims.

Understanding – We want to identify the biological principles by which different perturbations converge on an epileptic tissue state and determine which changes precede, accompany, or follow the development of epilepsy.

Translation – We want to make these states measurable in patients. By combining molecular biomarkers with quantitative pathology, EEG, and imaging, we aim to improve diagnosis and, importantly, prognosis. Who is developing epilepsy? How is the disease likely to progress? Which patients are biologically similar despite different clinical diagnoses?

How we work

Human tissue is the starting point. Experimental models are used to test mechanisms identified in human disease. Whenever possible, different measurements are obtained from the same tissue or patient rather than compared across separate cohorts. This allows relationships between molecular, structural, and functional changes to be measured directly.

Patient heterogeneity is not treated simply as noise. It is part of the biological problem. Quantitative / Digital pathology and computational analysis / “Artificial Intelligence” among many other methods allow us to identify patterns across cells and tissue that cannot be captured by visual assessment alone.

We connect molecular changes with tissue organisation and function, and translates these relationships into measurable markers of disease.

We call this approach Systems Neuropathology. Not what the tissue looks like (classical neuropathology), and not only what is altered in it (molecular neuropathology), but what state the brain is in and how it got there. The aim is simple – to understand epilepsy as a biological system and network disease and use that understanding to improve diagnosis and prognosis.