Neuronal network model of interictal and recurrent ictal activity

This is the final version of the article. Available from American Physical Society via the DOI in this record.We propose a neuronal network model which undergoes a saddle node on an invariant circle bifurcation as the mechanism of the transition from the interictal to the ictal (seizure) state. In the vicinity of this transition, the model captures important dynamical features of both interictal and ictal states. We study the nature of interictal spikes and early warnings of the transition predicted by this model. We further demonstrate that recurrent seizures emerge due to the interaction between two networks.This work was partially supported by FET IP Project MULTIPLEX 317532. A.V.G. is grateful to LA I3N for Grant No. PEST UID/CTM/50025/2013. M.A.L. acknowledges the financial support of the Medical Research Council (MRC) via Grant No. MR/K013998/01. K.E.L. was supported by the Department of Anesthesiology at the University of Michigan and the National Institutes of Health, Grant No. RO1 GM098578