Replay of Interictal Sequential Activity Shapes the Epileptic Network Dynamics

Abstract

Both the imbalance of neuronal excitation and inhibition, and the network disorganization may lead to hyperactivity in epilepsy. However, the insufficiency of seizure data poses the challenge of elucidating the network mechanisms behind the frequent and recurrent abnormal discharges. Our study of two extensive intracranial EEG datasets revealed that the seizure onset zone exhibits recurrent synchronous activation of interictal events. These synchronized discharges formed repetitive sequential patterns, indicative of a stable and intricate network structure within the seizure onset zone (SOZ). We hypothesized that the frequent replay of interictal sequential activity shapes the structure of the epileptic network, which in turn supports the occurrence of these discharges. The Hopfield-Kuramoto oscillator network model was employed to characterize the formation and evolution of the epileptic network, encoding the interictal sequential patterns into the network structure using the Hebbian rule. This model successfully replicated patient-specific interictal sequential activity. Dynamic change of the network connections was further introduced to build an adaptive Kuramoto model to simulate the interictal to ictal transition. The Kuramoto oscillator network with adaptive connections (KONWAC) model we proposed essentially combines two scales of Hebbian plasticity, shaping both the stereotyped propagation and the ictal transition in epileptic networks through the interplay of regularity and uncertainty in interictal discharges.