Abstracts

Rationale: Seizures are classically thought to involve the hypersynchrony of cortical activity although the precise, physiological underpinning of this phenomenon remains poorly understood. Recent work has shown that the seizure itself contains a complex dynamical structure. This is obvious during visual examination of macroscopic voltage recordings from patients with epilepsy and has been demonstrated with a variety of signal processing techniques. Describing in quantitative detail the voltage activity of seizures may lead to a more robust understanding of their propagation, maintenance, and termination. Methods: We examine recordings from subdural electrode arrays (electrocorticogram or ECoG) of patients with pharmacoresistant epilepsy. We apply a simple coupling measure to define the functional connectivity between electrode pairs, and utilize a principled statistical approach to establish maps of the cortical network topology. We then analyze these maps using graph theoretical techniques. Results: We find that network topologies change dramatically at seizure onset and evolve in characteristic ways. In particular, we show that consistent network topologies emerge during a seizure, and that these topologies appear consistent between seizures of the same patient. Furthermore, we find that the seizure is, at onset, characterized by a large interconnected network, but that this structure fragments substantially during seizure propagation only to coalesce again before seizure termination. Conclusions: We propose that this deeper understanding of ictal network topologies may help guide future surgical treatments of epilepsy as well as provide information relevant for principled approaches to stimulation induced seizure interruption.