Observing the sleep-wake regulatory system to improve prediction of seizures

We describe our ongoing efforts to understand the dynamics of the sleep-wake regulatory system to improve seizure prediction. Although mathematical models of its dynamics have been developed, the activity of this system is difficult to observe directly. Therefore we have developed a data assimilation framework that combines sparse measurements of the sleep-wake regulatory system together with a mathematical model of its dynamics to estimate the unmeasured variables. This toolset will allow us to understand the interaction between modulators of the state-of-vigilance and seizure susceptibility and may provide meaningful indicators of an impending seizure.