Brain dynamics are never still. The same network behaves differently from one moment to the next, over the course of a seizure, across a night's sleep, through development, and across cycles that play out over days or weeks. Much of what matters clinically lives in this change over time: whether a seizure will stop, when the next one is likely to come, how a developing brain settles into stable patterns. A snapshot rarely tells the whole story.

In this research stream we treat time as the central variable. We model how dynamics evolve — from the fast collapse of a seizure into benzodiazepine resistance, to the slow drift of seizure risk over months — using tools from nonlinear dynamics, including attractor models and the study of long-term cycles. By tracking how patterns build, persist, and break down, we ask not just what the brain is doing, but where its dynamics are heading — and how reliably that can be anticipated.