A theoretical model for focal seizure initiation, propagation, termination, and progression

Abstract

We developed a neural network model that can account for the major elements common to human focal seizures. These include the tonic-clonic transition, slow advance of clinical semiology and corresponding seizure territory expansion, widespread EEG synchronization, and slowing of the ictal rhythm as the seizure approaches termination. These were reproduced by incorporating usage-dependent exhaustion of inhibition in an adaptive neural network that receives global feedback inhibition in addition to local recurrent projections. Our model proposes mechanisms that may underline common EEG seizure onset patterns and status epilepticus and postulates a role for synaptic plasticity in emergence of epileptic foci. Complex patterns of seizure activity and bi-stable seizure evolution end-points arise when stochastic noise is included. With the rapid advancement of clinical and experimental tools, we believe that this can provide a roadmap and potentially a testbed for future explorations of seizure mechanisms and clinical therapies.