Abstract
We investigate how changes in network structure can lead to pathological oscillations similar to those observed in epileptic brain. Specifically, we conduct a bifurcation analysis of a network of two Jansen-Rit neural mass models, representing two cortical regions, to investigate different aspects of its behavior with respect to changes in the input and interconnection gains. The bifurcation diagrams, along with simulated EEG time series, exhibit diverse behaviors when varying the input, coupling strength, and network structure. We show that this simple network of neural mass models can generate various oscillatory activities, including delta wave activity, which has not been previously reported through analysis of a single Jansen-Rit neural mass model. Our analysis shows that spike-wave discharges can occur in a cortical region as a result of input changes in the other region, which may have important implications for epilepsy treatment. The bifurcation analysis is related to clinical data in two case studies.
Highlights
Epilepsy is regarded as the second most common neurological disease after stroke
Epilepsy surgery is a treatment option for patients whose seizures continue despite pharmacological interventions
Computational modeling studies are an alternative to understand epilepsy at a network level and generate new hypotheses regarding the basic mechanisms that lead to seizures
Summary
The hallmark of epilepsy is recurrent unprovoked seizures, during which a network of the brain is hyper-excitable [1]. Epilepsy surgery is a treatment option for patients whose seizures continue despite pharmacological interventions. There is a strong research effort directed towards alternative methods to control seizures. In order to develop new robust therapies, there is a need to understand the mechanisms that lead to seizures. This has proven to be a difficult problem to unravel from an experimental point of view. Computational modeling studies are an alternative to understand epilepsy at a network level and generate new hypotheses regarding the basic mechanisms that lead to seizures
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