A bistable computational model of recurring epileptiform activity as observed in rodent slice preparations

REACTIVE CONTROL OF EPILEPTIFORM DISCHARGES IN REALISTIC COMPUTATIONAL NEURONAL MODELS WITH BISTABILITY

We aim to derive fully autonomous seizure suppression paradigms based on reactive control of neuronal dynamics. A previously derived computational model of seizure generation describing collective degrees of freedom and featuring bistable dynamics is used. A novel technique for real-time control of epileptogenicity is introduced. The reactive control reduces practically all seizures in the model. The study indicates which parameters provide the maximal seizure reduction with minimal intervention. An adaptive scheme is proposed that optimizes the stimulation parameters in nonstationary situations.

Is slack an intrinsic seizure terminator?

Understanding how epileptic seizures are initiated and propagated across large brain networks is difficult, but an even greater mystery is what makes them stop. Failure of spontaneous seizure termination leads to status epilepticus-a state of uninterrupted seizure activity that can cause death or permanent brain damage. Global factors, like changes in neuromodulators and ion concentrations, are likely to play major roles in spontaneous seizure cessation, but individual neurons also have intrinsic active ion currents that may contribute. The recently discovered gene Slack encodes a sodium-activated potassium channel that mediates a major proportion of the outward current in many neurons. Although given little attention, the current flowing through this channel may have properties consistent with a role in seizure termination.