IntroductionExisting dynamical models can explain the transmigration mechanisms involved in seizures but are limited to a single modality. Combining models with networks can reproduce scaled epileptic dynamics. And the structure and coupling interactions of the network, as well as the heterogeneity of both the node and network activities, may influence the final state of the network model.MethodsWe built a fully connected network with focal nodes prominently interacting and established a timescale separated epileptic network model. The factors affecting epileptic network seizure were explored by varying the connectivity patterns of focal network nodes and modulating the distribution of network excitability.ResultsThe whole brain network topology as the brain activity foundation affects the consistent delayed clustering seizure propagation. In addition, the network size and distribution heterogeneity of the focal excitatory nodes can influence seizure frequency. With the increasing of the network size and averaged excitability level of focal network, the seizure period decreases. In contrast, the larger heterogeneity of excitability for focal network nodes can lower the functional activity level (average degree) of focal network. There are also subtle effects of focal network topologies (connection patterns of excitatory nodes) that cannot be ignored along with non-focal nodes.DiscussionUnraveling the role of excitatory factors in seizure onset and propagation can be used to understand the dynamic mechanisms and neuromodulation of epilepsy, with profound implications for the treatment of epilepsy and even for the understanding of the brain.

Abnormal brain networks are likely to be the trigger of seizure generation of epilepsy. Clarifying the effects of abnormal structures on brain function is of great significance for brain diseases. Due to the complexity of brain networks, the relationship between structural and functional brain networks is not yet well-defined. In this letter, we apply a generate model depicting the interrelationship between structural and functional connectivity, to reproduce similar resting whole brain networks and focal epileptic networks through networks with different topologies. It is found that only the underlying network connected with scale-free structure can reproduce the properties of focal epilepsy network, while the resting network has a small probability of reproduction under both the small-world network and the scale-free network. In particular, this reproduction capacity is immune to the nodal distance modes of the underlying network. This suggests that there exits severe heterogeneity in the focal epilepsy network similar to the scale-free network, which may facilitate the clinical structural inference of seizure location.